Jialin Li

Jialin Li is a Visiting Assistant Professor at the Department of Mathematics and Statistics, University of Massachusetts Amherst. Previously, he served as a Postdoc Research Fellow at the Joseph L. Rotman School of Management, University of Toronto, under Professors Ningyuan Chen, Ming Hu, and Sheng Liu. He earned his PhD in Applied Mathematics (AMSC program) from the University of Maryland, College Park, advised by Ilya Ryzhov. His research focuses on methodologies for decision-making under uncertainty, emphasizing societal impact through stochastic optimization, uncertainty quantification, and statistical learning.

His work has been recognized, including selection for the February 2025 Applied Probability Collection for his paper on Gaussian processes. He has secured grants such as the Graduate Student Summer Research Fellowship (University of Maryland, 2019), TD Management Data and Analytics Lab Research Grant (2023), and New Pilot Postdoc Funding (Rotman School of Management, 2022). His teaching is noted for award-winning excellence. Current affiliations include the Lederle Graduate Research Tower, UMass Amherst.

Research interests span theoretical advancements and applications, including data privacy in pricing (as explored in ongoing work). No lab/teams are explicitly listed, but collaborations are implied through his interdisciplinary work.