Hal Cooper

Graduate Students, PhD
Hal is a 4th year PhD student interested in machine learning, network science, and game theory. He has applied this interest to problems from a variety fields, including computational neuroscience, sports analytics, and finance.
 
Through a Joint Study Agreement between IBM SystemG (IBM's network science research group) and IEOR, Hal's current research focuses on the development of scalable and interpretable game theoretic methodologies using graph database technology and recent developments in deep learning.
 
Faculty Advisor: Garud Iyengar


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