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Columbia University’s Data Science Institute Presents:
DATA SCIENCE DAY

Authors/Collaborators are listed in alphabetical order.



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Wednesday, April 6
 

8:00am

Registration
Please remember to bring your Eventbrite ticket with you. 

Wednesday April 6, 2016 8:00am - 9:00am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

8:50am

Welcome Remarks: Director of The Data Science Institute
Speakers
avatar for Kathy McKeown

Kathy McKeown

Director, Data Science Institute
A leading scholar and researcher in the field of natural language processing, McKeown focuses her research on big data; her interests include text summarization, question answering, natural language generation, multimedia explanation, digital libraries, and multilingual applications. Her research group's Columbia Newsblaster, which has been live since 2001, is an online system that automatically tracks the day's news, and demonstrates the... Read More →


Wednesday April 6, 2016 8:50am - 8:55am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

8:55am

Welcome Remarks: Dean of the The Fu Foundation School of Engineering and Applied Science
Speakers
avatar for Mary C. Boyce

Mary C. Boyce

Dean of Engineering, Columbia University
Mary C. Boyce is Dean of Engineering at The Fu Foundation School of Engineering and Applied Science at Columbia University in the City of New York and the Morris A. and Alma Schapiro Professor of Engineering. Prior to joining Columbia, Dean Boyce served on the faculty of the Massachusetts Institute of Technology (MIT) for over 25 years, leading the Mechanical Engineering Department from 2008 to 2013. | | Her research focuses on materials and... Read More →


Wednesday April 6, 2016 8:55am - 9:00am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

9:00am

Opening Keynote, Dan Doctoroff
The Coming Technological Revolution in Cities 
We’re on the brink of a historic period for cities around the world. By 2050, the population in cities will double, intensifying existing socioeconomic, public health and environmental problems. At the same time, innovations in technology can be used to design communities that are more efficient, responsive and resilient. In his presentation, Dan will be speaking about the coming technological revolution in cities, and how local governments across the globe are poised to use advanced connective technology and data analytics to drastically improve people’s lives and solve some of society’s most pressing issues. 

Speakers
avatar for Dan Doctoroff

Dan Doctoroff

Chairman and CEO, Sidewalk Labs
Dan Doctoroff is Chairman and CEO of Sidewalk Labs, the urban innovation company that he founded in partnership with Google.  Sidewalk Labs will develop products, services and platforms at the intersection of the physical and digital worlds to help make cities become more efficient, responsive, resilient and greener.  | | Dan was President and Chief Executive Officer of Bloomberg L.P., the leading provider of news and information to... Read More →


Wednesday April 6, 2016 9:00am - 9:45am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

9:45am

Mining Images, Speech, Text and Social Ties for Insights and Important Events

Shih-Fu Chang  | Exploring Multimedia Recognition Tools in Big Data Applications
Advances in computer vision and the growth of digital photos and videos have created new opportunities to integrate content-recognition tools with mobile apps and large-scale systems. If you want more information about a building, product or bottle of wine, it’s now possible to search the Web with an image on your phone. New 3D sensors and search tools allow users to scan real-world objects and find matching models to make new products. Emerging multimedia-recognition tools are making it possible to track and summarize breaking news from streaming video and social media. This technology is also embedded in smart search engines that can mine video footage from sporting events, roads and security cameras to flag key events, from touchdowns to traffic accidents to criminal activity. I will give an overview of the novel technologies we are developing and discuss open issues.

Julia Hirschberg | Applications for Detecting Emotion in Text and Speech
Identifying the emotional content of written and spoken language is increasingly useful in business, medicine and security. Large data sets of text and speech, including social media, interviews and phone conversations, can be used to train systems to detect consumer reactions to products and services (and to flag ‘fake’ reviews), to diagnose medical conditions such as depression, and identify deception in a wide variety of government, business and social service settings. Each application picks up subtle cues that may indicate whether a speaker is angry, happy, disgusted, afraid, sad or surprised. Similar approaches have been used to distinguish among personality traits, and to infer how tired, drunk or bored someone might be.

Kathy McKeown | Tracking Events Through Time: Objective and Personal Views
The chaos following Hurricane Sandy in 2012 brought home the need for a faster, more accurate way to filter the oceans of text streaming over social media and news sites during and after a crisis. We have been working on an automated method for monitoring and summarizing news as events unfold. Our method can flag new information as it becomes available, and generate updates. This can be extremely useful during emergencies as well as for tracking a wide variety of everyday events. In a related project, we’ve come up with a way to automatically identify the most compelling part of a personal narrative, what we call the “most reportable event.” I will discuss the natural language processing techniques that underlie this work, and future research directions.

Tian Zheng | Mapping Subpopulations within Big Networks
Estimating the size of stigmatized groups such as the homeless, people with HIV and commercial sex workers remains difficult, even in the digital age. Those belonging to marginalized subpopulations may be difficult to reach by phone, or in online surveys, or may simply prefer to keep sensitive personal information to themselves. Advances in network science are now allowing researchers to move past these obstacles to learn more about hard-to-reach demographic groups. My colleagues and I have developed a modeling framework to infer the size and other hidden features of subpopulations within a large study sample. Our method produces inferential results that are easy to interpret and relevant for visualizing, monitoring and understanding structures underlying large, complex networks.


Speakers
avatar for Shih-Fu Chang

Shih-Fu Chang

Senior Executive Vice Dean and Richard Dicker Professor of Telecommunications and Professor of Computer Science, Columbia Engineering
Shih-Fu Chang is Richard Dicker Chair Professor, Director of the Digital Video and Multimedia Lab, and Senior Executive Vice Dean of The Fu Foundation School of Engineering and Applied Science at Columbia University. He is an active researcher leading development of theories, algorithms, and systems for multimedia analysis and retrieval. In the last two decades, he and his students developed some of the earliest image/video search engines... Read More →
avatar for Julia Hirschberg

Julia Hirschberg

Percy K. and Vida L. W. Hudson Professor of Computer Science and Department Chair, Columbia Engineering
Julia Hirschberg is Percy K. and Vida LW Hudson Professor of computer science at Columbia University and chair of the Department. She does research in prosody, spoken dialogue systems, and emotional and deceptive speech. She received her PhD in Computer Science from the University of Pennsylvania in 1985.  She worked at Bell Laboratories and AT&T Laboratories -- Research from 1985-2003 as a Member of Technical Staff and as a... Read More →
avatar for Kathy McKeown

Kathy McKeown

Director, Data Science Institute
A leading scholar and researcher in the field of natural language processing, McKeown focuses her research on big data; her interests include text summarization, question answering, natural language generation, multimedia explanation, digital libraries, and multilingual applications. Her research group's Columbia Newsblaster, which has been live since 2001, is an online system that automatically tracks the day's news, and demonstrates the... Read More →
avatar for Tian Zheng

Tian Zheng

Associate Professor of Statistics, Graduate School of Arts and Sciences
Tian Zheng is associate professor of Statistics at Columbia University. She obtained her PhD from Columbia in 2002. Her research is to develop novel methods and improve existing methods for exploring and analyzing interesting patterns in complex data from different application domains. Her current projects are in the fields of statistical genetics, bioinformatics and computational biology, feature selection and classification for high... Read More →


Wednesday April 6, 2016 9:45am - 10:30am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

10:30am

Q&A
Attendees will have an opportunity to engage in conversation with the lightning talk spekers.

Wednesday April 6, 2016 10:30am - 10:35am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

10:35am

Break
Wednesday April 6, 2016 10:35am - 10:50am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

10:50am

Innovations to Keep Data Secure

Jason Healey | Building a Defensible Cyberspace
Cyber attacks top the list of national security threats and also pose a threat to our personal finances, as recent data breaches at banks, credit card companies and businesses have shown. One of the main reasons that cyber threats are escalating is that for decades it has been far easier to attack than defend. Columbia’s School for International and Public Affairs (SIPA) has convened a New York Cyber Task Force to bring together policymakers and technologists in academia, banks, and other industries, to determine how to reverse the problem so that a dollar of defense buys more than a dollar of attack. A defensible cyberspace has checks and balances and a broad set of stakeholders acting as stewards. It can adapt to changing conditions, recover quickly after failure and scale up solutions. I will discuss what technologies and policies have been most successful to date and what more is needed.

Tal Malkin | Secure Computation: Encrypted Search and Beyond
Secure computation is one of the most exciting achievements in cryptographic research in the last few decades. It allows mutually distrustful parties to jointly perform computations on private data without revealing any extraneous information. Once a theoretical field, secure computation is becoming increasingly more practical and relevant to real-world applications. I will discuss a private database management system that we have developed, Blind Seer. This system allows clients to perform a rich set of queries over an encrypted database while keeping the data and query hidden. Blind Seer runs efficiently on a 100-million record, 10-terabyte database — two to 10 times slower than running insecure MySQL queries on a non-encrypted database. 


Moderators
avatar for Austin Long

Austin Long

Associate Professor of International and Public Affairs, School of International and Public Affairs
Austin Long is an assistant professor, teaching security policy. Long previously worked as an associate political scientist for the RAND Corporation, serving in Iraq as an analyst and advisor to the Multinational Force Iraq and the U.S. military. He also worked as a consultant to MIT Lincoln Laboratory, on a study of technology and urban operations in counterinsurgency. Long is the author of Deterrence - From Cold War to Long War: Lessons... Read More →

Speakers
avatar for Jason Healey

Jason Healey

Senior Research Scholar, School of International and Public Affairs
Jason Healey is a Senior Research Scholar at Columbia University’s School for International and Public Affairs specializing in cyber conflict, competition and cooperation. Prior to this, he was the founding director of the Cyber Statecraft Initiative of the Atlantic Council where he remains a Senior Fellow. He is the editor of the first history of conflict in cyberspace, A Fierce Domain: Cyber Conflict, 1986 to 2012 and co-authored the... Read More →
avatar for Tal Malkin

Tal Malkin

Associate Professor of Computer Science, Columbia Engineering
Tal Malkin is an associate professor of Computer Science at Columbia University, where she directs the Cryptography Lab. She received her Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2000, and joined Columbia after three years as a research scientist in the Secure Systems Research Department at AT&T Labs - Research. Her research interests are in cryptography, security, complexity theory, and related... Read More →


Wednesday April 6, 2016 10:50am - 11:15am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

11:15am

Developing Algorithms that Know Your Likes and Dislikes Better Than You

Shipra Agrawal | Explore and Exploit: Because You May Not Know What You're Missing
To improve its movie recommendations to subscribers, Netflix looks at what subscribers liked in the past to predict future preferences. But that method leaves out movies subscribers might like even better but don’t know about. Amazon faces a similar problem in recommending products to its customers. Discovering the full range of possibilities involves a trade-off between exploration and exploitation of data. Many sequential decision making problems are rooted in this problem, including recommendation systems, online advertising, content optimization, revenue and inventory management, and even teaching computers to play games like Pong and Go. I will discuss how machine learning and optimization techniques can be combined to achieve near-optimal trade-offs between exploration and exploitation.

Olivier Toubia | Recommending Movies by Character Traits Featured
Current movie recommendation systems are largely based on viewers’ past preferences. We propose an alternative that taps into viewer preferences for stories that feature specific character traits, a finding documented in the media psychology literature. Borrowing from the positive psychology literature, we have developed a character-based classification system that is easy to interpret, communicate and act on. We have also developed a companion natural language processing tool that can infer character traits from movie summaries. In two online studies, we show that character traits are a strong predictor of what movies people like. Our results apply to films that achieve critical acclaim as well as box-office success. We show that character-based classification works for models that use content alone, and content with collaborative filtering, to predict viewer behavior.


Speakers
avatar for Shipra Agrawal

Shipra Agrawal

Assistant Professor of Industrial Engineering and Operations Research, Columbia Engineering
Profesor Shipra Agrawal is an Assistant Professor in the Department of Industrial Engineering and Operations Research. Her research spans several areas of optimization and machine learning, including data-driven optimization under partial, uncertain, and online inputs, and related concepts in learning, namely multi-armed bandits, online learning, and reinforcement learning. She is also interested in prediction markets and game theory... Read More →
avatar for Olivier Toubia

Olivier Toubia

Glaubinger Professor of Business, Columbia Business School
Olivier Toubia is the Glaubinger Professor of Business and the Faculty Director of the Lang Center for Entrepreneurship at Columbia Business School. His research focuses on various aspects of innovation (including idea generation, preference measurement, and the diffusion of innovation), social networks and behavioral economics. He teaches a course on Customer-Centric Innovation, a course (“Research to Revenue”) that... Read More →


Wednesday April 6, 2016 11:15am - 11:40am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

11:40am

Q&A
Attendees will have an opportunity to engage in conversation with the lightning talk spekers.

Wednesday April 6, 2016 11:40am - 11:45am
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

11:45am

Networking Lunch
Wednesday April 6, 2016 11:45am - 12:30pm
North Lobby Lerner

12:30pm

Measuring and Addressing Social and Environmental Problems in Cities

Donald Davis | Mining Yelp Reviews to Measure Segregation in New York City
Until they were dismantled in the mid-1960s, the segregationist Jim Crow laws in the southern United States severely limited social interactions among ethnic groups. Despite the Civil Rights Act and later reforms, the U.S. remains deeply segregated, even in northern cities like New York. While standard measures of segregation exist for residences, jobs, and schools, we currently have no way of measuring how segregated common public activities like going to restaurants is. By studying five years of Yelp reviews in New York City, my colleagues and I provide the first estimate of diversity in city restaurants. Early results suggest that dining patterns are also segregated, though not as markedly as in housing.

Xiaofan (Fred) Jiang  | Smart Systems for Monitoring Air Pollution and Personal Energy Use
Analyzing observations of the physical world can be a messy process. But the rise of sensors to measure air quality, ocean temperatures and any number of other changes is allowing us to study our environment and actions like never before. I will discuss two projects that use intelligent sensor systems to map the environment. In one, my colleagues and I combined inexpensive, custom-built Internet-connected sensors with cloud-based data analysis to measure and infer air-quality at city scales. In a second project, here at Columbia, my lab is combining building energy-use monitoring with location data to estimate an individual’s energy footprint to provide real-time feedback to cut energy use. 

Desmond Patton | Preventing Gang Violence through Social Media Analysis
Social media is often an extension of the street for gang-involved youth. They may taunt rival gang members, downplay shootings and brag about fights and drug deals. Sometimes the tough talk turns into real violence. To be able to intervene, social workers need to understand how likely a specific post on Twitter may lead to violence. To do so requires deciphering the coded language and culture of gang-involved youth. I have recently collaborated with social science researchers and data scientists to analyze Twitter posts by Chicago gang members. Our goal is to combine observations with natural language processing tools to detect and decode high-risk language. I will discuss our process and early results.


Moderators
avatar for Andrew Smyth

Andrew Smyth

Professor of Civil Engineering and Engineering Mechanics, Columbia Engineering
Andrew Smyth is a professor of civil engineering and engineering mechanics at Columbia Engineering. He specializes in structural health monitoring, using sensor information to determine the condition of critical infrastructure. Smyth has been involved with the sensor instrumentation and vibration analysis and remote monitoring of a large number of iconic long-span bridges and landmark buildings and museums. His research interests include... Read More →

Speakers
avatar for Donald Davis

Donald Davis

Ragnar Nurkse Professor of Economics and Department Chair, Graduate School of Arts and Sciences
Donald Davis has been a professor of economics at Columbia University since 1999. In 2001 he was appointed chairman of the Department of Economics at the University. Professor David's research interests include international trade, economic development in the open economy, microeconomic theory, and open economy macroeconomics. He has published extensively on these topics. Some of his recent works include "Bones, Bombs, and... Read More →
avatar for Xiaofan (Fred) Jiang

Xiaofan (Fred) Jiang

Assistant Professor of Electrical Engineering, Columbia Engineering
Xiaofan (Fred) Jiang is an Assistant Professor in the Electrical Engineering Department at Columbia University. Fred received his B.Sc. (2004) and M.Sc. (2007) in Electrical Engineering and Computer Science, and his Ph.D. (2010) in Computer Science, all from UC Berkeley. Before joining SEAS, he was Senior Staff Researcher and Director of Analytics and IoT Research at Intel Labs China. Fred’s research interests include cyber physical... Read More →
avatar for Desmond Patton

Desmond Patton

Assistant Professor of Social Work, School of Social Work
Dr. Desmond Upton Patton is an Assistant Professor at the Columbia School of Social Work and a Faculty Affiliate of the Social Intervention Group (SIG) and the Data Science Institute.  His research utilizes qualitative and computational data collection methods to examine how and why youth and gang violence, trauma, grief and identity are expressed on social media and the real world impact they have on well-being for low-income youth of... Read More →


Wednesday April 6, 2016 12:30pm - 1:05pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

1:05pm

The Moneyball Approach to Healthier Living

Hod Lipson | Data Smashing: Uncovering Order in Data Stream
From speech recognition to the discovery of new stars, almost all automated tasks involve comparing streams of data for similarities and outliers. Automated discovery methods, however, have not kept pace with the exponential growth in data. One reason is that most algorithms depend on humans to define what features to compare. Here, we propose a new way to match multiple sources of data streams without any prior learning. We show how this principle can be applied to challenging problems, including the interpretation of EEG patterns in epileptic seizures, the detection of abnormal heartbeats in ECG data and classifying astronomical objects from light measurements. Our data smashing principles produce results as accurate as algorithms developed by domain experts, and could open the door to understanding increasingly complex observations that experts don’t yet know how to interpret.

David Madigan | Observational Studies: Promise and Peril
Randomized experiments are the gold standard in measuring the effects of interventions in medicine, education, social science and other areas. In reality, researchers often rely on observational studies, leading to vast numbers of contradictory findings published in scholarly journals and widely disseminated through the media. Decision makers and the public assume that a rigorous peer-review process guarantees that these results are valid. This is not always so. Well-intentioned analysts make design choices, run analyses and publish their results overlooking the possibility that different choices may have produced entirely different results. I will provide an overview of the current state of the art in observational studies in healthcare and describe some promising research directions.

Olena Mamykina |  Predicting Blood-Glucose Levels to Manage Diabetes
Advances in personal health tracking promise to help individuals gain deep insights into their health and behavior. Yet, most health apps still rely on humans to identify trends, make discoveries and take action. In this research, we are building computational models and interactive decision-support tools to help type 2 diabetics improve their nutritional choices. Our decision-support tool forecasts how a planned meal will influence blood-glucose levels based on an individual’s physiology and past data. Early results suggest that this automated prediction tool may produce more accurate assessments than individuals or their healthcare providers can. 

Adler Perotte | Predicting Kidney Disease Progression with Large-Scale Patient Data
Columbia University coordinates a global network of health databases known as the Observational Health Data Science and Informatics (OHDSI) collaborative. With hundreds of millions of patient records, OHDSI allows researchers to look for large-scale patterns that can reveal new ways to identify and treat disease. In a recent study, my colleagues and I used observational health data to build a model to predict how likely a patient with stage 3 kidney disease, in which the kidney has lost half of its function, will progress to stage 4, with up to 90 percent loss. Our model, which incorporated patient lab test results and clinical records, outperformed models that did not include this information. Identifying patients at high risk for disease progression allows doctors to customize treatment that can stall or prevent its progression.


