I am an Assistant Professor of Data Sciences and Operations at the USC Marshall School of Business. Prior to joining USC, I was a UC President’s Postdoctoral Fellow at UC Berkeley. I received my Ph.D. at Stanford University in the Operations Research group within the Department of Management Science & Engineering, and was a research fellow at the Simons Institute for the Theory of Computing. Earlier, I earned a B.Sc. in Computer Engineering with a minor in Mathematics from Sharif University of Technology.

I develop principled methods for learning and decision-making in complex systems, where data is often incomplete, costly to collect, or influenced by strategic behavior. Drawing on tools from applied probability, optimization, and algorithm design, my research contributes to the foundations of machine learning and operations research. I design robust, data-efficient algorithms that enable reliable inference and intervention in domains such as public health, and online platforms—where decisions must often be made under uncertainty and partial observability.

As one illustration of my broader agenda, I have designed algorithms with provable theoretical guarantees to predict epidemic trajectories using small, local network samples—eliminating the need for parametric model assumptions about the underlying network. In a different line of work, I collaborated with the Los Angeles Unified School District (LAUSD) to create network models for epidemic spread, guiding COVID-19 reopening strategies and informing safer, more equitable policy decisions.

For a full list of my publications, click here.

Email:yalimoha@usc.edu.