Daniel Russo

Daniel Russo is an assistant professor in the Decision, Risk, and Operations division of Columbia Business School. His research lies at the intersection of statistical machine learning and sequential decision-making, and contributes to the fields of online optimization, reinforcement learning, and sequential design of experiments. He joined after spending a year as an assistant professor at Northwestern's Kellogg School of Management and one year at Microsoft Research in New England as postdoctoral researcher. He received his PhD from Stanford University in 2015, under the supervision of Benjamin Van Roy. In 2011, he received his BS in Mathematics and Economics from the University of Michigan.

Education

• Doctor of Philosophy (PhD) Stanford University (2011 — 2015)
• Bachelor of Science (BS) University of Michigan (2007 — 2011)

Companies

• Assistant Professor Columbia Business School (2017)
• Assistant Professor Kellogg School of Management (2016 — 2017)
• Postdoctoral Researcher Microsoft (2015 — 2016)
• Research Intern oDesk (2013 — 2014)
• Economic Consultant Intern Charles River Associates (2011 — 2011)
• Undergraduate Researcher University of Southern California (2010 — 2010)