Speakers
avatar for Hod Lipson

Hod Lipson

Professor of Mechanical Engineering, Columbia Engineering
Hod Lipson is a roboticist who works in the areas of artificial intelligence and digital manufacturing. He and his students love designing and building robots that do what you’d least expect robots to do: Self replicate, self-reflect, ask questions, and even be creative.  Hod's research asks questions such as: Can robots ultimately design and make other robots? Can machines be curious and... Read More →
avatar for David Madigan

David Madigan

Executive Vice President for Arts and Sciences and Dean of the Faculty of Arts and Sciences, Professor of Statistics, Columbia University
David Madigan received a bachelor’s degree in Mathematical Sciences and a Ph.D. in Statistics, both from Trinity College Dublin. He has previously worked for AT&T Inc., Soliloquy Inc., the University of Washington, Rutgers University, and SkillSoft, Inc. He has over 100 publications in such areas as Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance and probabilistic graphical models. He is an elected... Read More →
avatar for Olena Mamykina

Olena Mamykina

Assistant Professor of Biomedical Informatics, College of Physicians and Surgeons
Olena Mamykina is an Assistant Professor of Biomedical Informatics in the Department of Biomedical Informatics at Columbia University. Her primary research interests reside in the areas of Biomedical Informatics, Human-Computer Interaction, Ubiquitous and Pervasive Computing, and Computer-Supported Collaborative Work. Her broad research interests include individual and collective cognition, sensemaking and problem-solving in the context... Read More →
avatar for Adler Perotte

Adler Perotte

Associate Research Scientist in Biomedical Informatics, College of Physicians and Surgeons
Dr. Adler Perotte is an Associate Research Scientist in the Department of Biomedical Informatics. Dr. Perotte’s primary research area is the development and application of statistical machine learning methods, including probabilistic graphical models for biomedical informatics. Dr. Perotte’s research interests are both in the development of novel methodology with broad applicability across domains and the application of such... Read More →


Wednesday April 6, 2016 1:05pm - 1:50pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

1:50pm

Q&A
Attendees will have an opportunity to engage in conversation with the lightning talk spekers.

Wednesday April 6, 2016 1:50pm - 2:00pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

1. Map of Demos and Posters

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

A Closed-Loop Brain-Computer Interface for Regulating Cognitive State During Dynamic Boundary Avoidance Tasks [D19]
Superior human performance in complex tasks such as piloting a modern jet fighter or driving a Formula 1 car requires goal-directed navigation while operating within narrow and dynamic physical constraints. a balancing act of maximizing task engagement while keeping autonomic stress response in check - a failure to do so can result in catastrophic accidents. The presented experimental setup represents a closed-loop brain-computer interface system that infers cognitive workload and provides feedback to achieve a reduction in task-induced arousal/stress with the aim to increase performance during high workload boundary avoidance tasks (BAT).

Demo/Poster Presenter
avatar for Josef Faller

Josef Faller

Postdoctoral Research Scientist in Biomedical Engineering, Columbia Engineering
Josef Faller received his B.Sc. and M.S. in Computer Science from Vienna University of Technology (2007, 2009) and his Ph.D. in Computer Science from Graz University of Technology (2015). His research focuses on neuroimaging and brain machine interfaces.
avatar for Sameer Saproo

Sameer Saproo

Postdoctoral Research Scientist in Biomedical Engineering, Columbia Engineering
Sameer Saproo received his B.E. in Information Technology from the Mumbai University (2003), his M.S. in Computer Science from the UC Irvine (2007), and Ph.D. in Cognitive Neuroscience from the UC San Diego (2012). His research focuses on neural information processing, neuroimaging, visual attention, and brain machine interfaces.
avatar for Victor Shih

Victor Shih

PhD Candidate in Biomedical Engineering, Columbia Engineering
Victor Shih received his B.S. in Biomedical Engineering and Electrical and Computer Engineering from Duke University (2012) and his M.S. in Biomedical Engineering from Columbia University (2014). His research focuses on computational neural modelling, artificial intelligence, and brain machine interfaces.

Demo/Poster Collaborator
avatar for Paul Sajda

Paul Sajda

Professor of Biomedical Engineering, Radiology (Physics) and Electrical Engineering, Columbia University
Paul Sajda received his B.S. in Electrical Engineering from MIT (1989) and his M.S. and Ph.D. in Bioengineering from the University of Pennsylvania (1992, 1994). In 1994 he joined the David Sarnoff Research Center where he went on to become the Head of the Adaptive Image and Signal Processing Group. He is currently a Professor in the Departments of Biomedical Engineering, Electrical Engineering and Radiology at Columbia University where... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

A Unified Tool to Explore and Build Patient Cohorts [D16]
Observational Health Data Sciences and Informatics (OHDSI) is an open, multi-stakeholder, interdisciplinary collaborative whose goal is to create and apply open-source large-scale data analytic solutions to leverage the value of observational health data to improve health care globally. OHDSI spans an international network of researchers and health databases worldwide and is centrally coordinated at Columbia University. Currently, with a goal to reach 1,000,000,000+ patient records, the growing network of collaborators consists of 100+ academic, industrial, and regulatory researchers.    This year, the OHDSI community is showcasing a new open-source tool called ATLAS. It is a web application that attempts to integrate features from various OHDSI applications into a single cohesive experience for researchers. It will enable researchers to quickly test hypotheses. ATLAS allows researchers to explore summary statistics on various OHDSI databases, search medical terminologies in order to define clinical concepts, and define and visualize cohorts of interests.

Demo/Poster Presenter
avatar for Karthik Natarajan

Karthik Natarajan

Assistant Professor of Biomedical Informatics, College of Physicians and Surgeons
Dr. Karthik Natarajan is an Assistant Professor in the Department Biomedical Informatics at Columbia University Medical Center. He received his BS in computer science at the University of Texas at Austin. After working in the technology sector for some time, he went on to obtain his PhD in biomedical informatics at Columbia University. Dr. Natarajan’s research interests are in operationalizing clinical informatics solutions. His specific... Read More →
avatar for Mark Velez

Mark Velez

Clinical Research Programmer Analyst in Biomedical Informatics, College of Physicians and Surgeons
TA

Taha Abdul-Basser

Program Analyst and Software Developer in Biomedical Informatics, College of Physicians and Surgeons

Demo/Poster Collaborator
avatar for Adler Perotte

Adler Perotte

Associate Research Scientist in Biomedical Informatics, College of Physicians and Surgeons
Dr. Adler Perotte is an Associate Research Scientist in the Department of Biomedical Informatics. Dr. Perotte’s primary research area is the development and application of statistical machine learning methods, including probabilistic graphical models for biomedical informatics. Dr. Perotte’s research interests are both in the development of novel methodology with broad applicability across domains and the application of such... Read More →
avatar for Sumitra Sengupta

Sumitra Sengupta

Associate Professor of Biomedical Informatics; Vice Chair of Biomedical Informatics; Director, NYP, Biomedical Informatics, Columbia University
Dr. Soumitra Sengupta is an Associate Professor of Biomedical Informatics at Columbia University and leads a clinical information development team providing informatics services to NewYork-Presbyterian Hospital. Additionally, he participates in technical and system architecture functions in Information Technology at the Medical Center and the Hospital. He earned a BE degree in electrical and electronics engineering at the Birla Institute of... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Agolo: The Future of Search [D7]
Users are inundated every day by an exponentially increasing amount of unstructured data in reports, filings, articles, social media, emails and chat. Agolo builds proprietary summarization technology for business intelligence that improves accuracy by 4x. Agolo transforms unstructured data into topical summaries at machine scale. Summarization is the first step in Agolo's mission to build a next generation search platform that goes beyond the 10 blue links.

Demo/Poster Presenter
avatar for Julian Norton

Julian Norton

Head of User Experience, Agolo
Julian Norton leads the user experience and design at Agolo. He uses both qualitative and quantitative research to guide product development. Working exclusively at technology focused-startups, Julian has a unique skill set of experience and interaction design. Julian focuses on identifying and understanding the needs of the user to help shape Agolo. He has a BFA in Graphic Design from Purchase College, with post-graduate studies at NYU and SVA.
avatar for Prem Ganeshkumar

Prem Ganeshkumar

Natural Language Processing Engineer, Agolo
Prem leads the development of summarization technology at Agolo. Summarization is the first step in Agolo's mission to build a next generation enterprise search platform that goes beyond the 10 blue links. | Prior to Agolo, Prem received a Master's in Computer Science from Columbia University, a Bachelor's in Computer Science from University of Michigan and was a software engineer at Amazon.com.

Demo/Poster Collaborator
MA

Mohamed AlTantawy

Chief Technology Officer, Agolo


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

AMuSe: Large-scale WiFi Video Distribution [D34]
Currently, wireless video distribution cannot be provided in crowded venues due to limited resources. In our  recent papers we proposed AMuSe, a scalable system for WiFi multicast video delivery. The system includes a scheme for dynamic selection of a subset of the receivers as feedback nodes and a rate adaptation algorithm MuDRA that maximizes the channel utilization while meeting QoS requirements. We implemented AMuSe in the ORBIT testbed and evaluated its performance with 150-200 nodes. We present a dynamic web-based application that demonstrates the operation of AMuSe based on traces collected on the testbed in several experiments. The application allows to compare the performance of AMuSe with other multicast schemes and evaluate the performance of video delivery.

Demo/Poster Presenter
avatar for Craig Gutterman

Craig Gutterman

PhD Student in Electrical Engineering, Columbia Engineering
Craig Gutterman graduated with B.S. degrees in Electrical Engineering from Rutgers University in May 2012 and M.S. in Electrical Engineering from Columbia University in February 2014. He is currently working towards his Ph.D. at Columbia University. His interests include mobile and wireless networks, optimization algorithms, and data science. His research focuses on analyzing data and developing algorithms to improve... Read More →
avatar for Gil Zussman

Gil Zussman

Associate Professor of Electrical Engineering, Columbia Engineering
Gil Zussman received the B.Sc. degree in Industrial Engineering and Management and the B.A. degree in Economics (both summa cum laude) from the Technion – Israel Institute of Technology in 1995. He received the M.Sc. degree (summa cum laude) in Operations Research from Tel-Aviv University in 1999 and the Ph.D. degree in Electrical Engineering from the Technion – Israel Institute of... Read More →
avatar for Timothy Goodwin

Timothy Goodwin

Undergraduate Student in Computer Science, Columbia Engineering
Timothy Goodwin is a third year computer science major at Columbia Engineering. He is broadly interested in multimedia and communication technologies and has been pursuing these interests with the Wireless and Mobile Networking Laboratory. He is currently developing wireless feedback applications on Android for the lab's Adaptive Multicast Services project.
avatar for Varun Gupta

Varun Gupta

PhD Candidate in Electrical Engineering, Columbia Engineering
Varun Gupta completed his undergraduate studies in Electrical Engineering at IIT Delhi and received his M.S. in Electrical Engineering at Columbia University in October 2012. He is currently working towards his Ph.D. at Columbia University. His research interests include network performance evaluation, stochastic modeling, wireless networks, and datacenter networks.
avatar for Yigal Bejerano

Yigal Bejerano

Member of Technical Staff, Mathematics of Networks and Systems Research Department, Bell Labs, Nokia
Throughout his professional life Bejerano has tried to combine applied and fundamental research in the fields of networking and algorithms. In Bell-Labs he had the privilege to work with many excellent researchers on various design, management and optimization problems in the context of wireless and wired networks. He joint Bell-Labs in 2000, after finishing his  Ph.D. studies at the Electrical Engineering Dept. under the... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

An Introduction to Stan [D1]
"Stan had been successfully utilized in Pharma, Sports Analytics, Financial Econometrics, Publishing and other verticals.
The Stan project includes:
 (1) a computer language for users to model data with unprecedented flexibility
 (2) a variety of gradient-based algorithms to estimate the parameters of the model
 (3) a math library that supports auto-differentiation to calculate the gradients
 (4 interfaces from shells, R, Python, Julia, Matlab, and Stata
 (5) a webapp to visualize and diagnose the estimation output
 (6) a community of developers (mostly based at Columbia) and users all over the world.
Our demo will focus on estimating models that have been pre-compiled and made available through the R interface, including visualizing and diagnosing the output via the webapp and comparing the expected loss across models when predicting new data. Please see chapter 1 of
http://xcelab.net/rmpubs/rethinking/Statistical_Rethinking_sample.pdf
which is part of a recently-published textbook describing how to do data analysis using Stan.
"

Demo/Poster Presenter
avatar for Alp Kucukelbir

Alp Kucukelbir

Postdoctoral Research Scientist, Data Science Institute
Alp Kucukelbir develops statistical machine learning algorithms and he uses probabilistic programming to develop scalable and robust inference techniques. He enjoys working on applications in structural biology. He is currently working with David Blei and collaborates closely with Andrew Gelman on the Stan probabilistic programming system. Kucukelbir obtained his... Read More →
avatar for Ben Goodrich

Ben Goodrich

Lecturer in the Discipline of Political Science, Columbia University
Ben Goodrich is a core developer of Stan, which is a collection of statistical software for Bayesian estimation of models, and is the maintainer of the corresponding rstan and rstanarm R packages. He teaches in the political science department and in the Quantitative Methods in the Social Sciences master's program at Columbia University.
avatar for Daniel Lee

Daniel Lee

Staff Associate, Institute for Social and Economic Research
Daniel Lee is a statistical researcher affiliated with ASC, working for Andrew Gelman. Research includes new MCMC algorithms and applied Bayesian models.
avatar for Dustin Tran

Dustin Tran

PhD Candidate in Computer Science, Columbia Engineering
Dustin Tran is Ph.D. student in Computer Science at Columbia, where he is advised by David Blei and Andrew Gelman. He works in the fields of Bayesian statistics and machine learning and his research interests include general-purpose inference algorithms, Bayesian nonparametric statistics and hierarchical models, and causal inference. Tran is also a member of the Blei Lab and the Stan development team. He... Read More →
avatar for Eric Novik

Eric Novik

Founder and CEO, Stan Group Inc.
Eric is founder and CEO of Stan Group Inc. , the company that is dedicated to spreading the joys of Bayesian modeling and the Stan language (mc-stan.org) to the masses. | | Prior to Stan Group, Eric was a Data Scientist at TIBCO Spotfire where he built statistical applications for customers in Financial Services, Energy, Pharma, and Consumer Goods Sectors. Prior to TIBCO, he was a Statistical Consultant at Random House where he built pricing... Read More →
avatar for Jonah Gabry

Jonah Gabry

Staff Associate, Institute for Social and Economic Research and Policy
Jonah is a researcher in statistics affiliated with Columbia's Applied Statistics Center and working with Andrew Gelman and the Columbia Population Research Center. He also develops software tools for applied researchers as a member of the Stan Development Team.

Demo/Poster Collaborator
avatar for Bob Carpenter

Bob Carpenter

Associate Research Scientist, Institute for Social and Economic Research and Policy
Bob Carpenter is a research scientist in computational statistics (Columbia University). He designed the Stan probabilistic programming language and is one of the Stan core developers. Bob has a Ph.D. in cognitive and computer science (University of Edinburgh), worked as a professor of computational linguistics (Carnegie Mellon University), an industrial researcher and programmer in speech recognition and natural language processing (Bell Labs... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Bringing Large and Diverse Datasets to Mobile Devices for Public Education [D26]
Two Columbia University apps for the mobile smart phone and tablet (Earth Observer App and Polar Explorer: Sea Level App) offer interactive exploration of large earth and environmental datasets (terabytes) with the objective of providing an enhanced public understanding of regional and global climate change. The land and ocean surfaces and the atmosphere are updated monthly from satellite remote sensing.  The increase in the temperature of the ocean interior that drives thermal expansion and the rise of sea level and the flow of ice sheets on Antarctic and Greenland towards the coasts are visualized in yearly steps back to the 1960's. A finger tap anywhere in the imagery presents descriptive text. Earth Observer is designed as a topic driven atlas, whereas the user of Polar Explorer: Sea Level is guided to seek answers to questions. Currently the apps have about 100,000 users.

Demo/Poster Presenter
avatar for Bill Ryan

Bill Ryan

Special Research Scientist, Lamont-Doherty Earth Observatory
avatar for David Porter

David Porter

Postdoctoral Research Scientist, Lamont-Doherty Earth Observatory
David Porter tudied atmospheric and oceanographic sciences and is interested in the interactions between Earth system components in the polar regions. His current research is focused on ice-ocean interaction in Greenland looking at glacier 'pairs' and what is causing them to behave differently. Are warming ocean waters responsible for the increase in mass loss of marine-terminating glaciers worldwide?
avatar for Margie Turrin

Margie Turrin

Education Coordinator, Lamont-Doherty Earth Observatory
Margie Turrin is Education Coordinator at Columbia University's Lamont-Doherty Earth Observatory where she develops and runs science education projects for groups from informal community education, to K12 and undergraduate students. Her projects and publications range from engaging students and the public in the polar regions, understanding our Earth and environment, human interactions and impacts on their environment, Hudson River education... Read More →

Demo/Poster Collaborator
avatar for Andrew Goodwillie

Andrew Goodwillie

Data Systems Manager, Lamont-Doherty Earth Observatory
After a degree in geophysics from Durham (UK) and graduate work at Oxford, Andrew Goodwillie spent eight years at Scripps Institution of Oceanography, where he continued working on his  research interests in lithospheric flexure using shipboard gravity and bathymetry, the construction of satellite-derived geoid and gravity fields, and, the creation of gridded depth databases from echo-soundings and contours. He also spent five of... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Citizen Sensors for Structural Health Monitoring [D20]
A crowdsourcing-based, SHM-oriented smartphone application, namely, Citizen Sensors for SHM (CS4SHM) is demonstrated. The demonstration includes vibration measurement from a small-scale structural model, wireless data submission to the web server, and viewing the identification results online. CS4SHM enables users to collect vibration data from smartphone sensors, extract the time history in text format, and submit the data via a web view connected to an online server. The vibration time history received by the server is automatically processed from the time to the frequency domain via Discrete Fourier Transform (DFT). In this way, the server determines the peak frequency and stores the results as well as the raw input data for further post-processing uses. Monitoring the modal identification results over time allows users to notice changes in dynamic characteristics of a structure.

Demo/Poster Presenter
avatar for Ekin Ozer

Ekin Ozer

PhD Candidate in Civil Engineering and Engineering Mechanics, Columbia Engineering
Ekin Ozer got his BSc and MSc degrees from Bogazici University, Department of Civil Engineering, in 2009 and 2012, respectively. He continues his studies as a PhD candidate in Department of Civil Engineering and Engineering Mechanics, Columbia University. | His research interests include structural health monitoring (SHM), structural dynamics, system identification, model updating, reliability estimation, earthquake engineering, digital signal... Read More →

Demo/Poster Collaborator
avatar for Maria Q. Feng

Maria Q. Feng

Renwick Professor of Civil Engineering, Columbia Engineering
Maria Feng is Renwick Professor at the Department of Civil Engineering and Engineering Mechanics. Her research is on the forefront of multidisciplinary science and engineering in sensors, structural health monitoring, intelligent structures and system control for smart city applications, with an emphasis on structural safety and system resilience against natural and man-made hazards. She has made a number of original contributions to the... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Computer Assisted Neighborhood Visual Assessment System (CANVAS) [D21]
CANVAS is a web-based tool for systematically and reliably assessing neighborhood built, pedestrian and road way conditions using Google Street View.  Neighborhood auditing (aka Systematic Social Observation), a research technique where trained auditors visit neighborhoods to collect observational data on street level built and social environment conditions, has long been used in urban sociology, social epidemiology,  planning and design research and traffic safety research.  However, the approach is quite expensive with travel time costing more than actual on the ground research time. CANVAS obviates the need for travel and provides a uniform and centralized means of conducting neighborhood audits across larger areas and with higher density of observations than can be achieved using in-person audit methods.   CANVAS allows a research method that previously was used on a boutique scale to be deployed on an industrial scale.  Research using CANVAS to understand pedestrian injury risk in NYC was recently published.

