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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 • 2:00pm - 4:30pm
An Introduction to Stan [D1]

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"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

Attendees (7)