Daniel Russo
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Philip H. Geier Jr. Associate Professor at Columbia Business School |
About Me
I am an associate professor in the Decision, Risk, and Operations division of Columbia Business School. My research is motivated by the long-term aspirations of reinforcement learning: to design agents or systems that learn through interaction to select effective sequences of decisions toward a goal. This is a naturally interdisciplinary research area with roots in AI, operations research, statistics, control theory, and economics.
I've tried to ground this longer-term research by working on frontiers of industry practice. Currently, I work as an Amazon Scholar applying reinforcement learning to supply chain optimization. I previously spent five years working with Spotify to apply reinforcement learning and large language models to audio recommendations.
I completed my undergraduate studies in math and economics at the University of Michigan, doctoral studies at Stanford University under the supervision of Benjamin Van Roy, and worked as a postdoctoral researcher at Microsoft Research New England. My research has been recognized by several awards in the operations research community: the George Nicholson Prize (best paper by a PhD student), the JFIG Paper Award (best paper by a junior faculty member), the Frederick W. Lanchester Prize (best contribution to operations research in the past five years), and the Erlang Prize (early career award for contributions to applied probability). I currently serve as an associate editor at Management Science, Operations Research, and Stochastic Systems.
AI Agents Initiative
I am one the leaders of a new AI Agents Initiative at Columbia. We have funding for multiple positions at the postdoctoral and pre-doctoral level.