Demo/Poster Presenter
avatar for Andrew Rundle

Andrew Rundle

Associate Professor of Epidemiology, Mailman School of Public Health
Dr. Rundle's research focuses on the determinants of sedentary lifestyles and obesity and the health related consequences of these conditions. Dr. Rundle Co-directs the Built Environment and Health Research Group (beh.columbia.edu), a trans-disciplinary team of researchers studying how neighborhood built and social environments influence health, particularly physical activity and obesity risk. His work on urban design and... Read More →

Demo/Poster Collaborator
avatar for Gina Lovasi

Gina Lovasi

Assistant Professor of Epidemiology, Mailman School of Public Health
Gina S. Lovasi is an assistant professor in Epidemiology at the Columbia University Mailman School of Public Health.  Her research examines how local policies and initiatives influence cardiovascular and respiratory health, seeking to understand whether the anticipated health benefits have been realized and to explore any unanticipated health effects.  She works to incorporate GIS into a range of health-related research projects in... Read More →
avatar for Stephen Mooney

Stephen Mooney

NIH Pre-Doctoral Cancer Training Fellow in Epidemiology, Mailman School of Public Health
Stephen Mooney is an epidemiology doctoral student at Columbia University Mailman School of Public Health.  His research interests include spatial analytic techniques, epidemiologic methods, and physical activity.
avatar for Kathryn Neckerman

Kathryn Neckerman

Senior Research Scientist, School of Social Work
Kathryn Neckerman is Associate Director of Columbia’s Health & Society Scholars Program. Neckerman is a sociologist who has conducted research on the role of race and ethnicity in urban labor markets, family structure, and education. She is the author of Schools Betrayed: Roots of Failure in Inner-City Education (Chicago, 2007) and the editor of Social Inequality (Russell Sage, 2004) and (with Peter Bearman and Leslie Wright) After... Read More →
avatar for Julien Teitler

Julien Teitler

Associate Professor of Social Work and Sociology / Director of the Columbia University Social Indicators Survey Center., Department of Sociology, Columbia University
Julien Teitler is Associate Professor of Social Work and Sociology and Director of the Columbia University Social Indicators Survey Center. Teitler’s research focuses on the effects of social environments and policies on families and children, on health disparities, and on research methodology. Teitler teaches classes in Human Behavior and the Social Environment and in Research Methodology. | Professor Teitler’s research... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing Toolkit [D3]
In today’s data-driven world, programmers routinely incorporate user data into complex algorithms, heuristics, and application pipelines. While often beneficial, this practice can have unintended and detrimental consequences, such as the discriminatory effects identified in Staples’ online pricing algorithm and the racially offensive labels recently found in Google’s image tagger.    We argue that such effects are bugs that should be tested for and debugged in a manner similar to functionality, performance, and security bugs. We developed FairTest, a testing toolkit that detects unwarranted associations between an algorithm’s outputs (e.g., prices or labels) and user subpopulations, including protected groups (e.g., defined by race or gender). FairTest reports any statistically significant associations to programmers as potential bugs, ranked by their strength and likelihood of being unintentional, rather than necessary effects.    In the demo, we will show how FairTest can be used to identify unfair disparate impact, offensive labeling, and disparate rates of algorithmic error in data-driven applications. For example, we will show how FairTest can reveal subtle biases against older populations in the distribution of error in a real predictive health application, and offensive racial labeling in an image tagger akin to Google's. 

Demo/Poster Presenter
avatar for Daniel Hsu

Daniel Hsu

Assistant Professor of Computer Science, Columbia Engineering
Daniel Hsu is an assistant professor in the Department of Computer Science and a member of the Data Science Institute, both at Columbia University. Previously, he was a postdoc at Microsoft Research New England, and the Departments of Statistics at Rutgers University and the University of Pennsylvania. He holds a Ph.D. in Computer Science from UC San Diego, and a B.S. in Computer Science and Engineering... Read More →
avatar for Roxana Geambasu

Roxana Geambasu

Assistant Professor of Computer Science, Columbia Engineering
Roxana Geambasu is an assistant professor in the Computer Science Department at Columbia University. She is interested in computer systems in a broad sense, including distributed systems, the Web, security and privacy, operating systems, and databases. More specifically, her  current research focuses on the challenges and opportunities created by today's emerging technologies, such as the Web, cloud computing, and powerful mobile... Read More →
avatar for Vaggelis Atlidakis

Vaggelis Atlidakis

PhD Candidate in Computer Science, Columbia Engineering
Vaggelis is a Computer Science Ph.D. student at Columbia University in the city of New York. He is a member of the Software Systems Laboratory and his advisors are Roxana Geambasuand Jason Nieh. Before joining Columbia Vaggelis was a member of the European Organization for Nuclear Research (CERN), IT Department. At CERN he contributed to the project Agile Infrastructure, which provides Infrastructure as a Service... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

FindYou: A Personal Location Privacy Auditing Tool [D11]
Smartphones and apps provide us with extremely useful location-based services. When we use these services, we let the service providers know where we are and when we're there. This data can be used to infer many useful but potentially sensitive attributes of users. This work lets users import data collected about them from a few popular location-based services. They can visualize this data, and additionally see some basic inferences we make about them based on this data. This can be used as a location privacy audit system, where users can realize what they're letting the world know and take appropriate actions. Eventually, we hope to turn it into a system where users can donate their data to help us learn about the relationship between the demographics and the places people visit.

Demo/Poster Presenter
avatar for Christopher Riederer

Christopher Riederer

PhD Candidate in Computer Science, Columbia Engineering
SH

Stephanie Huang

Undergraduate Student in Computer Science, Columbia Engineering

Demo/Poster Collaborator
avatar for Augustin Chaintreau

Augustin Chaintreau

Assistant Professor of Computer Science, Columbia Engineering
Augustin Chaintreau is an Assistant Professor of Computer Science at Columbia University. His research, by experience in industry, is centered on real world impact and emerging computing trends, while his training, in mathematics and theoretical computer science, is focused on guiding principles. He designed and proved the first reliable, scalable and network-fair multicast architecture while working at IBM during his Ph.D. He... Read More →
DE

Daniel Echikson

Undergraduate Student in History, Columbia College

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

FlexICoN: A Self-Interference-Cancelling Full-Duplex Radio Enabling Next-Generation Wireless Communications [D33]
Full-duplex (FD) wireless is an emergent wireless communication paradigm that can greatly improve wireless network performance but is also fraught with fundamental challenges. FD operation involves simultaneous transmission and reception at the same frequency, resulting in the tremendous transmitter self-interference at the receiver input. This self-interference can be a billion times more powerful than the desired signal to be received. In this demo, an FD radio that consists of a software-defined radio, an analog self-interference cancellation circuitry, and a circulator with an antenna will be presented. We will demonstrate simultaneous transmission and reception at the same frequency channel with self-interference suppression across the antenna, analog, and digital domains to achieve cancellation with nearly one part-per-billion accuracy. This demo is part of the FlexICoN (http://flexicon.ee.columbia.edu/) project at Columbia University.

Demo/Poster Presenter
avatar for Jelena Marasevic

Jelena Marasevic

PhD Candidate in Electrical Engineering, Columbia Engineering
Jelena Marasevic is a Ph.D. student at the Department of Electrical Engineering, Columbia University, under Professor Gil Zussman's advising. She graduated with the B.Sc. degree from University of Belgrade, School of Electrical Engineering, in 2011 and started her M.S./Ph.D. program at Columbia University right after. Her main research interests are in the area of combinatorial and stochastic network optimization, with applications... Read More →
avatar for Nicole Grimwood

Nicole Grimwood

Undergraduate Student in Electrical Engineering, Columbia Engineering
avatar for Tingjun Chen

Tingjun Chen

PhD Candidate in Electrical Engineering, Columbia Engineering
Tingjun Chen is second year Ph.D. Student in Electrical Engineering. He works at the Wim.Net Labwith Prof. Gil Zussman on algorithms, optimization, and implementation in wireless, sensor, and energy harvesting networks. He graduated with a B.Eng. degree in Electronic Engineering from Tsinghua University in 2014, and received his M.S. degree in Electrical Engineering from Columbia University in... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Frequency-Translational Quadrature-Hybrid Receivers for Frequency-Agile Massive Carrier Aggregations [D28]
To accommodate the predicted 1000x data throughput growth in 5G communications, massive carrier aggregation (CA) is becoming one of the key technologies to boost system bandwidth.  Different regional spectrum policies lead to a large number of band combinations and challenge the conventional receiver architecture. Filter bank designs become extremely complex and costly. Thus, we demonstrate a new RF receiver architecture named frequency-translational quadrature-hybrid (FTQH) receivers for massive carrier aggregation. The FTQH receivers breaks the constraint between antenna impedance matching and the LNA input impedance by marrying design techniques of microwave circuits and CMOS analog IC. This facilitates the use of highly reflective LNAs and voltage domain wideband RF signal splitting. In this demo setup, three FTQH receivers are connected as an RF daisy chain to support as much as six-band downlink carrier aggregation. Six modulated signals are generated, received and analyzed in real time to demonstrate frequency-agile massive carrier aggregations. 

Demo/Poster Presenter
avatar for Jianxun Zhu

Jianxun Zhu

MS Student in Electrical Engineering, Columbia Engineering
Jianxun Zhu is a second year masters student of Columbia University, majored in Electrical Engineering. He is currently conducting research in Columbia Integrate System Laboratory (CISL) Kinget Group, under the guidance of Professor Peter Kinget.
avatar for Peter Kinget

Peter Kinget

Professor of Electrical Engineering, Columbia Engineering
Peter R. Kinget received an engineering degree in electrical and mechanical engineering and the Ph.D. in electrical engineering from the Katholieke Universiteit Leuven, Belgium. He has worked in industrial research and development at Bell Laboratories, Broadcom, Celight and Multilink before joining the faculty of the Department of Electrical Engineering, Columbia University, NY in 2002. He is also a consulting expert on patent litigation and a... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

HARVEST: A Longitudinal Patient Record Summarization System at the Point of Care [D24]
As more and more observations are recorded in patient records, providers face an overwhelming amount of complex data points, with little time for making sense of them all. This phenomenon of information overload has been observed in primary and specialty care, during hospital admissions, and in the emergency room. One of the promises of the electronic health record is to support clinicians at the point of care. Unfortunately, it seldom provides effective cognitive support. HARVEST is an interactive, problem-oriented patient record summarization system. It innovates in three ways: (i) it extracts content from the patient notes, where key clinical information resides; (ii) it aggregates and presents information from multiple care settings, including inpatient, ambulatory, and emergency department encounters; and (iii) it is integrated into the electronic health record at NewYork-Presbyterian Hospital.

Demo/Poster Presenter
avatar for Marc Sturm

Marc Sturm

IT Director, New-York Presbyterian Hospital
I am an IT Director at NYP Data Analytics team. I have been working in IT for over 20 years, and in Health Care for over 10 years. I am responsible of the Big Data and Data Science project at the hospital.
avatar for Sharon Lipsky Gorman

Sharon Lipsky Gorman

Programmer Analyst in Biomedical Informatics, College of Physicians and Surgeons
Sharon works for the Department of Biomedical Informatics at Columbia University. She is one of the core developers and designers of HARVEST, a longitudinal patient record summarization system for supporting clinicians at the point of care. Her research interests include data visualization and machine learning. | | Sharon holds a M.S. in computer science from Polytechnic Institute of New York and an M.A. from Columbia University in biomedical... Read More →

Demo/Poster Collaborator
avatar for Noemie Elhadad

Noemie Elhadad

Associate Professor of Biomedical Informatics, College of Physicians and Surgeons
Prof. Elhadad's research is in biomedical informatics, natural language processing, and data mining. She develops techniques that aim to support clinicians, patients, and health researchers in their information workflow by automatically extracting and making accessible information from unstructured, large clinical datasets (e.g., the electronic patient record) and patient platforms (e.g., online health communities). Her research relies on... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Heisenbyte: Thwarting Memory Disclosure Attacks using Destructive Code Reads [D4]
Vulnerabilities that disclose executable memory pages en- able a new class of powerful code reuse attacks that build the attack payload at runtime. In this work, we present Heisenbyte, a system to protect against memory disclosure attacks. Central to Heisenbyte is the concept of destructive code reads – code is garbled right after it is read. Garbling the code after reading it takes away from the attacker her ability to leverage memory disclosure bugs in both static code and dynamically generated just-in-time code. By leveraging existing virtualization support, Heisenbyte’s novel use of destructive code reads sidesteps the problem of incomplete binary disassembly in binaries, and extends protection to close-sourced COTS binaries, which are two major limitations of prior solutions against memory disclosure vulnerabilities. Our experiments demonstrate that Heisenbyte can tolerate some degree of imperfect static analysis in disassembled binaries, while effectively thwarting dynamic code reuse exploits in both static and JIT code, at a modest 1.8% average runtime overhead due to virtualization and 16.5% average overhead due to the destructive code reads.

Demo/Poster Presenter
avatar for Adrian Tang

Adrian Tang

PhD Candidate in Computer Science, Columbia Engineering
Adrian is a PhD student who joined the IDS Lab in Fall 2012. His interests include vulnerability research, malware analysis and detection. He is currently researching in hardware-oriented techniques to detect malware attacks

Demo/Poster Collaborator
avatar for Simha Sethumadhava

Simha Sethumadhava

Associate Professor of Computer Science, Columbia Engineering
Simha Sethumadhavan is an Associate Professor of Computer Science at Columbia Engineering. He is the founding director of the Computer Architecture and Security Technologies Lab (CASTL) at Columbia University. Sethumadhavan’s research interests are in hardware security, hardware support for security and privacy and energy-efficient computing. He has been recognized with an NSF CAREER award (2011), a top paper award (2004) and a teaching... Read More →
avatar for Salvatore Stolfo

Salvatore Stolfo

Professor of Computer Science, Columbia University
Salvatore J. Stolfo is Professor of Computer Science at Columbia University. He received his Ph.D. from NYU Courant Institute in 1979 and has been on the faculty of Columbia ever since. He won an IBM Faculty Development Award early in his academic career in 1983. He has published several books and well over 250 scientific papers since then, several winning best paper awards, in the areas of parallel computing, AI knowledge-based systems, data... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

How Technology Harnesses Science and Data to Give Answers to Decision-Makers [D22]
Global risk of rainfall-related disasters? How El Niño impacts rainfall globally? Risk of malaria in Africa? Risk of famine in the Philippines? Rice production risk in Bicol, the Philippines? Risk of fire in Indonesia? How will seasonal rainfall shift in the upcoming seasons globally? What matters: global warming or year-to-year variability?   So many questions, one answer: the International Research Institute for Climate and Society (IRI) Data Library (DL) and Maprooms. Get the answers to those questions (and more) for yourself by surfing the IRI Maprooms. Tailor your analysis and generate maps and graphs online, on the fly. An IRI DL expert will facilitate your exploration by telling you how technology enables the harnessing of science and data to deliver information to decision-makers. And, why not, start your own program online to make your own analysis of one or more of the hundreds datasets available in the DL.

Demo/Poster Presenter
avatar for John del Corral

John del Corral

Senior Staff Associate, Earth Institute, The International Research Institute for Climate and Society
After receiving his computer science degree from the Univ. of Colorado in 1983, John del Corral joined the EPA-funded Acid Deposition Modeling Project, headed by Julius Chang, at the National Center for Atmospheric Research. He participated in the Regional Acid Deposition Model (RADM) model development and analysis of model results, moving with the project to the Atmospheric Sciences Research Center at SUNY, Albany in 1987. In 1991, del Corral... Read More →
avatar for Michael Bell

Michael Bell

Senior Staff Associate, Earth Institute, The International Research Institute for Climate and Society
Michael Bell studied meteorology at the University of Oklahoma and graduated with bachelor’s and master’s degrees in 1994 and 2001, respectively. His master’s work involved the study of the decadal and interannual variability of West African rainfall disturbance lines. He joined the IRI in 2001. Bell’s research and academic interests include rainfall variability in West Africa, drought, water resources sustainability... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Hybrid Analog-Digital Computing for Solving Nonlinear Systems [D32]
"Due to the anticipated slowdown of speed and efficiency improvements in integrated circuits, researchers are looking for new scalable ways to get useful computation with existing silicon technology. Our work explores using analog electronic circuits to assist conventional digital computers to obtain high performance and low energy computation.
Our prototype analog co-processor solves nonlinear and linear systems of equations, delivering approximate solutions which are useful in physical simulations and machine learning tasks. Commonly perceived downsides of analog computing, such as low precision and accuracy, limited problem sizes, and difficulty in programming are all compensated for using methods we discuss. Based on our findings, small-scale uses of analog computing can bring efficient physics simulation to energy-efficient, Internet-of-Things devices. On the other hand, large-scale uses of analog computing can speed up the training of machine learning applications.
"

Demo/Poster Presenter
avatar for Yipeng Huang

Yipeng Huang

PhD Candidate in Computer Science, Columbia Engineering
Yipeng is a fourth year PhD student in computer science. | | Yipeng Huang received the B.S. degree in computer engineering in 2011, and M.S. and M.Phil. degrees in computer science in 2013 and 2015, respectively, all from Columbia University. He previously worked at Boeing, in the area of computational fluid dynamics and engineering geometry. His research interests include applications of analog computing, and performance and efficiency... Read More →

Demo/Poster Collaborator
avatar for Ning Guo

Ning Guo

PhD Candidate in Electrical Engineering, Columbia Engineering
Ning Guo is a 4th-year PhD student,  supervised by Prof. Yannis Tsividis, at Electrical Engineering Department, Columbia University. His research interests include ultra low-power analog/mixed-signal circuit design, analog/hybrid computing, energy-efficient embedded computing, continuous-time computing.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Idea Generation, Creativity, and Prototypicality [D13]
Please note that this demo will only be available until 3:45PM.

We explore the use of Big Data tools to shed new light on the idea generation process, automatically “read” ideas in order to identify promising ones, and help people be more creative. The literature suggests that creativity results from the optimal balance between novelty and familiarity, which should be measured based on the combinations of words in an idea. We build semantic networks where nodes represent word stems relevant to a particular idea generation topic, and edge weights capture the novelty vs. familiarity of word stem combinations (i.e., the weight of an edge that connects two word stems measures their scaled co-occurrence). Each idea contains a set of word stems, which form a semantic subnetwork. The edge weight distribution in that subnetwork reflects how the idea balances novelty with familiarity. Consistent with the “beauty in averageness” effect, we find that ideas with semantic subnetworks that have a more prototypical edge weight distribution are judged as more creative. Practically, we demonstrate how our research can be used to automatically identify promising ideas, and recommend words to users on the fly to help them improve their ideas.

