Sadegh Shirani
About me
I am a third-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 explores questions related to causal inference, high dimensional statistics, and reinforcement learning, particularly in the context of designing experiments in the presence of complex network interference effects.
Email: sshirani 'at' stanford 'dot' edu
Working Papers
(1) Causal Message Passing: A Method for Experiments with Unknown and General Network Interference
with M. Bayati
(2) Asymptotic Analysis of Multi-Class Advance Patient Scheduling
with H. Abouee-Mehrizi and M. K. S. Faradonbeh
Second place, INFORMS Health Applications Society (HAS) 2023 Best Student Paper Competition
MSOM Healthcare SIG 2023
Finalist, Canadian Operations Research Society 2022 Student Paper Award
Journal Papers
(1) Departure Time Choice Models in Urban Transportation Systems Based on Mean Field Games
with M. Ameli, JP Lebacque, H. Abouee-Mehrizi, L. Leclercq, Transportation Science 56(6):1483-1504, 2022.
Best Paper, INFORMS TSL Urban Transportation SIG 2022
Refereed Conference Papers
(1) Online Reinforcement Learning in Stochastic Continuous-Time Systems
with M. K. S. Faradonbeh, Proceedings of Thirty Sixth Conference on Learning Theory (COLT), PMLR 195:612-656, 2023.
(2) Thompson Sampling Efficiently Learns to Control Diffusion Processes
with M. K. S. Faradonbeh and M. Bayati, Neural Information Processing Systems (NeurIPS), 2022.
(3) Bayesian Algorithms Learn to Stabilize Unknown Continuous-Time Systems
with M. K. S. Faradonbeh, IFAC International Workshop on Adaptive and Learning Control Systems (ALCOS), 2022
(4) Mean Field Games Framework to Departure Time Choice Equilibrium in Urban Traffic Networks
with M. Ameli, JP. Lebacque, H. Abouee-Mehrizi, L. Leclercq, Transportation Research Board 100th Annual Meeting-A Virtual Event (TRB), 2021