Sadegh Shirani
Sadegh Shirani
I am a fifth-year PhD student in Operations, Information & Technology at the Stanford Graduate School of Business, where I'm fortunate to be advised by Mohsen Bayati.
My research interests include causal inference, reinforcement learning, and stochastic modeling. At the core of my work is experimental design under network interference. I leverage insights from message passing models to develop methods for estimating causal effects when underlying network structures are unknown or poorly understood.
In my work, I use tools from probability theory, statistical physics, graphical models, and the theory of stochastic differential equations. My research is mainly motivated by studying systems where uncertainties, together with limited available data, compromise the quality of decisions. Examples include interventions in public health settings and experiments in ride-sharing systems.
Faculty Advisors
Research Interests
- Causal inference
- Reinforcement learning
- Stochastic modeling and optimization
- Generative diffusion models
Publications
*Second place, INFORMS Revenue Management and Pricing (RMP) Jeff McGill Student Paper Award, 2025. **Honorable mention, INFORMS Health Applications Society (HAS) Best Student Paper Competition, 2025. ***MSOM Technology, Innovation, and Entrepreneurship SIG, 2025
*Honorable mention, George Nicholson Student Paper Competition, 2024 and **Finalist, MSOM Student Paper Competition, 2024
*Short version in Neural Information Processing Systems (NuerIPS), 2022.
*Second place, INFORMS Health Applications Society (HAS) 2023 Best Student Paper Competition; **MSOM Healthcare SIG 2023; and ***Finalist, CORS 2022 Student Paper Award
*TSL Urban Transportation SIG Best Paper Award 2022