Demo/Poster Presenter
avatar for Oded Netzer

Oded Netzer

Associate Professor of Business, Columbia Business School
Professor Netzer's research centers on one of the major business challenges of the data-rich environment of the 21st century: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. His research has... Read More →
avatar for Olivier Toubia

Olivier Toubia

Glaubinger Professor of Business, Columbia Business School
Olivier Toubia is the Glaubinger Professor of Business and the Faculty Director of the Lang Center for Entrepreneurship at Columbia Business School. His research focuses on various aspects of innovation (including idea generation, preference measurement, and the diffusion of innovation), social networks and behavioral economics. He teaches a course on Customer-Centric Innovation, a course (“Research to Revenue”) that... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Mapping Tibetan Monasteries [D10]
This project is a new attempt to combine Tibetan studies and digital humanity by utilizing GIS technology. Tibet is known for its diverse and splendid monastic traditions with a long history, and the primary goal of this project is visualizing the development of Tibetan monasteries from the 9th to 21th centuries. By collecting the information of 2,733 monasteries in Tibet, our work team built a database of Tibetan monasteries and further visualized the development of Tibetan monasteries for 1,200 years as a GIS map with timeline tool. Moreover, our team produced different theme maps of Tibetan monastic cultures, such as the affiliations of monasteries the clusters of livestocks. In addition to visualizing the big data by GIS technology, we analyzed the patterns of Tibetan monasteries and presented our work on Columbia Wikischolars. We strongly hope to participate in "2016 Data Science Day @ CU" in order to have more people access fascinating Tibetan culture through digital humanity.  

Demo/Poster Presenter
avatar for Ling-Wei Kung

Ling-Wei Kung

PhD Candidate in East Asian Languages and Cultures, Graduate School of Arts and Sciences
Ling-wei Kung is a Ph.D. student in Sino-Tibetan history. His research focuses on transregional legal practices and economic exchanges among Tibet, Mongolia, Xinjiang and late imperial China. He is also more broadly interested in the history of Inner Asian peoples between the Qing and Russian Empires. He is currently conducting two research projects: “The Most Important Place: Environment, Communities and Identities in Gansu Province of... Read More →
QQ

Qichen Qian

MA Student in East Asian Languages and Cultures, Graduate School of Arts and Sciences
avatar for Tongtong Zhu

Tongtong Zhu

Graduate Student, East Asian Languages and Cultures
XX

Xiaoze Xu

MA Student in East Asian Languages and Cultures, Graduate School of Arts and Sciences



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Mobile Phone Based Systematic Street Observations and Geotagged Photos to Identify Vector Control Opportunities in Informal Communities [D17]
Rio das Pedras, home to approximately 63,500 residents, is the third largest informal community in Rio de Janeiro, Brazil. A tightly woven community, Rio das Pedras has continually attracted new residents while developing a growing local economy. Despite the collective successes, some services and infrastructure that many developed areas take for granted are missing in Rio das Pedras.    The team used the Fulcrum platform, a mobile data collection tool, to deploy a customized structured questionnaire and map layer of Rio das Pedras in order to conduct a neighborhood audit of the area. The app allowed the team to coordinate the collection photographic and location data in real time.  The project coordinator and two data collectors were able to collect SSO data at 643 locations (86% of all street segments) in Rio das Pedras, essentially collecting a saturated sample across the entire community.      More than 4,000 geotagged photos have subsequently been used to create themed photo collages, and visuals of random 5% sample of the street segments observed.  These photos have also been used to illustrate a community health profile produced for distribution to local residents and stakeholders.

Demo/Poster Presenter
avatar for Andrew Rundle

Andrew Rundle

Associate Professor of Epidemiology, Mailman School of Public Health
Dr. Rundle's research focuses on the determinants of sedentary lifestyles and obesity and the health related consequences of these conditions. Dr. Rundle Co-directs the Built Environment and Health Research Group (beh.columbia.edu), a trans-disciplinary team of researchers studying how neighborhood built and social environments influence health, particularly physical activity and obesity risk. His work on urban design and... Read More →
avatar for Gina Lovasi

Gina Lovasi

Assistant Professor of Epidemiology, Mailman School of Public Health
Gina S. Lovasi is an assistant professor in Epidemiology at the Columbia University Mailman School of Public Health.  Her research examines how local policies and initiatives influence cardiovascular and respiratory health, seeking to understand whether the anticipated health benefits have been realized and to explore any unanticipated health effects.  She works to incorporate GIS into a range of health-related research projects in... Read More →
avatar for Richa Gupta

Richa Gupta

Graduate Student in Epidemiology, Mailman School of Public Health
avatar for Richard V. Remigio

Richard V. Remigio

Ph.D. Candidate in Environmental Health Sciences, Graduate School of Arts and Sciences
Richard Remigio is a PhD candidate in the Climate and Health Program. Prior to starting his doctoral studies, he worked as an environmental engineer for the US Environmental Protection Agency (USEPA) working broadly on water quality protection at the national scale. His primary research interests relates to characterizing the impacts of observed and projected heat wave events on vulnerable populations. He is also interested in understanding the... Read More →

Demo/Poster Collaborator
avatar for Gustavo S. Azenha

Gustavo S. Azenha

Associate Research Scholar, Institute of Latin American Studies
Gustavo S. Azenha received his M.S. and Ph.D. from Cornell University,with an interdisciplinary background in the biology and social sciences (sociocultural anthropology & development sociology).  Gustavo's primary disciplinary expertise is development anthropology with a thematic specialization on globalization, social movements, and public policy. His academic and professional projects have been fairly diverse:  He has... Read More →
avatar for Melika Ranjbar Behrooz

Melika Ranjbar Behrooz

Undergraduate Student in Urban Studies, Barnard College
Melika Behrooz is a third-year student at Barnard College, majoring in Urban Studies and focusing in Public Health. She is currently working within a research group led by Professor Gina Lovasi, focusing on an urbanizing favela outside of Rio. She has also been working with Professor Lovasi on urban health projects as part of Mailman's newly launched Urban+Health Initiative. She is particularly interested in utilizing the data science methods... Read More →
MC

Marilia Carvalho

Brazilian National School of Public Health at FioCruz
avatar for Folake Eniola

Folake Eniola

PhD Candidate in Epidemiology, Mailman School of Public Health
avatar for Sandro Galea

Sandro Galea

Adjunct Professor of Epidemiology, Mailman School of Public Health
Sandro Galea, MD, MPH, DrPH, is a physician and an epidemiologist. Dr. Galea is interested in the social production of health of urban populations. His work explores innovative cells-to-society approaches to population health questions. His primary focus is on the causes of brain disorders, particularly common mood-anxiety disorders and substance abuse. He has long had a particular interest in the consequences of mass trauma and conflict... Read More →
avatar for Daniel M. Sheehan

Daniel M. Sheehan

Member of the Built Environment and Health Project (BEH), Department of Epidemiology, Columbia University
Daniel M. Sheehan is a member of the Built Environment and Health Project (BEH) research group at Columbia University's Department of Epidemiology where he builds and processes geospatial databases for environmental health-related projects. He earned his MA in GIS from University at Buffalo and is currently enrolled in the IDSE's Certification of Professional Achievement in Data Sciences. Prior to joining the GIS team at BEH, he worked... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

MoMA Through Time [D8]
With MoMA Through Time, we explore the rich exhibition history of the Museum of the Modern Art (MoMA) using the exhibition dataset provided by the museum. So far, it looks at the most popular artists’ exhibition frequencies at the museum, as well as exploring how different countries and movements are represented at the museum throughout its existence. This project was originally created for "MoMA Untitled: Art Datathon," hosted by the museum and was the overall winner for the event.

Demo/Poster Presenter
avatar for Manuel Rueda

Manuel Rueda

MS Student in Data Science, Data Science Institute
Manuel Rueda is a M.S. student in Data Science at Columbia University. He received his B.S. in Economics in 2010 from ITESM (Mexico), after which he worked for 5 years on big data analysis for financial risk management. His main interests include machine learning, social data and data visualization systems.
avatar for Woojin Kim

Woojin Kim

MS Student in Data Science, Data Science Institute
Woojin Kim received his BS degree in Chemical Engineering from Cornell University in 2012 and MS degree in Chemical Engineering from Columbia University in 2013. He is currently pursuing a MS degree in Data Science at Columbia University. His interests include machine learning / data mining applications for predictive analytics and data visualization. |

Demo/Poster Collaborator
avatar for Nomaduma Masilela

Nomaduma Masilela

Fellow at The Museum of Modern Art, The Museum of Modern Art
Nomaduma Masilela is a second-year PhD candidate who studies modern and contemporary art from Africa and the Diaspora. She is a Ford Pre-Doctoral Fellow and a Mellon Mays Undergraduate Fellow. | | Nomaduma received her BA from Barnard College (2007). She was a Curatorial Fellow at The Kitchen, New York (2007-08) and conducted independent research in Dakar, Senegal as a Mortimer Hays Brandeis Traveling Fellow (2008-09) before arriving at Columbia... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Monitoring Large Scale Disasters [D23]
During crises such as natural disasters or other human tragedies, information   needs of both civilians and responders often require urgent, specialized   treatment. Monitoring and summarizing important information during such an   event remains a difficult problem. We present a system for monitoring online   news for such disasters. Given a query: e.g. "Hurricane Sandy," our system   analyzes the web, and produces a sequence of updates, brief textual   descriptions about the current state of the event, as that event unfolds   over time.    We use novel, disaster-specific features for generating updates,    including geo-locations and language models representing the language of    disaster.   Our demo will allow users to see updates generated for   pre-run queries including: Hurricane Sandy, the Boston Marathon bombing,   and 40 other large scale disasters. A work-in-progress demo can be seen at the   url listed. 

Demo/Poster Presenter
avatar for Chris Kedzie

Chris Kedzie

PhD Candidate in Computer Science, Columbia Engineering

Demo/Poster Collaborator
avatar for Kathy McKeown

Kathy McKeown

Director, Data Science Institute
A leading scholar and researcher in the field of natural language processing, McKeown focuses her research on big data; her interests include text summarization, question answering, natural language generation, multimedia explanation, digital libraries, and multilingual applications. Her research group's Columbia Newsblaster, which has been live since 2001, is an online system that automatically tracks the day's news, and demonstrates the... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Personalized Compass--A Compact Visualization for Direction and Location [D29]
Maps on mobile/wearable devices often make it difficult to determine the location of a point of interest (POI). For example, a POI may exist outside the map or on a background with no meaningful cues. To address this issue, we present Personalized Compass, a self-contained compact graphical location indicator. Personalized Compass uses personal a priori POIs to establish a reference frame, within which a POI in question can then be localized. Graphically, a personalized compass combines a multi-needle compass with an abstract overview map. In this demonstration, we present a prototype iOS map application with Personalized Compass. Attendees will have the opportunities to interactively use Personalized Compass to perform a series of map-based location and direction tasks.

Demo/Poster Presenter
avatar for Daniel Miau

Daniel Miau

PhD Candidate in Computer Science, Columbia Engineering
avatar for Steven Feiner

Steven Feiner

Professor of Computer Science, Columbia Engineering
Steven Feiner is professor of computer science at Columbia Engineering, where he directs the Computer Graphics and User Interfaces Lab and co-directs the Columbia Vision and Graphics Center. His interests include human–computer interaction, augmented reality and virtual environments, 3-D user interfaces, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, and information visualization. Feiner... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

QuantMiner for Mining Quantitative Association Rules [D12]
We present QuantMiner, a Data Mining tool for mining Quantitative Association Rules that is taking into consideration numerical attributes in the mining process without a binning/discretization a priori of the data. It exploits a recent and innovative research in using genetic algorithms for mining quantitative rules published in IJCAI 2007.   The system is based on a genetic algorithm that dynamically discovers “good” intervals in association rules by optimizing both the support and the confidence of the rules. The experiments on real and artificial databases have shown the usefulness of QuantMiner as an interactive, exploratory data-mining tool.    The software was published in the Journal of Machine Learning Research open source software.  http://jmlr.org/papers/v14/salleb-aouissi13a.html 

Demo/Poster Presenter
avatar for Ansaf Salleb-Aouissi

Ansaf Salleb-Aouissi

Lecturer in the Discipline of Computer Science, Columbia Engineering
Ansaf Salleb-Aouissi joined the Department of Computer Science as a Lecturer in Discipline in July 2015. Ansaf received her PhD in Computer Science from University of Orleans, France in 2003, after which she pursued her training as a postdoctoral fellow at INRIA, Rennes (France). She was appointed as an Associate Research Scientist at the Columbia University’s Center for Computational Learning Systems in 2006 and served as an adjunct... Read More →
avatar for Antonio Moretti

Antonio Moretti

PhD Candidate in Computer Science, Columbia Engineering


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Real Time Cyber Risk Pricing Model [D5]
Using a network of virtual machines, this model demonstrates the frequency and severity of security breaches. The data gathered in this environment is then used to price cyber risk based on the cost to remediate, the length of the breach and the likelihood of future breaches.

Demo/Poster Presenter
avatar for Robert Terrin

Robert Terrin

MBA Candidate, Columbia Business School


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

RObotic Spine Exoskeleton (ROSE) [D14]
The ROSE Brace is designed to first understand spinal deformities, such as scoliosis.  With that knowledge it can then be used to develop novel treatment protocols or methods of diagnosis.  This is done through the use of multiple segments which can push or bend different portions of the torso to move the underlying spine.  This allows the wearer to move on their own while still receiving forces from the brace.

Speakers
avatar for Sunil Agrawal

Sunil Agrawal

Professor of Mechanical Engineering and of Rehabilitation and Regenerative Medicine, Columbia Engineering
Dr. Agrawal obtained a PhD degree in Mechanical Engineering from Stanford University in 1990 with emphasis on robotics, dynamics, and control. He currently directs the Robotics and Rehabilitation Laboratory (ROAR) and Robotic Systems Engineering Laboratory (ROSE), which have an active group of PhD, MS, UG, and  post-doctoral researchers. Dr. Agrawal’s current and past research has focused on the design... Read More →

Demo/Poster Presenter
JP

Joon Park

PhD Student in Mechanical Engineering, Columbia Engineering
avatar for Paul Stegall

Paul Stegall

PhD Candidate in Mechanical Engineering, Columbia Engineering
Paul received the B.S. degree in mechanical engineering from Johns Hopkins University, Baltimore, MD, USA, in 2009. He is currently working towards the Ph.D. degree in mechanical engineering at Columbia University, New York, NY, USA. He is with the Robotics and Rehabilitation Laboratory, Columbia University. His research interests include robotic rehabilitation, human learning, and gait training.
avatar for Riancy Li

Riancy Li

Undergraduate Student in Mechanical Engineering, Columbia Engineering

Demo/Poster Collaborator
RM

Rosemarie Murray

Undergraduate Student in Mechanical Engineering, Columbia Engineering
HZ

Haohan Zhang

Research Assistant, Mechanical Engineering, Columbia University


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Scalable Platform for Efficient Embedded Big-Data Processing [D31]
The quest for energy efficiency affects all types of computer systems, from data centers to embedded devices. As the amount of sensor-generated data continues to grow, their processing by analytics applications is increasingly pushed to the  edge of the cloud. The demand for efficient embedded big-data processing translates in the emergence of heterogeneous architectures, which combine accelerators with general-purpose processors. Heterogeneity, however, exacerbates design and programming complexity. We propose a system-level design methodology that is scalable and application-driven. It relies on a flexible architecture balancing heterogeneity and regularity to ease the integration of accelerators and processors. It promotes intellectual property reuse and enables quick design-space exploration at both the component and application levels. Furthermore, it addresses the challenges of running legacy software and managing energy in accelerator-enhanced architectures. We demonstrate our methodology with a computer-vision application integrated with a real-time monitoring mechanism implemented on a high-end FPGA prototyping system. 

Demo/Poster Presenter
avatar for Davide Giri

Davide Giri

PhD Candidate in Computer Science, Columbia Engineering
avatar for Emilio G. Cota

Emilio G. Cota

PhD Candidate in Computer Science, Columbia Engineering
avatar for Paolo Mantovani

Paolo Mantovani

PhD Candidate in Computer Science, Columbia Engineering
Paolo is a PhD student at Columbia University working with the System-Level-Design group under the supervision of Professor Luca Carloni. He  completed his M.S. degree in Electronic Engineering at "Politecnico di Torino" in 2010 and earned his  piano diploma at the Conservatory of Music L. Campiani in Mantova in 2007. | As a master student in Torino Paolo focused on VLSI and process-variation-awaredesign. At Columbia University his... Read More →

Demo/Poster Collaborator
avatar for Luca Carloni

Luca Carloni

Associate Professor of Computer Science, Columbia Engineering
Luca Carloni is an associate professor of computer science at Columbia Engineering. He received a Faculty Early Career Development (CAREER) Award from the National Science Foundation in 2006, was selected as an Alfred P. Sloan Research Fellow in 2008, and received the Office of Naval Research (ONR) Young Investigator Award in 2010. Carloni’s research interests include methodologies and tools for multi-core system-on-chip platforms... Read More →
avatar for Giuseppe Di Guglielmo

Giuseppe Di Guglielmo

Associate Research Scientist in Computer Science, Columbia Engineering

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Scopio - An Intelligent Social Media Content Curation and Rights Management Platform [D9]
Scopio is a premier platform that licenses trending images and videos on social media, curated specifically to suit clients needs.  It processes millions of  user generated content (UGC) contributed by users across multiple social media platforms, identifies the most appropriate content for a client, and procures the rights for that content to be legally used by the client.    It employs a set of complex algorithms to process the social media streams like Twitter and Instagram, to filter out unwanted content, then uses a mix of smart vision based categorization system as well as manual verification to make sure that the content is curated as per the client's needs.  It then provides a dashboard for customers to reach out to the content contributors, obtain the rights for that content, which then can be used legally for marketing purposes.  Scopio's dashboards and workflow supported by solid technology cuts down on the social media content curation and rights management process time by as much as 70%.    The system has been piloted with multiple brands as well as news/media organizations like Reuters.  Chris Wiggins, professor at CU and Chief Data Scientist at NY Times gave it the tagline "Getty Images in real time".

Demo/Poster Presenter
avatar for Manoj Pooleery

Manoj Pooleery

Chief Technology Officer, Scopio
Manoj Pooleery is a seasoned IT executive and Entrepreneur with 20 years of experience in Enterprise Architecture, Software development, Project and Program Management, teaching and mentoring. He specializes in Entrepreneurship, multi-year Strategy development, Budgeting, Technology direction and Project Proposals. His current technology specialization areas are Natural Language Processing, Machine Learning, Predictive Analytics, Cloud... Read More →
avatar for Nour Chamoun

Nour Chamoun

Chief Creative Officer, Scopio
A graduate of the Design + Technology masters program at Parsons School of Design, Chamoun is currently the Chief Creative Officer at Scopio. Scopio is a high-tech social image agency. They streamline the copyright process for user generated images and videos. They are an image marketplace where users get paid for their work, where in the past they have not been, and clients finally have an effective way to use social images-in real... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Sensing Using Thin Film Technologies [D30]
Thin film and printable electronics offer the opportunity for the development and fabrication of new electronic systems with a range of applications.  In this demo we will showcase three applications of thin film systems applied to sensor systems and data collection, namely:    -Flexible devices for strain and position sensing (with Peter Allen and Matei Ciocarlie)  -Flexible systems for optical imaging and analysis (with Hongtao Ma and Andreas Hielscher)  -Printed sensors for chemical and vapor sensing (with Howard Katz)    Demos will show these systems in operation, and students will be on hand to answer questions about their fabrication and application. 

