Daniel Russo
 |
Philip H. Geier Jr. Associate Professor at Columbia Business School |
About Me
I an associate professor in the Decision, Risk, and Operations division of the Columbia Business School. I teach a core MBA course on statistics and a PhD course on dynamic optimization. My research lies at the intersection of machine learning and online decision making, mostly falling under the broad umbrella of reinforcement learning. Outside academia, I work as an Amazon scholar applying reinforcement learning to supply chain optimization. I previously spent five yeras working with Spotify to apply reinforcement learning and large language models to audio recommendations.
My research has been recognized by the Erlang Prize, the Frederick W. Lanchester Prize, a Junior Faculty Interest Group Best Paper Award, and first place in the George Nicholson Student Paper Competition. I currently serve as an associate editor at Management Science, Operations Research, and Stochastic Systems.
Prior to joining Columbia, I spent one great year as an assistant professor at Northwestern's Kellogg School of Management and one year at Microsoft Research in New England as Postdoctoral Researcher. I received my PhD from Stanford University in 2015, where I was advised by Benjamin Van Roy. In 2011 I received my BS in Mathematics and Economics from the University of Michigan.
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.