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Columbia University’s Data Science Institute Presents:
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avatar for Hal Cooper

Hal Cooper

Columbia Engineering
PhD Candidate in Industrial Engineering and Operations Reasearch

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 Columbia University, and a Bachelor of Engineering (Electrical Engineering) from the University of Newcastle, Australia.