Dr. Lin Fan

Biography

Lin Fan is an Assistant Professor of Operations at the Kellogg School of Management at Northwestern University. He joined Kellogg in September 2024 after serving as a Postdoctoral Scientist at Amazon in the Supply Chain Optimization Technologies division. Lin holds a PhD in Management Science and Engineering, as well as master's degrees in Statistics and Mechanical Engineering from Stanford University, and a bachelor's in Mechanical Engineering from Georgia Institute of Technology. His primary research interests lie at the intersection of applied probability and data-driven operations, with specializations in multi-armed bandits, reinforcement learning, statistical inference, stochastic processes, and stochastic simulation. In his academic role, Lin teaches emerging topics in operations management, focusing on decision-making under uncertainty and stochastic models. His scholarly work includes various journal articles, with a particular emphasis on robust bandit algorithms and their applications in operations research. Lin has been recognized with awards such as the Stanford University Centennial Teaching Assistant Award and the George Nicholson Student Paper Competition Place for his work on optimizing bandit algorithms. He is committed to advancing knowledge in the field of operations management, equipping students with the tools and insights necessary to excel in the industry.

Research Interests

Experience

Awards