Shipra Agrawal is an Assistant Professor in the Department of Industrial Engineering and Operations Research, and a member of Data Science Institute at Columbia University. Her research focuses on learning to make decisions using synergistic methods that combine data analytics, machine learning, and optimization techniques. Specific topics of her interest include multi-armed bandits, online learning, online optimization, and reinforcement learning, with applications in dynamic pricing, online retail, internet advertising, recommendation systems, and dynamic resource allocation.
Agrawal joined Columbia in September 2015 from Microsoft Research where she worked in the Machine learning and Optimization group in Bangalore. Previously, she received her PhD in Computer Science from Stanford University in June 2011.