Mohammad Mosaffa

Biography

I am a Ph.D. student in Quantitative Marketing at Cornell University (Cornell Tech & Johnson Graduate School of Management), where my research bridges machine learning, causal inference, and economic theory to study how data and algorithms shape Personalization, Polarization, and Privacy (PPP) in digital platforms. Broadly, my work develops decision-focused machine learning frameworks that connect computational modeling with the economics of information, with applications to unstructured media content, digital advertising, and platform decision-making.
Before Cornell, I completed an M.Sc. in Mathematics at the University of British Columbia, where I explored deep learning methods for text-based prediction of waiting times in service and healthcare systems. I also hold a B.Sc. in Industrial Engineering from Tehran Polytechnic, where I developed data-driven task allocation models for service operations.