Assaf Zeevi is Professor and holder of the Kravis chair at the Graduate School of Business, Columbia University. His research and teaching interests lie at the intersection of Operations Research, Statistics, and Machine Learning. In particular, he has been developing theory and algorithms for reinforcement learning, Bandit problems, stochastic optimization, statistical learning and stochastic networks. Assaf's work has been applied in online retail, healthcare analytics, dynamic pricing, recommender systems, and social learning in online marketplaces.
Assaf received his B.Sc. and M.Sc. (Cum
Laude) from the Technion, in Israel, and subsequently his Ph.D. from
Stanford University. He spent time as a visitor at Stanford University,
the Technion and Tel Aviv University. He is the recipient of several
teaching and research awards including a CAREER Award from
the National Science Foundation, an IBM Faculty Award, Google
Research Award, as well as several best paper awards including the 2019
Lanchester
Prize. Assaf has recently served a term as Vice Dean at
Columbia Business School and Editor-in-Chief of Stochastic Systems (the
flagship journal of INFORMS' Applied Probability Society). He also
serves on various other editorial boards and program committees in the
Operations Research and Machine Learning communities, as well as
scientific advisory boards for startup companies in the high technology
sector.