Demo/Poster Presenter
avatar for Ioannis (John) Kymissis

Ioannis (John) Kymissis

Associate Professor of Electrical Engineering, Columbia Engineering
Ioannis (John) Kymissis is an Associate Professor of Electrical Engineering at Columbia Engineering. His area of specialization is solid state electronics and device fabrication. He researches thin film devices and systems, especially focusing on optoelectronic and sensing devices based on organic and amorphous metal oxide thin film materials. Current areas of research include investigations into device performance, fabrication, packaging, and... Read More →
avatar for Kostas Alexandrou

Kostas Alexandrou

PhD Candidate in Electrical Engineering, Columbia Engineering
Kostas Alexandrou received his B.S degree in Computer Engineering from the Piraeus University of Applied Sciences  in 2008. He continued his studies joining the international Master's in Nanotechnology, a joint degree from 3 European universities, finishing with a thesis at IBM Almaden in California. | In 2012, he joined as a PhD candidate Columbia University, department of electrical engineering  where he has been working on the... Read More →
SD

Simona Dalmasso

Columbia University
avatar for Youngwan Kim

Youngwan Kim

PhD Candidate in Electrical Engineering, Columbia Engineering
Youngwan (Willis) Kim obtained his Dual B.S degree magna cum laude in Electrical Engineering from Kyungpook National University, Korea and University of Texas, Dallas in 2011. During his undergraduate studies, he worked as a circuit designer and system developer at Winitech (South Korea) from 2007 to 2009 for central monitoring and control systems used by police and fire station. Also, he worked on the project "Active... Read More →

Demo/Poster Collaborator
CY

Caroline Yu

Student, ELectrical Engineering, Columbia University

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Shuffler: Continuous Code Layout Randomization [D6]
Many programs are vulnerable to code-reuse attacks, where their own code is stitched together to form a malicious exploit (known as Return-Oriented Programming or ROP). Recently, Just-In-Time ROP attacks have been described which dynamically discover a target program's code, so even if it is randomized differently every time it runs, ROP can still be performed. We present Shuffler, the first comprehensive re-randomization technique that continuously changes the layout of code in memory as it runs. This process is self-hosting, and the code which implements the migration is itself re-randomized. Shuffler defines a time window -- as short as 100ms -- within which a ROP attacker must gather information, compile, and execute their exploit. This extra time dimension will confound most existing attacks.

Demo/Poster Presenter
avatar for David Williams-King

David Williams-King

PhD Candidate in Computer Science, Columbia Engineering
David is a PhD student at Columbia University advised by Junfeng Yang, Simha Sethumadhavan, and Roxana Geambasu. His interests include security and operating systems, compilers, and speech recognition. He currently researches randomization-based techniques to defeat code reuse attacks, and the practicality of such defenses. | | David graduated from the University of Calgary in 2012 and obtained a master's degree in 2014 from the University... Read More →
avatar for Michelle Zheng

Michelle Zheng

Undergraduate Student in Computer Science and Economic, Columbia College
Michelle is an undergraduate student studying Computer Science and Economics.  She is assisting David Williams-King with his research project, the Shuffler. Michelle’s interests include security, compilers and 3-D user interface design. Michelle is graduating from Columbia College in May 2016.  She worked at Goldman Sachs in the Credit Risk Technology department in the summer of 2015. She has also received awards at HackMIT and... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

SoleSound: A Gait Analysis Device with Tactile and Auditory Feedback [D15]
The SoleSound is a fully portable wearable system that consists of a pair of smart footwear units capable of measuring an individual’s gait characteristics and providing audio-tactile feedback to the wearer. A separate hip pack unit contains a single-board computer which stores the sensor data collected from the footwear units and processes that information in real time to synthesize feedback corresponding to the wearer’s movements.     Underfoot pressures are recorded by each footwear unit via four pressure sensors mounted below the insole. Kinematic data (orientation and linear acceleration) is collected from IMU units located within each footwear and on the user’s shanks. In addition, a side mounted ultrasonic sensor is used to estimate base of walking. Feedback is provided via five vibro-tactile transducers mounted in areas of the sole where density of mechanoreceptors is highest. Practical applications include diagnostic gait analysis for fall prevention and virtual reality simulation.  

Demo/Poster Presenter
avatar for Damiano Zanotto

Damiano Zanotto

Associate Research Scientist in Mechanical Engineering, Columbia Engineering
Damiano Zanotto received Bachelor' s and Master's degrees in Mechanical Engineering in 2005 and 2007, respectively, as well as a Ph.D. degree in Industrial Engineering (curriculum in Mechatronics) in 2011, all from the University of Padua, in Padua, Italy. Between 2011 and 2013, he was a Postdoctoral Researcher with the Mechanical Systems Laboratory (MSL) at the University of Delaware. Since 2013 he has been working with the Robotics and... Read More →
HZ

Huanghe Zhang

MS Student in Mechanical Engineering, Columbia Engineering
JX

Jesse Xing

MS Student in Mechanical Engineering, Columbia Engineering
avatar for Sunil Agrawal

Sunil Agrawal

Professor of Mechanical Engineering and of Rehabilitation and Regenerative Medicine, Columbia Engineering
Dr. Agrawal obtained a PhD degree in Mechanical Engineering from Stanford University in 1990 with emphasis on robotics, dynamics, and control. He currently directs the Robotics and Rehabilitation Laboratory (ROAR) and Robotic Systems Engineering Laboratory (ROSE), which have an active group of PhD, MS, UG, and  post-doctoral researchers. Dr. Agrawal’s current and past research has focused on the design... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Using Data Science to Generate Real-Time Blood Glucose Forecasts for Individuals with Diabetes [D18]
In this demo we will showcase a novel way to utilize data collected through self-monitoring to predict health impact of future actions. Diabetes is a chronic illness affecting nearly 10% of Americans, and requires multiple adjustments to diet, exercise, and other lifestyle choices. Yet anticipating the impact of these adjustments can be challenging for both individuals with diabetes and their caregivers. We have developed Mealyzer, a mobile application that facilitates diabetes self-management by providing users with real-time, personalized, physiology-based forecasts of blood glucose levels based on prospective meals. Users record their blood glucose and meals by submitting images and descriptive text, and subsequently receive short-term blood glucose predictions that are generated in a data assimilation framework that uses a dual unscented Kalman filter to personalize mechanistic models of the glucose-insulin system. In this demo, we will showcase the Mealyzer mobile interface, and visualization of the forecasts generated with computational models.

Demo/Poster Presenter
avatar for David J. Albers

David J. Albers

Associate Research Scientist in Biomedical Informatics, College of Physicians and Surgeons
David Albers is an Associate Research Scientist who earned his bachelor’s in mathematics and bachelor’s, master’s, and PhD degrees in physics at the University of Wisconsin at Madison. Experienced in nonlinear science and dynamical systems, Dr. Albers has recently aimed to apply these skills and methods to electronic health records and intensive care data, particularly looking at temporal changes. He has worked closely with Dr... Read More →
avatar for Matthew Levine

Matthew Levine

Research Associate in Biomedical Informatics, College of Physicians and Surgeons
Matthew Levine is a Research Associate in the Department of Biomedical Informatics at Columbia University. His primary research interests focus on the temporal dynamics of biomedical data. Matthew’s recent work involves pairing mechanistic models with physiologic data, with a goal of making useful forecasts and inferences about not only measurable physiology (e.g. blood glucose) but also the underlying dynamics of biological systems (i.e... Read More →
avatar for Olena Mamykina

Olena Mamykina

Assistant Professor of Biomedical Informatics, College of Physicians and Surgeons
Olena Mamykina is an Assistant Professor of Biomedical Informatics in the Department of Biomedical Informatics at Columbia University. Her primary research interests reside in the areas of Biomedical Informatics, Human-Computer Interaction, Ubiquitous and Pervasive Computing, and Computer-Supported Collaborative Work. Her broad research interests include individual and collective cognition, sensemaking and problem-solving in the context... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Visualizing Population Exposure to Hazards: The SEDAC Hazards Mapper and HazPop Mobile App [D25]
A growing array of data on natural hazards and population and infrastructure distribution is available online through open web mapping services. The Hazards Mapper and HazPop Mobile App enable users to visualize recent data on earthquakes, tornadoes, wildfires, and other hazards in relationship to population, settlements, and major infrastructure such as dams and power plants. Users are also able to perform spatial queries to determine the total population around an existing facility or within a user-defined circle or polygon. The mobile app, currently implemented for iPhones and tablets running iOS, utilizes location services to support additional query and alert functions. These tools, together with selected population and infrastructure data, are available through the NASA Socioeconomic Data and Applications Center (SEDAC), which is operated by the Center for International Earth Science Information Network (CIESIN), part of the Earth Institute at Columbia University.

Demo/Poster Presenter
ES

Elisabeth Sydor

Publications Coordinator, Earth Institute, Center for International Earth Science Information Network
avatar for Greg Yetman

Greg Yetman

Senior Staff Associate, Earth Institute, Center for International Earth Science Information Network
Greg Yetman is associate director for the Geospatial Applications Division at CIESIN. He is a geographer specializing in the application of geographic information system (GIS) technologies in applied and research fields, including population geography, natural disasters, and environmental assessment. He has acted as a technical advisor on GIS to government and international organizations, including the United Nations Geographic Information... Read More →
JS

Joachim Schumacher

Senior Staff Associate, Earth Institute, Center for International Earth Science Information Network
avatar for Robert Chen

Robert Chen

Director & Senior Research Scientist, Earth Institute, Center for International Earth Science Information Network
Robert S. Chen is director of CIESIN, the Center for International Earth Science Information Network, a research unit of the Earth Institute at Columbia University. He manages the NASA Socioeconomic Data and Applications Center (SEDAC), part of NASA’s network of earth science data centers. He is currently a co-chair of the Thematic Network on Sustainable Development Data of the United Nations Sustainable Development Solutions Network... Read More →
avatar for Sri Vinay

Sri Vinay

Senior Staff Associate, Earth Institute, Center for International Earth Science Information Network
Sri Vinay heads the Information Technology division at CIESIN. He is the systems engineer for the Socioeconomic Data and Applications Center (SEDAC), a data center in NASA’s Earth Observing System Data and Information System. His training is in electrical and computer engineering, energy technology and applications of remote sensing and GIS. His area of expertise and interests are:systems and software engineering, information systems... Read More →

Demo/Poster Collaborator
avatar for Frank Pascuzzi

Frank Pascuzzi

Developer, ESDIS Project
AP

Al Pinto

Developer, Other


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Wall Street meets FinTech: Interactive Visualization of Simulations of Systemic Financial Market Risk Conditional on Policy Interventions [D2]
A key issue for regulators and the banking and financial service industries is mitigating  systemic large-scale counterparty risk.  Currently, individual financial institutions and regulators conduct systemic risk exposure analysis using proprietary models and data protocols absent any agreed upon baseline, best practices or public scrutiny. Without industry standards, shared benchmarks, or means to validate results, the impact of alternative policy interventions on the overall risk in the financial system remains uncertain.    The demo will illustrate new open source analytical tools that     1) Develop highly granular trade and counterparty cross-asset class risk simulation;   2) Aggregate at the counterparty level; and  3) Explore systemic linkages and changes under policy intervention scenarios.    Bringing large-scale open source risk models to the public domain will enable a standard-based approach that facilitates research and greater understanding of the impact that policy levers have on the financial system.

Demo/Poster Presenter
avatar for Matthew Weber

Matthew Weber

Vice President UX and Design, Zoomdata
Matthew Weber is an award winning UX designer and executive, who has had his work showcased by Apple and has lectured at NASA. He has a passion for making data easy to use, and is currently VP of UX and Design at Zoomdata, as well as an associate at Columbia University. Matthew is the founder of the UX + Data Meetup, and is also an advisory board member for the UX Awards.  
avatar for Scott Sobolewski

Scott Sobolewski

Quaternion
Scott is a finance and risk professional specializing in capital planning, stress testing, and model development at large US banks. He advises financial institutions on risk management and regulatory compliance matters, helping clients accelerate model development and achieve high-value institutional objectives.  | Scott has extensive experience meeting Dodd Frank deliverables and managing regulatory relationships with the Federal Reserve... Read More →
avatar for Sharyn O'Halloran

Sharyn O'Halloran

George Blumenthal Professor of Political Economy and Professor of International Affairs | Chief Academic Officer SPS, School of International and Public Affairs
Sharyn O'Halloran is the George Blumenthal Professor of Political Economy and Professor of International and Public Affairs at Columbia University in New York City A political scientist and economist by training, O’Halloran has written extensively on issues related to the political economy of international trade and finance, regulation and institutional reform, economic growth and democratic transitions, and the... Read More →

Demo/Poster Collaborator
avatar for David K. Park

David K. Park

Dean of Strategic Initiatives / Director of Special Projects, Arts and Sciences
David K. Park is Dean of Strategic Initiatives and serves as a senior advisor to the Executive Vice President and Dean of Faculty of the Arts and Sciences at Columbia University. Dr. Park is a member of Columbia University's Institute for Data Sciences and Engineering New Media Center, Director of Special Projects at the Applied Statistics Center and Fellow at the Center for the Management of Systemic Risk at Columbia University. Dr. Park is also... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Wireless Demonstrator with Analog-Enabled Digital MIMO Receivers for High Data Rate Wireless Communication [D27]
Wireless MIMO communication systems significantly improve data rate and data reliability with the spatial selectivity provided by multiple antennas and digital signal processing. However, the RF/analog circuits and data-converters in receivers are exposed to spatial interference due to the lack of spatial selectivity in analog domain.     In this wireless demonstrator, an 8-element spatio-spectral-filtering MIMO receiver array uses a 2×4 antenna array to detect a weak desired signal in the presence of a stronger spatially-distinct in-band blocker. 45 simultaneous beams in a 5×9 array are formed digitally. An image shows 45 pixels, the brightness of each indicates the received signal strength on a corresponding beam.     Without RF/analog spatial rejection, the receiver array outputs are saturated by the strong blocker. The desired signals cannot be detected on the image. With RF/analog spatial rejection, receiver saturation is prevented. The blocker disappears in the image and the desired weak signal can be clearly detected.

Demo/Poster Presenter
avatar for Linxiao Zhang

Linxiao Zhang

PhD Candidate in Electrical Engineering, Columbia Engineering
Linxiao Zhang graduated from Nanyang Technological University, Singapore, in 2011 with a Bachelor's degree in Electrical and Electronics Engineering. He interned at the Institute of Microelectronics, Singapore, for five months in 2009. In Summer 2012, he joined Dr. Harish Krishnaswamy's research group as a PhD-track student.



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

A 450mV Timing-Margin-Free Unsupervised Sorter based on Spiking Neural Network [P11]
In the on-going quest to enabling energy-efficient cognitive computing, specialized, often non-Von-Neumann, architecture in near/sub-VTH circuits emerges as a promising candidate. However, the complex and parallel nature of the architecture combined with the large delay variability from near/sub-VTH circuits impose prohibitive timing margin to cycle time and limit the achievable efficiency. The conventional error detection and correction (EDAC) techniques can remove margin, however, they can cause significant overhead since most of them target super-VTH in-order microprocessors. In this work, EDAC technique suitable for near/sub-VTH complex and parallel architecture is demonstrated in an unsupervised sorter based on spiking neural network for brain-computer-interface microsystems using 1) body boost correction, 2) fully-static error-detecting latch, 3) sparse error detection, and 4) local-buffer-less latches and clock distribution. The technique improves energy-efficiency by 49.3% and FCLK by 35.6% compared to the baseline with margin at the area overhead of 4.1%. No additional VDD is needed.

Demo/Poster Presenter
avatar for Josh Seongjong Kim

Josh Seongjong Kim

PhD Candidate in Electrical Engineering, Columbia Engineering
Josh Seongjong Kim received his B.S. degree in electrical engineering from Hanyang University, South Korea, in 2010, and his M.S. degree from University of Michigan in 2012. He is currently pursuing Ph.D. degree in electrical engineering at Columbia University, New York. His research interests include low-power and variation tolerant VLSI circuit and system design. He is a student fellow of the Catalyst Foundation  | (e) sk3667 at... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

A Lightweight Early Arbitration Method for Low-Latency Asynchronous 2D-Mesh NoC’s [P12]
The thrust of massively-parallel computing has become the dominating trend in the micro-electronics industry over the last decade. An efficient on-chip communication infrastructure is a key to building such high-performance many-core processors. In recent years, networks-on-chip (NoC’s) are identified as a promising solution to resolve the on-chip-communication bottleneck. These on-chip networks replace traditional ad hoc bus-based communication with packet switching in a structured network architecture, and therefore inherently separate the design of communication from computing elements. A new low-latency interconnection network, "AEoLiAN," is proposed, using a 2D mesh topology. An asynchronous (i.e. clock-less) design methodology is used to obtain high-performance and ease-of-integration heterogeneous processors. The NoC contains a lightweight monitoring network to rapidly notify routers of incoming traffic in advance, thereby allowing early arbitration and channel allocation. Network-level simulations show significant improvements in system latency (34.4-37.9%) and moderate throughput gain (14.7-27.1%) over an existing optimized asynchronous baseline network.

Demo/Poster Presenter
avatar for Weiwei Jiang

Weiwei Jiang

PhD Candidate in Computer Science, Columbia Engineering
Weiwei Jiang is a Ph.D. candidate in the Department of Computer Science at Columbia University, working with Prof. Steven Nowick. He received the M.S. degree in computer science from Columbia University in 2010 and the B.S. degree from Tsinghua University, China in 2008, with a concentration of electrical engineering. His current research focuses on low-power and high-performance asynchronous networks-on-chip to serve as an integrative medium for... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Adaptive Quantification of Pulmonary Emphysema With a Hidden Markov Measure Field Model [P1]
Full-lung (FL) computed tomography (CT) has been widely used for pulmonary emphysema quantification. Cardiac CT scans include approximately 2/3 of the lung and can be obtained more rapidly and with lower radiation exposure than FL scans. This work presents a novel method for emphysema quantification on both FL and cardiac scans, based on parametric modeling of intensity distributions and a hidden Markov measure field model to segment emphysematous regions. The framework adapts to the characteristics of an image to ensure a robust quantification of emphysema under varying CT imaging protocols and scanner types. Compared to standard approaches, the presented model provides 1) very high longitudinal correlation with 87 subjects and a total of 365 FL scans acquired with varying imaging protocols; and 2) more reproducible emphysema segmentation and higher longitudinal correlations from a diverse pool of scanner types and thousands of subjects with ten thousands of cardiac scans.

