Shipra Agrawal is an Assistant Professor in the Department of Industrial Engineering and Operations Research, and member of Data Science Institute, at Columbia University. Her research spans several areas of optimization and machine learning, including data-driven optimization under partial, uncertain, and online inputs, and related concepts in learning, namely multi-armed bandits, online learning, and reinforcement learning. She is also interested in prediction markets and game theory. Application areas of her interests include internet advertising, recommendation systems, revenue management and resource allocation problems. She serves on editorial board of Management Science. Shipra received her PhD in Computer Science from Stanford University in June 2011 under guidance of Prof. Yinyu Ye, and was a researcher at Microsoft Research India from July 2011 to August 2015. For further information, please see CV . Here is a press article about some of her recent research.