Dr. Yeganeh Alimohammadi

Biography

Yeganeh Alimohammadi is an Assistant Professor in the Data Sciences Operations at USC Marshall School of Business. Her research focuses on developing algorithms and models for decision-making under uncertainty, with practical applications in digital platforms, social networks, and epidemic forecasting. She integrates probability theory and algorithm design with machine learning techniques to address challenges related to scalability, robustness, and data uncertainty. In data-rich environments, she designs sampling and thinning methods that make large-scale analyses both tractable and reliable. In contrast, in data-scarce situations, she develops targeted data collection strategies and robust inference methods to help policymakers and organizations draw reliable conclusions from partial and noisy data. Before joining USC, Alimohammadi received her PhD in Management Science and Engineering from Stanford University and was recognized as a UC President’s Postdoctoral Fellow, as well as a UC Berkeley Research Fellow at the Simons Institute for Theory of Computing.

Research Interests