Demo/Poster Presenter
avatar for Jie Yang

Jie Yang

PhD Candidate in Biomedical Engineering, Columbia Engineering
Jie Yang is a Ph.D. student in the Department of Biomedical Engineering at Columbia University, working with Dr. Andrew Laine. Her research interests are in quantitative medical image analysis and pattern recognition. She is currently working on adaptive pulmonary emphysema quantification and texture learning from computed tomography (CT) images of the lung.



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Cardiorespiratory Events in the NICU: Continuous Monitoring, Data Repositories and Daily Automated Reporting Versus Intermittent Bedside Documentation [P2]
We compared hemoglobin oxygen saturation data (SpO2) from a continuous data (CD) repository called BedMaster with intermittent documentation (ID) by the bedside nurse in the first month of life in premature infants. BedMaster is an archive database that is interfacing with the bedside patient monitors to collect and archive vital signs, waveforms and clinical alarm data every 2 seconds. A novel algorithm is then applied to remove artifact based on heart rate signal. CD showed higher number of desaturation episodes per day compared to ID (35 vs 3; p<0.001). CD was also able to be manipulated to show the percent time infants spent in various categories of oxygenation levels, something not yet available at the bedside or in the literature. Using a CD repository and custom algorithms, we are able to categorize a natural history of oxygen burden in premature infants not previously available to us or in the literature.

Demo/Poster Presenter
avatar for Nimrod Goldshtrom

Nimrod Goldshtrom

Postdoctoral Clinical Fellow in Pediatrics, College of Physicians and Surgeons
Nimrod is a third year clinical fellow in neonatology at the medical center. His research is currently on using non-invasive monitoring on preterm infants specifically looking at associations with feeding and whether near-infrared spectroscopy can be used to predict disease. He is also part of a working group trying to utilize continuous, real-time vital sign data to generate hypotheses and evaluate clinical status of infants in the intensive... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Cardiovascular Disease Risk And Birth Month? Discovering and Replicating Novel Birth Month Associations [P3]
An individual’s birth month has a significant impact on their lifetime disease risk. Previous studies reveal relationships between birth month and several diseases including asthma, attention deficit hyperactivity disorder, and myopia, leaving most diseases completely unexplored. We developed a hypothesis-free method called SeaWAS (Season-Wide Association Study) that systematically investigates disease-birth month patterns across all conditions. Our algorithm was first applied at Columbia University Medical Center on a dataset containing 1,749,400. We found that 9 cardiovascular conditions were significantly associated with birth month (Jan-Apr), which had never been reported previously. External validation of these findings was performed at Mount Sinai Hospital (MSH, N=1,169,599) also located in New York City (same climate). Seven of the nine conditions revealed at CUMC had significantly correlated birth month – disease risk patterns at MSH. We also explore relationships between biological mechanisms underlying these novel relationships including maternal flu infection and serum vitamin D levels.

Demo/Poster Presenter
avatar for Mary Regina Boland

Mary Regina Boland

PhD Candidate in Biomedical Informatics, College of Physicians and Surgeons
As a PhD student in the laboratory of Dr. Nicholas Tatonetti, Boland aims to explore and understand the systems-level genetic interactions that occur in patients taking multiple drugs targeting diverse genes and gene pathways. In particular, her focus is to develop methods for understanding the systems-level genetic interactions responsible for adverse drug events. As a translational bioinformatician, she is also interested in developing... Read More →

Demo/Poster Collaborator
avatar for Joel Dudley

Joel Dudley

Assistant Professor of Genetics and Genomic Sciences; Director of Biomedical Informatics, Icahn School of Medicine at Mount Sinai
Dr. Dudley is currently Assistant Professor of Genetics and Genomic Sciences and Director of Biomedical Informatics at the Icahn School of Medicine at Mount Sinai. He also directs the newly formed Harris Center for Precision Wellness at Mount Sinai. Prior to Mount Sinai, he held positions as Co-founder and Director of Informatics at NuMedii, Inc. and Consulting Professor of Systems Medicine in the Department of Pediatrics at... Read More →
avatar for Li Li

Li Li

Assistant Professor, Columbia University
Li is an Assistant Professor with over 10 years experience in clinical research and translational bioinformatics involving genetic and clinical risk factor identification, diagnostic assay development, and new therapeutic targets discovery. Her expertise is in translational research by integrating high-throughput genomics, genetics, various molecular measurements, and electronic medical records data with over 50 peer-reviewed publications... Read More →
avatar for Riccardo Miotto

Riccardo Miotto

Data Scientist, Icahn School of Medicine at Mount Sinai
Riccardo's research interests encompass the design of algorithms for information retrieval, machine learning, and data mining applied to real-world data collections.He is currently focusing on machine learning applied to clinical data for personalized medicine. His previous work concerned (1) clinical trial search engines through free-text eligibility criteria processing, and (2) music information retrieval, in particular... Read More →
avatar for Nicholas Tatonetti

Nicholas Tatonetti

Assistant Professor, Biomedical Informatics
Assistant Professor of Biomedical Informatics Department of Biomedical Informatics, | Columbia Initiative for Systems Biology, & Department of Medicine at Columbia University | Research Specialty: Translational bioinformatics, machine learning, observational data mining, combinatorial drug design, emergent biology, genetic networks and network analysis, clinical data analysis


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Central Clearing: On the Regulation of Collateral Requirements [P25]
Clearinghouses operate in a highly regulated environment. Collateral requirements are subject to regulatory approval, and are critically reviewed, since collateral is viewed as the first line of protection for the systemi-cally important clearinghouse in the event of a client default. This does not, however, take away entirely the freedom of the clearinghouse to choose her preferred collat-eralization rules. Regulators often require portfolios to be “fully collateralized,” which effectively creates a floor on the level of collateral a clearinghouse can demand. Since collateral, essentially a contingent claim that pays off only when there is a default, protects clearinghouses from counterparty risk, one may argue that it may be incentive compatible for the clearinghouse to impose even higher requirements. Regulatory authorities thus need to understand the incentives of the clearinghouse, so to design policies that align the interests of the clearinghouse with those of the regulator. We design an extensive form game where the profit maximizing clearinghouse clears client trades submitted via a clearing member bank, in the absence of a regulator. We analytically characterize all subgame perfect Nash equilibria, and show that the resulting equilibrium can only involve very low or very high collateral levels, depending on the riskiness of the traded contract and the benefits that clients can capture from trading. When equilibrium collateral levels are high, the introduction of a regulatory constraint would have no effect since the clearinghouse would have chosen high collateral requirements anyway; when equilibrium collateral levels are low, regulations are necessary to protect the clearinghouse from default losses in bad states of nature.

Demo/Poster Presenter
avatar for W. Allen Cheng

W. Allen Cheng

PhD Candidate in Industrial Engineering and Operations Reasearch, Columbia Engineering
Wan-Schwin Allen Cheng (1988 --) is a Taiwanese-American born in Buffalo, New York. He graduated from National Taiwan University in 2010 with honors, majoring in Mathematics. After fulfilling his Taiwanese military duties, he worked as a research assistant at Academia Sinica. He then proceeded to earn his masters in science and engineering in Applied Mathematics and Statistics in 2013 from the Johns Hopkins University. He was supported by... Read More →

Demo/Poster Collaborator
avatar for Agostino Capponi

Agostino Capponi

Assistant Professor of Industrial Engineering and Operations Research, Columbia Engineering
Agostino Capponi joined Columbia University's IEOR Department in August 2014, where he is also a member of the Data Science Institute. His main research interests are in the area of networks, with a special focus on systemic risk, contagion, and control. In the context of financial networks, the outcome of his research contributes to a better understanding of risk management practices, and to assess the impact of regulatory policies aimed... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Connectivity Homology Enables Inter-Species Network Models of Synthetic Lethality [P4]
Synthetic lethality (SL) is an interaction where two nonessential genes lead to cellular inviability when knocked out simultaneously. Recent work suggests it may be useful in cancer therapy. It may also predict novel drug-drug interactions and suggest mechanisms of adverse drug reactions. Few SL interactions have been found in humans to date, but many are known in yeast. Here, we present Species INdependent TRAnslation (SINaTRA), an algorithm that predicts SL in translation between species using protein-protein interaction (PPI) networks and connectivity homology. We validate SINaTRA using S. cerevisiae and S. pombe and find that model performance improves significantly with the use of SINaTRA. In addition, SINaTRA outperforms other methods of predicting SL, including genetic homology. We then apply our model to the human PPI network. After genetic filtering using 1000 Genomes data, we provide 100 million human gene pairs with measures of their predicted synthetic lethality (SINaTRA scores)

Demo/Poster Presenter
avatar for Alexandra Jacunski

Alexandra Jacunski

PhD Candidate in Systems Biology, College of Physicians and Surgeons
Alexandra is a PhD candidate in the Tatonetti Lab. Her  research focuses on utilizing and understanding biological networks, especially in the contexts of drug-drug interactions (DDIs) and human disease. Part of her research pertains to the development of methods that allow for the direct comparison of biological networks between species, which have allowed her to create inter-species models of biological processes.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Crowd-Sourcing Data and Quality Control: OSM Roads Validation in Low-Income Countries [P13]
Launched in 2004, OpenStreetMap (OSM) is the largest collaborative project to date to create free and editable cartographic data of the world. This study aims to validate quality aspects of road features in OSM such as positional accuracy, completeness, and lineage in four West African countries. A series of test diagnostics integrates statistical and spatial analysis to measure positional accuracy at road intersections against satellite imagery from Google Earth; completeness via discrete classification, spatial regression, and inter-settlement connectivity analyses; and finally, lineage by comparing versioning of road features against positional accuracy results. All the analysis is conducted in R and ArcGIS. This work was completed by CIESIN, a unit of the Earth Institute at Columbia University, under the CODATA Task Group for Global Roads Data Development.

Demo/Poster Presenter
avatar for Paola Kim-Blanco

Paola Kim-Blanco

Senior Staff Associate, Earth Institute, Center for International Earth Science Information Network


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Describing High-Order Statistical Dependence Using "Concurrence Topology,” with Application to Functional MRI Brain Data [P21]
We propose a new nonparametric method, "Concurrence Topology (CT)", for describing dependence among dichotomous variables. CT starts by translating the data into a "filtration", i.e., a series of shapes. Holes in the filtration correspond to relatively weak or negative association among the variables. CT uses computational topology to describe the pattern of holes in the filtration. CT is able to describe high-order dependence while avoiding combinatorial explosion. We employed CT to investigate brain functional connectivity based on dichotomized functional MRI data. The data set includes subjects diagnosed with ADHD and healthy controls. In an exploratory analysis, working in both the time and Fourier domains, CT found a number of differences between ADHD subjects and controls in the topology of their filtrations. A paper based on this work has been published.

Demo/Poster Presenter
avatar for Steven Ellis

Steven Ellis

Associate Professor of Clinical Neurobiology in Psychiatry, College of Physicians and Surgeons
Steven P. Ellis, Ph.D. is Associate Prof. of Clinical Neurobiology (in Psychiatry). He is Director, Statistics and Computing Core, Conte Center: Neurobiological and Developmental Antecedents to Suicidal Behavior: The Neurobiology of Suicidal Behavior (CCNDASB). He is also PI on Project 8 of the CCNDASB, "Statistical methods in suicide research." He graduated cum laude, with Honors with Exceptional Distinction in Mathematics, and with a... Read More →

Demo/Poster Collaborator
avatar for Arno Klein

Arno Klein

Director of Neuroimaging and of SIMPL(E) Principal Scientist of Systems Biology, Sage Bionetworks
Arno's current research focuses on the analysis of mobile health sensor data and brain image data. He was the scientific lead on the mPower study that tracks symptoms of Parkinson disease by collecting voice, accelerometer, and tapping data, and am completing work on the mhealthx pipeline for extracting features from such data. He has been engaged in brain imaging research since 1988 and develop brain image analysis software, including the... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Developing High Performance Green Infrastructure System to Sustain Coastal Cities: A RESPONSIVE WEBSITE FOR CITIZEN-BASED BIOSWALE MONITORING [P14]
BIOSMILES is a smart site that allows residents of NYC to monitor the conditions of green infrastructure in their neighborhood. This tool comprises two components: a physical installation that includes a QR code, and a responsive platform available for free to all interested stakeholders. By using mobile devices, users are asked to input images or data that become instantly visible to the community and scientific cohort related to the site, including academic researchers, local authorities and representatives, and maintenance crew staff members. City agencies can address problems related to vandalism, health of vegetation, and additional detriments due to the presence of garbage or other solid waste. Geocoded data inform researchers and planners for site specific improvements and further expansion of the system. Community benefits include increased knowledge of vital aspects of environmental sustainability and strengthened social cohesion through a shared network to improve new distributed infrastructure approaches.

Demo/Poster Presenter
avatar for Daniel Laimer do Carvalhal da Câmara Machado

Daniel Laimer do Carvalhal da Câmara Machado

Urban Design Lab Analysis Assistant, Earth Institute
Originally from Sao Miguel, Portugal, Daniel has an educational background in Landscape Architecture and Urban Design. He pursued undergraduate studies as a Landscape Architect at both the Pennsylvania State University and the Danish Institute for Studies Abroad, affording him opportunities to work on international projects in both American and European urban contexts. In 2014 he was awarded the Certificate for Excellence in the Study of... Read More →
avatar for Filiberto Viteri Chavez

Filiberto Viteri Chavez

Urban Design Lab Spatial Analysis Associate, Earth Institute
Filiberto Viteri is a licensed architect in Ecuador, having graduated with a professional Degree in Architecture from the Catholic University of Santiago de Guayaquil in 2006. He received his Master of Architecture at the University of Illinois at Urbana Champaign with a Fulbright scholarship in 2010 and was awarded with the Ecuadorian Government’s Universities of Excellence Fellowship to study Urban Design at Columbia University where he... Read More →
avatar for Maria Paola Sutto

Maria Paola Sutto

Program and Communication Manager, Earth Institute, Urban Design Lab
Maria Paola Sutto is a biologist and a journalist. Her research interests focus on environmental impacts at different scales, from molecular markers to the organized urban systems that allow human species to develop. She moved to the United States in 1992 as foreign correspondent for the emerging field of multimedia (1993-2001), writing extensively for all aspects of urban life. In Italy, she began her career as research scientist for molecular... Read More →
avatar for Richard Plunz

Richard Plunz

Professor of Architecture, Planning and Preservation, Graduate School of Architecture, Planning and Preservation
Richard Plunz is a leading figure in urban design and one of the world’s leading authorities in urban housing: His Housing Studios, which he developed at Columbia are now an integral part of architectural curricula everywhere. Plunz moved to Columbia University in 1974 and in 1977 became chairperson of the Division of Architecture, with oversight on the renewal of the professional Master’s curriculum. Since 1992, he has been director... Read More →

Demo/Poster Collaborator
LC

Linda Cox

Executive Director, Bronx River Alliance
avatar for Patricia Culligan

Patricia Culligan

Associate Director and Professor of Civil Engineering and Mechanical Engineering, Data Science Institute
A leader in the field of water resources and urban sustainability, Culligan has worked extensively with The Earth Institute's Urban Design Lab at Columbia University to explore novel, interdisciplinary solutions to the modern day challenges of urbanization, with a particular emphasis on the City of New York. Culligan is the director of a joint interdisciplinary Ph.D. program between Columbia Engineering and the Graduate School of... Read More →
SG

Stuart Gaffin

Research Scientist, Earth Institute, Center for Climate Systems Research
MP

Matthew Palmer

Senior Lecturer in Discipline of Ecology, Evolution and Environmental Biology, Columbia University
JS

John Squires

Research Staff Assistant , Geospatial Applications Division, Columbia University

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Digital Matatus: Mapping Informal Mini-Bus Routes in African Cities [P15]
In many of the world's growing cities, semi-formal buses form the basis of public transit. However, little open and standardized data exist on these systems. The Digital Matatus project set out to test whether the geo-locative capabilities of mobile technology could be used to collect data on a semi-formal transit system in Nairobi, Kenya and whether that data could be translated into the General Transit Feed Specification (GTFS) standard for wider use. We were able to do this and get the first GTFS data for these systems upon Google Maps making the transit app available for Nairobi. Results of this work show that mobile technologies, which are increasingly prevalent in developing countries, can be used effectively to collect and deliver data in a modified GTFS format for semi-formal transit. Perhaps more importantly, through our work in Nairobi, we were able to identify the benefits and technical needs for developing data on semi-formal transit.

Demo/Poster Presenter
avatar for Jacqueline Klopp

Jacqueline Klopp

Associate Research Scholar, Earth Institute, Center for Sustainable Urban Development
Jacqueline Klopp is an Associate Research Scholar at the Center for Sustainable Urban Development at Columbia University. She previously taught the politics of development at the School of International and Public Affairs for many years.  A political scientist by training, her work focuses on the political processes around land-use, transportation, violence, displacement and planning in African cities with a strong focus on equity... Read More →

Demo/Poster Collaborator
avatar for Sarah Williams

Sarah Williams

Assistant Professor, Urban Planning and the Director of the Civic Data Design Lab at MIT School of Architecture and Planning School
Sarah Williams is currently an Assistant Professor of Urban Planning and the Director of the Civic Data Design Lab at Massachusetts Institute of Technology’s (MIT) School of Architecture and Planning School. The Civic Data Design Lab works with data, maps, and mobile technologies to develop interactive design and communication strategies that bring urban policy issues to broader audiences.  Trained as a Geographer (Clark... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Drone Based Preventive Surveillance Techniques for Vector-Borne Diseases with a Focus on the Zika Virus [P5]
With a particular focus on the Zika Virus, we propose the usage of drone-based preventive health surveillance techniques for vector-borne diseases. Using a combination of image streams (from a drone-mounted camera) and localized sensor information, this project aims to identify potential mosquito breeding grounds. Thermal images superimposed on RGB camera images are used in conjunction with geotagged information to help pinpoint a precise site. Using Image and Video Processing we intend to detect stagnant water bodies that contribute to the spread of mosquitoes. Quality assessment of images is done to reject images with noise and distortion. Ambient conditions are correlated with the results of Image Processing and a probability distribution is used to generate heat map visualization of the mosquito prevalent regions at a city level. An iOS App serves as a visualization tool.

Demo/Poster Presenter
avatar for Aditya Bagri

Aditya Bagri

MS Student in Electrical Engineering, Columbia Engineering
Aditya Bagri received his B.E. degree in Electronics & Telecommunication engineering from the University of Mumbai, in 2015. His interests lie in the field of Internet of Things and Data Analytics, primarily employing Smarter Technology and using Big Data in the world of sports.
avatar for Doyun Kim

Doyun Kim

PhD Candidate in Electrical Engineering, Columbia Engineering
Doyun Kim received his B.S. degree in electrical engineering from POSTECH( Pohang University of Science and Technology), South Korea, in 2013. He is currently pursuing a Ph.D. degree in Electrical Engineering at Columbia University, New York. His research interests include low-power VLSI circuit and system design.
avatar for Maanit Mehra

Maanit Mehra

MS Student in Electrical Engineering, Columbia Engineering
Maanit Mehra is a graduate student in the Electrical Engineering department at Columbia University, New York. Having worked in the space of embedded system design, he is currently pursuing his interests in the areas of robotics, smarter machines & the Internet-of-Things.
PM

Palash Matey

MS Student in Electrical Engineering, Columbia Engineering


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

From Players to Teams: Basketball Match Simulation [P26]
Conventional approaches to simulate matches have ignored that in basketball the dynamics of ball movement is very sensitive to the lineups on the court and unique identities of players on both offense and defense sides. In this work, we propose the simulation infrastructure that can bridge the gap between player identity and team level network. We model the progression of a basketball match using a probabilistic graphical model. We model every touch and event in a game as a sequence of transitions between discrete states. We treat the progression of a match as a graph, where each node is a network structure of players on the court, their actions, events, etc., and edges denote possible moves in the game flow. Our results show that either changes in the team lineup or changes in the opponent team lineup significantly affects the dynamics of a match progression.

