Ankit Sisodia is an Assistant Professor of Marketing at Purdue University. His research spans two streams. The first develops interpretable machine learning methods for marketing, including a disentanglement-based approach for discovering visual product characteristics from image data, with applications on visual conjoint analysis, structural demand estimation and market structure mapping, as well as related work on interpretable audio features of branded sonic logos. The second studies consumer privacy, illicit economic behavior using forensic economics methods, and personalization effectiveness through field experiments.
His work has been recognized with the ISMS Doctoral Dissertation Proposal Award and as a finalist for the ASA Statistics in Marketing Doctoral Research Award. He holds a Ph.D. in Quantitative Marketing from the Yale School of Management, an MBA from the Indian Institute of Management Ahmedabad, and a B.Tech. in Electrical Engineering from IIT BHU. Prior to academia, he worked at Myntra, Star India (21st Century Fox), and Tata Consultancy Services. At Purdue, he teaches New Product Development.
