About
I hold a PhD in Quantitative Marketing from the Yale School of Management. 

I specialize in the use of machine learning (ML) and artificial intelligence (AI) for business applications. I employ disentanglement learning, a generative deep learning method, on unstructured product image data to automatically find and quantify human interpretable visual characteristics. I apply the learned visual characteristics to estimate consumer preferences for watches using visual conjoint analysis. Additionally, I examine the automobile market's structure by using structured performance characteristics as well as human interpretable visual characteristics learned from product images.

Before my PhD, I worked at Myntra (online fashion retailer), 21st Century Fox (broadcast media) and Tata Consultancy Services (IT). I also hold a Post Graduate Diploma in Management from Indian Institute of Management Ahmedabad, and a B.Tech. (Electrical Engineering) from Indian Institute of Technology Banaras Hindu University.

Update: I moved to the Purdue University Daniels School of Business starting Fall 2023! At Purdue, I teach the "Marketing Management" course.

Research Papers

Generative Interpretable Visual Design: Using Disentanglement for Visual Conjoint Analysis, with Alex Burnap and Vineet Kumar (Conditionally Accepted at Journal of Marketing Research) (PDF)

• Winner, 2023 ISMS Doctoral Dissertation Proposal Competition

• Finalist, 2023 ASA Statistics in Marketing Doctoral Research Award

Works in Progress

Market Structure Mapping with Visual Characteristics, with Vineet Kumar and Alex Burnap

Did Illegal Shopping Stymie India's Demonetization? Evidence from an Online Retailer, with K. Sudhir and Nitish Jain