Demo/Poster Presenter
avatar for Min-hwan Oh

Min-hwan Oh

PhD Candidate in Industrial Engineering and Operations Reasearch, Columbia Engineering
avatar for Suraj Keshri

Suraj Keshri

PhD Candidate in Industrial Engineering and Operations Reasearch, Columbia Engineering

Demo/Poster Collaborator
GI

Garud Iyengar

Professor of Industrial Engineering and Operations Research and Department Chair, Columbia Engineering
Professor Garud Iyengar joined Columbia University’s Industrial Engineering and Operations Research Department in 1998. Professor Iyengar teaches courses in simulation and optimization. Professor Garud Iyengar’s research interests include convex optimization, robust optimization, queuing networks, combinatorial optimization, mathematical and computational finance, communication and information theory. He has published in... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Generation of Synthetic Spatially Embedded Power Grid Networks [P23]
<!--td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}-->The development of algorithms for enhancing the resilience and efficiency of the power grid requires evaluation with topologies of real transmission networks. However, due to security reasons, such topologies and particularly the locations of the substations and lines are usually not publicly available. Therefore, we study the structural properties of the North American grids and present an algorithm for generating synthetic spatially embedded networks with similar properties to a given grid. The algorithm uses the Gaussian Mixture Model (GMM) for node density estimation and generates nodes with similar spatial distribution to the nodes in a given network. Then, it uses two procedures, which are inspired by the historical evolution of the grids, to connect the nodes. The algorithm has several tunable parameters that allow generating grids similar to any given grid. We apply it to the Western Interconnection (WI) and to grids that operate under the SERC Reliability Corporation (SERC) and the Florida Reliability Coordinating Council (FRCC), and show that the generated grids have similar structural and spatial properties to these grids. To the best of our knowledge, this is the first attempt to consider the spatial distribution of the nodes and lines and its importance in generating synthetic grids.

Demo/Poster Presenter
avatar for Gil Zussman

Gil Zussman

Associate Professor of Electrical Engineering, Columbia Engineering
Gil Zussman received the B.Sc. degree in Industrial Engineering and Management and the B.A. degree in Economics (both summa cum laude) from the Technion – Israel Institute of Technology in 1995. He received the M.Sc. degree (summa cum laude) in Operations Research from Tel-Aviv University in 1999 and the Ph.D. degree in Electrical Engineering from the Technion – Israel Institute of... Read More →
avatar for Saleh Soltan

Saleh Soltan

PhD Candidate in Electrical Engineering, Columbia Engineering
Saleh Soltan is a Ph.D. student in the department of Electrical Engineering at Columbia University. He received B.S. degrees in Electrical Engineering and Mathematics (double major) from Sharif University of Technology, Iran in 2011 and the M.S. degree in Electrical Engineering from Columbia University in 2012. He is the Gold Medalist of the 23rd National Mathematics Olympiad in Iran in 2005 and the recipient of Columbia University Electrical... Read More →



Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Geographic Patterns for Social Network Users [P31]
This paper studies social network users’ geographic patterns by comparing Twitter and Flickr’s user distributions through the New York City. Twitter users’ locations are more widely-spread across the city than Flickr photos’ locations. Cluster patterns are very obvious for Flickr photos by looking at specific famous landmark sites. By aggregating public available data from both social networks onto census tract level, this research analyzes the effects of the number of landmark sites and population on the number of Flickr photos and tweets. The point clusters and regression results suggest that population tends to have positive relationship with tweet counts and negative relationship with photo counts on Flickr, while the number of landmark sites have much larger positive effect on Flickr photo counts than on tweet counts. The study discusses both the similarities and differences between the distribution patterns of the two social networks based on several different methods.

Demo/Poster Presenter
avatar for Yaran Fan

Yaran Fan

MS Student in Data Science, Data Science Institute
With 3-years of industry experience focusing on data analysis and customer insights, Yaran Fan is currently pursuing a MS degree in Data Science at Data Science Institute, Columbia University.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

GPU-Based Deep Learning Inference: An Application to Identyfing Diseases Based on Medical Images [P22]
The advent of deep learning has revolutionized the field of computer vision and machine perception. Deep learning technology combines artificial neural network architectures with massive computing power to perform training and inferences. On a high level, deep learning involves a two stage process: First a neural network is trained by tuning its numeric weights based on experience - i.e. determining its parameters using labeled examples of inputs and desired output. This makes neural nets adaptive to inputs and capable of learning. Second, the network is deployed to run inferences i.e. using its previously trained parameters to classify, recognize, and generally process unknown but similar inputs.[2] GPUs massively parallel capabilities and energy efficiency makes them the state of the art in training deep neural networks as opposed to more traditional CPU based platforms.

Demo/Poster Presenter
avatar for Jeet Raut

Jeet Raut

Co-founder and CTO, Behold.ai, Inc
Jeet is the Co-founder and CEO of Behold.ai Behold.ai’s medical software uses artificial intelligence to identify abnormalities in medical images, to help healthcare practitioners rapidly, accurately and consistently make better medical decisions. Behold.ai are proud graduates of Columbia's Almaworks program, as well as the Columbia Startup Lab.  | | Jeet received his B.S. cognitive psychology at the University of Illinois at... Read More →

Demo/Poster Collaborator
avatar for Peter Njenga

Peter Njenga

Cofounder and CTO, Behold.ai, Inc
Peter is a founder of behold.ai. He's an alumnus of Columbia University and University of California at Berkeley. He Previously worked at Facebook on machine learning for place search ranking and on messaging infrastructure. He also worked at Intel and AMD on chip verification. He loves morning runs along the Hudson river.

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Grandet: A Unified, Economical Object Store for Web Applications [P27]
Web applications are getting ubiquitous every day because they offer many useful services to consumers and businesses. Many of these web applications are quite storage-intensive. Cloud computing offers attractive and economical choices for meeting their storage needs. Unfortunately, it remains challenging for developers to best leverage them to minimize cost. This poster presents Grandet, a storage system that greatly reduces storage cost for web applications deployed in the cloud. Grandet provides both a key-value interface and a file system interface, supporting a broad spectrum of web applications. Under the hood, it supports multiple heterogeneous stores, and unifies them by placing each data object at the store deemed most economical. We implemented Grandet on Amazon Web Services and evaluated Grandet on a diverse set of four popular open-source web applications. Our results show that Grandet reduces their cost dramatically, and it is fast, scalable, and easy to use.

Demo/Poster Presenter
avatar for Gang Hu

Gang Hu

PhD Candidate in Computer Science, Columbia Engineering
Gang Hu is a fifth year PhD student in computer science. His research is focused on software reliability and privacy.
avatar for Yang Tang

Yang Tang

PhD Candidate in Computer Science, Columbia Engineering
Yang Tang is a Ph.D. student in the Department of Computer Science at Columbia University, working with Prof. Junfeng Yang. He received his M.Phil. degree in Computer Science and Engineering from the Chinese University of Hong Kong in 2011, and his B.Eng. degree in Computer Science and Technology from Tsinghua University in 2009.

Demo/Poster Collaborator
LW

Lingmei Weng

Computer Science Student, Columbia University
JY

Junfeng Yang

Associate Professor of Computer Science, Columbia University
XY

Xinhao Yuan

Computer Science Student, Columbia University

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Identifying Novel Drug Interactions Using Data Science: Drug Interaction Prediction Using Latent Signals and EHRs (DIPULSE) [P6]
Drug-induced prolongation of the QT interval on the electrocardiogram (long QT syndrome, LQTS) can lead to a potentially fatal ventricular arrhythmia called Torsades de Pointes (TdP). Over 40 drugs with both cardiac and non-cardiac indications have been found to increase risk for TdP, but drug-drug interactions contributing to LQTS (QT-DDIs) remain poorly characterized. Traditional methods for mining observational healthcare data are poorly equipped to detect QT-DDI signals due to low reporting numbers and a lack of direct evidence for LQTS. We developed an integrative data science pipeline that effectively circumvents these limitations by identifying latent signals for QT-DDIs in the FDA’s Adverse Event Reporting System and retrospectively validating these predictions using electrocardiogram data in electronic health records. The method generated 8 novel QT-DDIs. We experimentally validated one of these pairs – lansoprazole (proton-pump inhibitor) and ceftriaxone (cephalosporin antibiotic) – using patch-clamp electrophysiology to assess block of the hERG channel (IKr current).

Demo/Poster Presenter
avatar for Tal Lorberbaum

Tal Lorberbaum

PhD Candidate in Physiology and Cellular Biophysics, College of Physicians and Surgeons
Tal Lorberbaum is a 3rd year PhD candidate in the lab of Nicholas Tatonetti at Columbia University Medical Center. Tal's work focuses on developing computational approaches to analyze large clinical and biological datasets for the purpose of predicting and understanding adverse effects of drug-drug interactions. Tal received a B.S. in biomedical engineering from Cal Poly San Luis Obispo in 2012, where he developed intuitive and cost-effective... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Intelligent Wireless Charging for Electric Buses in Smart City [P16]
The auto industry is amidst a technological transformation to identify alternative sources of energy to power vehicles due to environmental factors. We examine the Metropolitan Transit Authority (MTA) buses since they operate in the city on a continuous cycle with increased coverage during peak transit times. We focus on the B63 bus route and perform a feasibility study to determine primarily whether wireless charging at specifically designated bus stops throughout the city can help to increase the feasibility of electric buses for city use both from an operational standpoint. We propose a framework that consists of a probabilistic model to capture the nature of the data and formalizing the feasibility study as an optimization problem. Using this framework we utilize the history of the system and the properties of the technology to find suitable locations for electric chargers without disrupting the operation of the system.

Demo/Poster Presenter
avatar for Albert Boulanger

Albert Boulanger

Senior Staff Associate, Center for Computational Learning Systems
Albert Boulanger (M.S. CS Univ. of Illinois 1983) has been at CU since 1994 and is Senior Staff Associate with the Center for Computational Learning Systems (CCLS) of Columbia University. Prior to that, Albert was a research scientist at Bolt, Beranek and Newman. Albert has played multiple technical and oversight roles in several Con Edison projects while at Columbia. He is valued for his ability to maintain a systems view of all the facets of... Read More →
avatar for Antonius Dieker

Antonius Dieker

Associate Professor of Industrial Engineering and Operations Research, Columbia Engineering
Ton Dieker earned a master's degree in Operations Research from the Vrije Universiteit Amsterdam in 2002 and a PhD degree in Mathematics from the University of Amsterdam in 2006. His research interests include stochastic models and computer simulation techniques. Honors include the Goldstine Fellowship from IBM Research, a CAREER Award from the National Science Foundation, the Erlang Prize from the Applied Probability Society of INFORMS, and a... Read More →
HS

Hooshmand Shokri Razaghi

PhD Candidate in Computer Science, Columbia Engineering
PD

Promiti Dutta

Ph.D Student, Computer Science, Columbia University
Promiti Dutta  holds a B.S. in chemical engineering, a master's degree in public health in molecular toxicology and epidemiology, and an M.S. in electrical engineering from Columbia University. She is currently a Ph.D. candidate in computer sciecne at Columbia. Her research interests are in the application of networking, communication, and machine learning algorithms towards the integration of electric vehicles and other technologies in... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Interactive Visualizations for Monoscopic Eyewear to Assist in Manually Orienting Objects in 3D [P17]
Assembly or repair tasks often require objects to be held in specific orientations to view or fit together. Research has addressed the use of AR to assist in these tasks, delivered as registered overlaid graphics on stereoscopic head-worn displays. In contrast, we are interested in using monoscopic head-worn displays, such as Google Glass. To accommodate their small monoscopic field of view, off center from the user's line of sight, we are exploring alternatives to registered overlays. We describe four interactive rotation guidance visualizations for tracked objects intended for these displays.

Demo/Poster Presenter
avatar for Barbara Tversky

Barbara Tversky

Professor of Psychology and Education, Teachers College
Barbara Tversky is Professor of Psychology and Education at Columbia Teachers College and Professor Emerita of Psychology at Stanford University.  She has done basic research on memory, categorization, spatial language and thinking, event perception and cognition with applications to eyewitness testimony, cognitive maps, visualizations, HCI, diagrammatic reasoning, design, and the arts. She has enjoyed collaborations with computer... Read More →
avatar for Carmine Elvezio

Carmine Elvezio

Staff Associate in Computer Science, Columbia Engineering
Carmine Elvezio is a staff associate in the Computer Graphics and User Interfaces Lab at Columbia University. His research interests include interaction and visualization techniques in augmented and virtual reality and system design of real-time interactive 3D graphics applications. He received his MS in Computer Science from Columbia University in 2012 and his BS in Computer Science from the Polytechnic Institute of New York University in... Read More →
avatar for Mengu Sukan

Mengu Sukan

PhD Candidate in Computer Science, Columbia Engineering
Mengu Sukan is a PhD student working with Steven Feiner in the Computer Graphics and User Interfaces Lab at Columbia University.  In his research, he designs and evaluates novel 3D visualizations and interaction techniques focusing on augmented reality (AR) for task assistance. Mengu has published papers, posters, and demos at the most selective venues for AR research (ISMAR, UIST, VR/3DUI, and CHI).
avatar for Steven Feiner

Steven Feiner

Professor of Computer Science, Columbia Engineering
Steven Feiner is professor of computer science at Columbia Engineering, where he directs the Computer Graphics and User Interfaces Lab and co-directs the Columbia Vision and Graphics Center. His interests include human–computer interaction, augmented reality and virtual environments, 3-D user interfaces, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, and information visualization. Feiner... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Mapping Cells and Their Connections in Networks of the Brain Master Clock [P7]
Understanding the neural networks associated with specific brain functions is a challenge. The brain’s master clock, located in the suprachiasmatic nucleus (SCN), and made up of ~20,000 “clock cells”, presents an ideal system for exploring the relationship of cellular/molecular events to inter-connections among cells, and how these networks sustain the body’s daily rhythms. At the intracellular level, rhythmicity is produced by feedback loops involving daily rhythms in expression of “clock” genes and associated proteins. To determine whether or not all SCN cells are identical in their intracellular/molecular clocks, we designed programs to assess protein expression levels over days, over time of day, and in location of individual cells within the nucleus, using Mathematica. Our novel approach to analyzing neural networks yields evidence of both regional and cellular specialization of clock protein expression. The findings point to a new mechanism for encoding information in SCN networks.

Demo/Poster Presenter
avatar for Erica Mezias

Erica Mezias

Research Assistant, Cognitive Development Center, Barnard College
Erica Mezias is a senior at Barnard College majoring in Psychology.  She is currently working on a senior thesis in Neuroscience and Behavior in Dr. Rae Silver's Neurobiology lab where she investigates the molecular basis of circadian rhythms using novel computational methods.  Erica has experience running analyses in Wolfram Mathematica to characterize circadian oscillations at the molecular level in brain tissue.
avatar for Malini Riddle

Malini Riddle

Undergraduate Research Assistant, Neuroscience & Behavior, Barnard College
Malini is a junior at Barnard College majoring in cellular neuroscience. She works as a research assistant at Dr. Rae Silver's Neurobiology Lab at Barnard, where she studies circadian rhythms using quantitative computational methods that she helps to develop. Malini has  experience in programming and running analyses using Wolfram Mathematica software to characterize and map circadian oscillations in brain tissue.

Demo/Poster Collaborator
DF

Duncan Foley

Department of Economics, New School for Social Research
JL

Joseph Lesauter

Senior Research Scientist in Psychology, Barnard College
RS

Rae Silver

Helene L. and Mark N. Kaplan Professor of Natural and Physical Sciences, Columbia University

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Mining the Performance History of the New York Philharmonic from 1842-2015: Programming Trends and Performer Networks [P32]
The recent release into the public domain of historical concert program data in XML format by the New York Philharmonic affords the opportunity of diachronic analysis of musical practice in the city, as reflected in the selected pieces performed and records of the participating performers themselves. First, time-series clustering of performance volume (number of performances per annum) over time factored on musical works (pieces) and their composers is performed to model how new music has been adopted by the ensemble. The orchestra's discovery and adoption of music can be characterized as a Fourier decomposition of the performance volume time-series. Then, nodes on a social network are given by the population of performers named in the database; edges between two nodes indicate a collaborative performance. The interactions between these adoption profiles and their performers are studied and general trends in the musical performance history of the New York Philharmonic are inferred.

Demo/Poster Presenter
EB

Eamonn Bell

PhD Candiate in Music Theory, Graduate School of Arts and Sciences
Eamonn Bell graduated from Trinity College, Dublin with a B.A. (Mod.) Mathematics and Music in June 2013. He was awarded the University Gold Medal for performance in the degree examinations. He was awarded the Geoffrey Singleton Prize and the Mahaffy Memorial Prize for "an essay on the theory or history of music, embodying some original research", for his B.A. dissertation on a model for fugal counterpoint in the music of Byrd.  He... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Model-Based Dashboards for Customer Analytics [P28]
Automating the customer analytics process is crucial for companies managing distinct customer bases. In dynamic spending environments, visualization plays a key role in understanding events of interest. These ideas have led to the real world popularity of analytics dashboards, a tool that has received scant attention from academics. In this work, we develop a nonparametric framework for understanding individual-level spending using Gaussian process priors over latent functions that describe customer spending along calendar, interpurchase, and customer lifetime dimensions. These curves form a dashboard that provides a visual representation of purchasing dynamics. The model flexibly and automatically captures the impact of events that influence spend propensity, even when these events are unknown a-priori. We illustrate the use of our model on spending data from two popular mobile games, and show that it generalizes common customer base analysis models, leading to better performance both in fitting and forecasting spending incidence.

Demo/Poster Presenter
avatar for Ryan Dew

Ryan Dew

PhD Candidate in Marketing, Columbia Business School
Ryan is a third year doctoral student in the Marketing Division of Columbia University's Graduate School of Business with a focus on Quantitative Marketing. His research focuses on developing and applying methods from Bayesian econometrics and machine learning to problems in marketing analytics. He graduated from the University of Pennsylvania with a B.A. in Mathematics, with a focus on applied statistics.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Personal Energy Footprinting [P18]
Recent advancements in energy monitoring technologies have contributed hugely to developing smart and energy-efficient buildings. However, existing solutions do not provide enough granularity to generate sufficient information about the real-time effect of an occupant’s personal actions on the overall energy consumption of a building. Extending the functionality of currently existing indoor localization and building energy monitoring techniques, our platform tracks each individual’s energy consumption in a shared environment, thus providing the user with visibility into his or her real-time energy footprint. The system we have implemented facilitates accountability of energy usage in commercial buildings, while simultaneously utilizing that information to provide actionable feedback and historical understanding for the occupants as well as building managers, ensuring that they can act appropriately in a timely manner.

