Bio. My name is Parshan Pakiman. I am a Postdoctoral Principal Researcher at the University of Chicago Booth School of Business, affiliated with the Healthcare Initiative. I have the privilege of working with Professor Dan Adelman. I earned my Ph.D. in Information and Decision Sciences from the University of Illinois Chicago. I am honored to have Professor Selva Nadarajah as my doctoral thesis advisor. Before my doctoral studies, I obtained a B.Sc. in Applied Mathematics from the School of Mathematics, Statistics, and Computer Science at the University of Tehran.
I will be on the 2024-2025 academic job market!
Research. My research combines reinforcement learning (RL), optimization, and machine learning to develop computationally
efficient algorithms with theory for impactful operations management problems. My research has two avenues:
(1) I study emerging problems at the core of operating room management and retailing, where the applicability of existing methods is limited, necessitating the development of new reinforcement learning and data-driven optimization methods for these problems.
(2) I develop general-purpose reinforcement learning algorithms that guarantee near-optimal control policies for a broad class of Markov decision processes and can be easily adopted across applications without requiring domain knowledge.