Hal Cooper

Hal is a doctoral student interested in graph computing, graph databases, and machine learning. He has applied this interest to problems from a variety of fields, including finance, computational neuroscience, sports analytics, and information retrieval.

Through close connections with industry (including joint study agreements and internships at Goldman Sachs, IBM, and Graphen, Inc.), Hal uses state of the art theory to tackle practical problems. Hal's dissertation work focuses on the research and development of graph database and computing technologies suited to massively concurrent access and other real-world requirements.


Email: [email protected]
Start Date: Sep 01, 2013
Faculty Advisor: Garud Iyengar
Program: PhD OR