Demo/Poster Presenter
avatar for Richa Glenn Netto

Richa Glenn Netto

MS Student in Electrical Engineering, Columbia Engineering
Richa Netto received her B.E. degree in Computer Engineering from the University of Mumbai in May 2015, and is currently pursuing a Masters in Electrical Engineering from Columbia University. Her primary areas of interest include Embedded Systems Design and the application of the Internet of Things in creating Smarter Environments.
avatar for Rishikanth Chandrasekaran

Rishikanth Chandrasekaran

MS Student in Computer Engineering, Columbia Engineering
Rishikanth finished his Bachelors in Electrical and Electronics Engineering in India and is currently pursuing his Masters in Computer Engineering at Columbia University. He is currently part of the Intelligent and Connected Systems Laboratory at Columbia University as a researcher. He specializes in designing Embedded and Cyber-Physical Systems with a focus on Internet of Things for creating smart and responsive environments.

Demo/Poster Collaborator
avatar for Xiaofan (Fred) Jiang

Xiaofan (Fred) Jiang

Assistant Professor of Electrical Engineering, Columbia Engineering
Xiaofan (Fred) Jiang is an Assistant Professor in the Electrical Engineering Department at Columbia University. Fred received his B.Sc. (2004) and M.Sc. (2007) in Electrical Engineering and Computer Science, and his Ph.D. (2010) in Computer Science, all from UC Berkeley. Before joining SEAS, he was Senior Staff Researcher and Director of Analytics and IoT Research at Intel Labs China. Fred’s research interests include cyber physical... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Preventing Code-Reuse Attacks with Instruction-Set Randomization [P24]
Instruction Set Randomization (ISR) was proposed in the last decade as a countermeasure against code injection attacks, where attackers introduce new code into the system as a step towards gaining control. Conventional wisdom is that ISR has lost its relevance due to the prevalence of code-reuse attacks, , a newer and harder threat, wherein the attackers stitches together existing code towards the same end. Code-injection no longer remains a critical component in typical contemporary attacks. In this work, we show that ISR is ineffective even against code-injection but (surprisingly) can be relevant against code-reuse attacks. However, to provide this capability, ISR needs to satisfy additional properties, specifically strong encryption, not found in older ISR implementations. We implement a new ISR system, called Polyglot, on a SPARC32-based Leon3 FPGA system that runs Linux. We show that it incurs very low performance overhead (approx. 6% for SPEC CPU benchmarks), while defending against ROP attacks and allowing critical features like page-sharing. Additionally, we argue that for threat models used by previous work, our scheme incurs no overhead on modern systems.

Demo/Poster Presenter
KS

Kanad Sinha

PhD Candidate in Computer Science, Columbia Engineering

Demo/Poster Collaborator
VK

Vasileios Kemerlis

PhD Candidate in Computer Science, Columbia Engineering
AK

Angelos Keromytis

Associate Professor of Computer Science, Columbia Engineering
avatar for Simha Sethumadhava

Simha Sethumadhava

Associate Professor of Computer Science, Columbia Engineering
Simha Sethumadhavan is an Associate Professor of Computer Science at Columbia Engineering. He is the founding director of the Computer Architecture and Security Technologies Lab (CASTL) at Columbia University. Sethumadhavan’s research interests are in hardware security, hardware support for security and privacy and energy-efficient computing. He has been recognized with an NSF CAREER award (2011), a top paper award (2004) and a teaching... Read More →

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Real-Time Optical Spectroscopic Monitoring of Permanent Lesion Progression During Cardiac Radiofrequency Ablation [P8]
Despite considerable advances in guidance of radiofrequency ablation (RFA) therapies for atrial fibrillation, success rates have been hampered by an inability to intraprocedurally characterize the extent of permanent injury. Insufficient lesions can elusively create transient conduction blockages that eventually re-conduct. Prior studies suggest significantly greater met-myoglobin concentrations (ctMmb) in the lesion core than in the healthy myocardium and may serve as a marker for irreversible tissue damage. In this work, we present real-time monitoring of permanent injury through spectroscopic assessment of ctMmb at the catheter tip. A commercial RFA catheter was modified accept illumination and collection fiber pairs to acquire real-time optical measurements throughout RF energy delivery. Dynamic changes in ctMmb were recovered from near-infrared diffuse reflectance spectra using a two-step inversion routine. A robust correlation (r=0.88,P<1e-7) was observed between extracted tissue ctMmb and the extent of tissue injury. These results support the use of spectroscopy-facilitated guidance of RFA procedures.

Demo/Poster Presenter
avatar for Charles C. Marboe, MD

Charles C. Marboe, MD

Professor of Pathology and Cell Biology, College of Physicians and Surgeons
Dr. Charles C. Marboe graduated from the Pennsylvania State University College of Medicine in 1976. He works in New York, NY and specializes in Anatomic Pathology. Dr. Marboe is affiliated with New York Presbyterian Hospital Columbia University Medical Center.
avatar for Christine P. Hendon

Christine P. Hendon

Assistant Professor of Electrical Engineering, Columbia Engineering
Christine Hendon is an assistant professor in the Department of Electrical Engineering.  Her research interests are in developing optical imaging and spectroscopy instruments for applications in cardiac electrophysiology and interventional cardiology. Dr. Hendon received the B.S. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2004, and M.S. and Ph.D. degrees in Biomedical Engineering... Read More →
RS

Rajinder Singh-Moon

PhD Candidate in Electrical Engineering, Columbia Engineering
avatar for Vivek Iyer, MD

Vivek Iyer, MD

Assistant Professor of Medicine, College of Physicians and Surgeons
Vivek Iyer, MD, MSE is a cardiac electrophysiologist, specializing in treating heart rhythm abnormalities. Dr. Iyer is boarded in Internal Medicine, Cardiovascular Disease and Clinical Cardiac Electrophysiology.
avatar for William Whang, MD

William Whang, MD

Associate Professor of Medicine, College of Physicians and Surgeons
avatar for Xinwen Yao

Xinwen Yao

PhD Candidate in Electrical Engineering, Columbia Engineering


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

SEUS - Audio Based Vehicle Localization [P19]
The rapid growth of commercial technologies made our environment and behavior change much faster than our body and natural skills. While thousands of years of evolution have trained us to cope with tasks that guaranteed our survival, our constant pursuit for a more confortable life introduced other unpredictable dangers in few decades. The increase in the number of automobiles together with the high demographic density of the modern cities, make the urban regions a hotspot for these hostile situations. As a solution we are introducing the SEUS (Sense Enhancement for Urban Safety), an embedded IoT system that uses multiple sensors, advance recognition algorithms, and cloud computing to scan the environment for potential treats and alert the user. The first SEUS prototype uses multiple MEMS microphones spread over the body to localize incoming vehicles.

Demo/Poster Presenter
avatar for Daniel de Godoy Peixoto

Daniel de Godoy Peixoto

PhD Candidate in Electrical Engineering, Columbia Engineering
Daniel de Godoy Peixoto is a PhD Candidate at Columbia University . Daniel received his Electrical Engineering B.Sc. (2007) at the Universidade Federal de Pernambuco,Brazil and M.S. (2015) at Columbia University. Daniel has experience designing Analog Integrated Systems and is currently researching the role of Analog Circuits on IoT Systems and how they can unveil new possibilities for wearable applications.
avatar for Peter Kinget

Peter Kinget

Professor of Electrical Engineering, Columbia Engineering
Peter R. Kinget received an engineering degree in electrical and mechanical engineering and the Ph.D. in electrical engineering from the Katholieke Universiteit Leuven, Belgium. He has worked in industrial research and development at Bell Laboratories, Broadcom, Celight and Multilink before joining the faculty of the Department of Electrical Engineering, Columbia University, NY in 2002. He is also a consulting expert on patent litigation and a... Read More →
avatar for Xiaofan (Fred) Jiang

Xiaofan (Fred) Jiang

Assistant Professor of Electrical Engineering, Columbia Engineering
Xiaofan (Fred) Jiang is an Assistant Professor in the Electrical Engineering Department at Columbia University. Fred received his B.Sc. (2004) and M.Sc. (2007) in Electrical Engineering and Computer Science, and his Ph.D. (2010) in Computer Science, all from UC Berkeley. Before joining SEAS, he was Senior Staff Researcher and Director of Analytics and IoT Research at Intel Labs China. Fred’s research interests include cyber physical... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Tax Laws and Tax Capacity: A Machine-Learning Approach [P30]
I use tools from natural language processing to construct a high-dimensional representation of tax code changes from the text of 1.6 million statutes enacted by state legislatures since 1963. A data-driven approach is taken to recover the effective tax code – the set of legal phrases in tax law that have the largest impact on revenues, holding major tax rates constant. Exogenous variation in tax legislation from judicial districts is used to capture revenue impacts that are solely due to changes in the tax code language, with the resulting phrases providing a robust out-of-sample predictor of tax collections. I then test whether political parties differ in patterns of effective tax code changes when they control state government. Relative to Republicans, Democrats use revenue-increasing language for income taxes but use revenue-decreasing language for sales taxes – consistent with a more redistributive fiscal policy – despite making no changes on average to statutory tax rates.

Demo/Poster Presenter
avatar for Elliott Ash

Elliott Ash

PhD Candidate in Economics, Graduate School of Arts and Sciences
Elliot Ash is a Ph.D. student in Economics. His research interests include Political Economy, Law and Economics, Public Economics, Applied Microeconomics, Natural Language Processing, Machine Learning. | |  


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

The Hidden Advantage of Lefties in Sports [P29]
In the modern era of professional tennis, there have been many great left-handed players. Although only 11% of the world's population is left-handed, left-handers comprise roughly 15% of professional tennis players. In sports as varied as boxing, baseball and fencing, the contrast is even more stark. Here we present a method for extracting the advantage of being left-handed in sports (as well as the inherent skill of each player) from match results, applying it to data from men’s professional tennis. Unlike previous point estimate approaches to this problem, our formulation is Bayesian and uses induced order statistics to address the truncated nature of the data set. We further demonstrate how the question can be approached in the absence of explicit match result data, outlining a methodology that can be used to determine the latent advantage of specific factors wherever there exists notions of ranking and competition.

Demo/Poster Presenter
avatar for Francois Fagan

Francois Fagan

PhD Candidate in Industrial Engineering and Operations Reasearch, Columbia Engineering
Francois Fagan started his PhD in the IEOR department in September 2013. He is currently working with Professors Martin Haugh and Garud Iyengar in the field of machine learning. Before coming to Columbia University, he attended the University of Cape Town in South Africa where he received a BSc (Honours) in Mathematics and Applied Mathematics in 2010. In 2012-2013 he completed a masters at Stellenbosch University, also in South Africa, in... Read More →
avatar for Hal Cooper

Hal Cooper

PhD Candidate in Industrial Engineering and Operations Reasearch, Columbia Engineering
Hal Cooper is an IEOR Ph.D. Candidate who began his Ph.D. in the fall of 2013 under adviser Garud Iyengar. Hal works on a variety of machine learning problems, particularly Bayesian inference and deep learning. His research focuses on the development of new modeling techniques for these frameworks, and their application to network science and computational neuroscience.    Hal holds a Master of Science in Operations Research from... Read More →

Demo/Poster Collaborator
avatar for Martin Haugh

Martin Haugh

Associate Professor of Professional Practice in Industrial Engineering and Operations Research, Columbia Engineering
Martin Haugh originally joined the Industrial Engineering and Operations Research Department in January 2002 after completing his PhD in Operations Research at MIT. He was a faculty member in the IEOR department until June 2005 and during this time his teaching and research focused on financial engineering. Between 2005 and 2009 he worked as a quant in the hedge fund industry in New York and London. He then returned to academia and the... Read More →
GI

Garud Iyengar

Professor of Industrial Engineering and Operations Research and Department Chair, Columbia Engineering
Professor Garud Iyengar joined Columbia University’s Industrial Engineering and Operations Research Department in 1998. Professor Iyengar teaches courses in simulation and optimization. Professor Garud Iyengar’s research interests include convex optimization, robust optimization, queuing networks, combinatorial optimization, mathematical and computational finance, communication and information theory. He has published in... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

The Impact of Earthquakes on Economic Productivity [P20]
This project combines natural science data with social science data, applying an interdisciplinary approach to investigate the long-term economic impacts of earthquakes. USGS ShakeMap data is used to provide a measure for the exogenous natural hazard of earthquakes in terms of peak ground acceleration. In the past, social science research has predominantly employed inadequate measures for the natural hazard of earthquakes. Here, a data set that represents global relevant ground shaking since 1973 is constructed and used for the first time to analyze global economic impacts. This data set is combined with social productivity data on two different geographic levels. First, conventional country-level World Bank GDP data is considered and then compared with an approach that looks at a 1x1 degree grid level, by using gridded G-Econ output data. Different regression models are applied for the quantitative analysis with particular focus on the spatial nature of the data.

Demo/Poster Presenter
avatar for Stephanie Lackner

Stephanie Lackner

PhD Candidate in Sustainable Development, School of International and Public Affairs
Stephanie Lackner is a PhD candidate in the Sustainable Development PhD program at SIPA. Her research interest are disasters and their short and long term socio-economic impacts, particularly earthquakes and other natural disasters. She holds a Master degree in Mathematics from the Vienna University of Technology.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Towards the Automatic Classification of Endomyocardial Tissues for Intracardiac OCT [P9]
Aiming to establish the relationship between ultrastructure and endomyocardial tissue types, especially diseased tissue, we develop an automated algorithm to segment and classify tissue types from intracardiac OCT images. We segmented the OCT image volumes using a graph searching method. Features are extracted and compared in each segmented region. A probabilistic model of relevance vector machine is developed to classify multiple tissue types such as scar, fibrotic myocardium, normal myocardium, endocardium, and adipose tissue. The algorithm is validated from OCT images obtaining from human heart. The tissue types are classified with a good accuracy and are visualized in three dimensions.

Demo/Poster Presenter
avatar for Yu Gan

Yu Gan

PhD Candidate in Electrical Engineering, Columbia Engineering
Yu Gan is a Ph.D. candidate in the Department of Electrical Engineering at Columbia University. He is a research assistant in the Structure Function Imaging Laboratory under supervision of Dr. Christine Hendon. His research interest involves image processing. He is working towards development of a new  analysis tool for image of optical coherence tomography.


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Using Social Media to Detect Foodborne Disease Outbreaks [P10]
Foodborne diseases are estimated to cause 3,000 deaths per year in the United States and many of these cases are caused by restaurants. Identifying and acting on outbreaks of these foodborne diseases quickly is essential to mitigating their negative effects on public health. Although there are official channels to report incidents of food poisoning to the local health departments, often restaurant patrons instead post informal complaints about their negative experiences on social media sites, such as Yelp and Twitter. In this work we construct a social media analysis system, targeted at identifying food poisoning-related documents from multiple online noisy text sources. By tracking social media posts from NYC that contain information about food poisoning incidents, we can successfully identify foodborne illness outbreaks that would otherwise go uninvestigated. These actionable inferences are then utilized by the NYC Department of Health to alleviate the consequences of outbreaks in NYC restaurants more effectively.

Demo/Poster Presenter
avatar for Tom Effland

Tom Effland

PhD Candidate in Computer Science, Columbia Engineering
Effland is an  NSF IGERT "Data to Solutions"​ fellow working with Prof. Luis Gravano. He researches novel techniques for extracting actionable information on rare events from social media. He is currently working on a project finding evidence of point-source food poisoning outbreaks from Twitter, Yelp, etc. to help the NYC Department of Health launch targeted investigations of restaurants more responsively.

Demo/Poster Collaborator
FP

Fotis Psallidas

PhD, Computer Science, Columbia University

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

2:00pm

Virtual Replicas for Remote Assistance in Virtual and Augmented Reality [P33]
In many complex tasks, a remote subject-matter expert may need to assist a local user to guide actions on objects in the local user's environment. However, effective spatial referencing and action demonstration in a remote physical environment can be challenging. We introduce two approaches that use Virtual Reality (VR) or Augmented Reality (AR) for the remote expert, and AR for the local user, each wearing a stereo head-worn display. Both approaches allow the expert to create and manipulate virtual replicas of physical objects in the local environment to refer to parts of those physical objects and to indicate actions on them. This can be especially useful for parts that are occluded or difficult to access.

Demo/Poster Presenter
avatar for Barbara Tversky

Barbara Tversky

Professor of Psychology and Education, Teachers College
Barbara Tversky is Professor of Psychology and Education at Columbia Teachers College and Professor Emerita of Psychology at Stanford University.  She has done basic research on memory, categorization, spatial language and thinking, event perception and cognition with applications to eyewitness testimony, cognitive maps, visualizations, HCI, diagrammatic reasoning, design, and the arts. She has enjoyed collaborations with computer... Read More →
avatar for Carmine Elvezio

Carmine Elvezio

Staff Associate in Computer Science, Columbia Engineering
Carmine Elvezio is a staff associate in the Computer Graphics and User Interfaces Lab at Columbia University. His research interests include interaction and visualization techniques in augmented and virtual reality and system design of real-time interactive 3D graphics applications. He received his MS in Computer Science from Columbia University in 2012 and his BS in Computer Science from the Polytechnic Institute of New York University in... Read More →
avatar for Mengu Sukan

Mengu Sukan

PhD Candidate in Computer Science, Columbia Engineering
Mengu Sukan is a PhD student working with Steven Feiner in the Computer Graphics and User Interfaces Lab at Columbia University.  In his research, he designs and evaluates novel 3D visualizations and interaction techniques focusing on augmented reality (AR) for task assistance. Mengu has published papers, posters, and demos at the most selective venues for AR research (ISMAR, UIST, VR/3DUI, and CHI).
avatar for Steven Feiner

Steven Feiner

Professor of Computer Science, Columbia Engineering
Steven Feiner is professor of computer science at Columbia Engineering, where he directs the Computer Graphics and User Interfaces Lab and co-directs the Columbia Vision and Graphics Center. His interests include human–computer interaction, augmented reality and virtual environments, 3-D user interfaces, knowledge-based design of graphics and multimedia, mobile and wearable computing, computer games, and information visualization. Feiner... Read More →

Demo/Poster Collaborator
avatar for Ohan Oda

Ohan Oda

PhD, Computer Science, Columbia University
Ohan Oda is a Ph.D candidate in Computer Science and a member of the Computer Graphics and User Interface Lab. He is currently developing the Goblin XNA infrastructure, which is a platform for research on 3D user interfaces, including augmented reality and virtual reality, with an emphasis on games. He is broadly interested in applications of mobile augmented reality systems in the field of recreation and entertainment, including virtual sports... Read More →


Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

4:30pm

Industry Partners | Thank You
DATA SCIENCE INDUSTRY AFFILIATES | THANK YOU FOR YOUR PARTNERSHIP

For information about the Institute's Industry Affiliates program, please contact us at datascience@columbia.edu.


Wednesday April 6, 2016 4:30pm - 5:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

4:30pm

Networking Reception

Networking Reception (Meet, Greet and Eat): To close the day, we will host a reception. Students, faculty and industry are encouraged to attend. A poster session will be


Wednesday April 6, 2016 4:30pm - 5:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040