Shipra Agrawal

Assistant Professor
Industrial Engineering and Operations Research
Member, Data Science Institute (DSI)
Affiliate, Department of Computer Science
Columbia University
Office: Mudd 423 Phone: 212 853 0684
Spring 2020 office hours: Tue 9am-10am

Brief Bio

Shipra Agrawal is Cyrus Derman Assistant Professor of the Department of Industrial Engineering and Operations Research. She is also affiliated with the Department of Computer Science and the Data Science Institute, at Columbia University. She received her PhD in Computer Science from Stanford University in June 2011 under the guidance of Prof. Yinyu Ye, and was a researcher at Microsoft Research India from July 2011 to August 2015. Her research spans several areas of optimization and machine learning, including online optimization under uncertainty, multi-armed bandits, online learning, and reinforcement learning. She is also interested in prediction markets and game theory.
Shipra serves as an associate editor for Management Science (Optimization area) and Mathematics of Operations Research (Learning theory area) and INFORMS Journal on Optimization. Her research is supported by a Google Faculty research award (2017), Amazon research award (2017), and an NSF CAREER Award. For further information, please see CV .

Selected Publications

(A full list of journal and conference papers is here )

Grants and awards

Some recent professional activities


Contact Information


News and Events
2021 [all events are virtual]
  • April 22 Invited talk at IIT Delhi.
  • April 21 Invited talk at Stanford RAIN (Research on Algorithms and Incentives in Networks) seminar.
  • Feb 19 Seminar at Arizona State University, School of Computing and Decision Systems Engineering.
  • Feb 9 Princeton ORFE department seminar.
2020 [all events are virtual]
  • Dec 4 Invited talk at Illinois Seminar on Data Science and Dynamical Systems, UIUC.
  • Nov 12-14 Invited talk and session at INFORMS 2020 annual meeting.
  • October 27-30 Co-organizing a workhop on Mathematics of Online Decision Making at Simons Institute, Berkeley from Oct 27-30, 2020.
  • Oct 8 Keynote at RL workshop, Amazon Machine Learning Conference.
  • July 17/18 Invited talk at Theory of RL workshop at ICML 2020.
  • July 17/18 Invited talk on "Learning to manage inventory" at Real-World Experiment Design & Active Learning workshop at ICML 2020. Video is here (at 6:01:00))
  • May 18 Our paper on Reinforcement Learning for Integer Programming" won the most popular poster award and honorable mention for the best paper award at MIP 2020.
  • May 2 Online tutorial on Thompson Sampling for reinforcement learning, YSML workshop, Columbia University.

  • December 14, NeurIPS: Speaking at the NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop in Vancouver.
  • Nov 18, Caltech: Speaking at Keller Colloquium in Computing and Mathematical Sciences.
  • Nov 8, UT Austin: Speaking at UT Austin McCombs.
  • Oct 30-Nov 1, Columbia: Co-organizing an exciting Symposium on Trustworthy AI at Columbia University.
  • Oct 21, INFORMS: Tutorial on bandits at the INFORMS annual conference in Seattle.
  • Oct 20, INFORMS: Co-chairing Nicholson student paper prize committee with Lewis Ntaimo. Winners to be announced on Oct 20 at INFORMS!
  • Sep-Oct 2019: Serving as Senior PC member for AAAI 2020.
  • Sep 26 2019: Speaking at the Multi Armed Bandit Workshop in London.
  • Sep 23 2019: Speaking at the ARC colloquium at Georgia Tech, Atlanta.