Mohamad Sadegh Shirani Faradonbeh

Sadegh Shirani received his PhD in Operations, Information & Technology at the Stanford Graduate School of Business. His research develops machine learning methods for modeling and decision-making in complex systems, spanning LLM-based simulation of human and human--AI dynamics, causal inference under network interference, and reliable AI for operational decision support. A recurring theme is that the underlying structure is hard to study directly: network connections are unknown, agent types are latent, or the relevant data are unstructured. He works on the theoretical foundations of these problems and builds tools that hold up in practice. In his work, he uses tools from graphical models, statistical physics, optimization, and probability theory. His 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.