Vice Provost for Advances in Learning Henry R. Byers Professor of Business Administration
Bharat N. Anand is Vice Provost for Advances in Learning and the Henry R. Byers Professor of Business Administration at Harvard Business School. Since 2013, Professor Anand has been the faculty chair of HBX, the Harvard Business School digital learning initiative that he helped to create. He helped oversee the design and creation of HBX’s digital learning platforms, and created one of its first online courses.
As Vice Provost, Professor Anand leads efforts to leverage technology to create more effective teaching tools, strategies, and resources. He oversees initiatives such as HarvardX, the Harvard Initiative for Learning and Teaching (HILT), the Advances in Learning Research Group, and DART (Digital Assets for Reuse in Teaching).
Professor Anand is an expert in digital strategy, media and entertainment strategy, corporate strategy, and organizational change. His work has examined competition in information goods markets, focusing on two central challenges that firms face in these markets: “getting noticed” amidst the increasing clutter of alternatives available to consumers, and “getting paid” for what they produce.
Professor Anand received his B.A. in economics from Harvard College magna cum laude, and his PhD in economics from Princeton University. He is a recipient of the Greenhill Award for outstanding contributions to Harvard Business School. Professor Anand lives in Wellesley, MA with his wife, Anju, and their daughter, Rhea.
He received a PhD in Politics from Princeton in 2010 and BA from the University of Rochester in 2001. His research interests include international relations, international political economy, statistical methodology, and experimental approaches to political science. His book on American foreign policy, Sailing the Water's Edge, was published in fall 2015, and was awarded the Gladys M. Kammerer Award for the best book published in the field of U.S. national policy. Recent projects include attitudes towards global climate technologies and policies, and the intersection of causal inference and machine learning methods for the social sciences.