Jialin Li
Portrait of Jialin Li

Visiting Assistant Professor

Department of Mathematics and Statistics

University of Massachusetts Amherst

I am a Visiting Assistant Professor at the Department of Mathematics and Statistics, University of Massachusetts Amherst. Previously I was a Postdoc Research Fellow in the area of Operations Management and Statistics at the Joseph L. Rotman School of Management, University of Toronto, under the supervision of Ningyuan Chen, Ming Hu and Sheng Liu. I received my PhD in applied math (AMSC) from the University of Maryland, College Park. I was fortunate to be advised by Ilya Ryzhov.

My research focuses on stochastic black-box models and uncertainty quantification. I look for new perspectives, new frameworks, and new models at the intersection of statistics and operations.

Papers

Authors in alphabetical order for all of my papers.

Work in Progress

Coming up next: 🐔!

Working Papers

Dynamic Balancing and Matchmaking in Competitive Live-Service Games.

Jialin Li, Zihao Qu, Mengfan Xu

Major Revision / Management Science

Data privacy in pricing: Estimation bias and implications.

Ningyuan Chen, Ming Hu, Jialin Li, and Sheng Liu

Resubmitted after Minor Revision / Manufacturing & Service Operations Management

MSOM iFORM SIG Day Presentation 2026 (iFORM = the Interface of Finance, Operations and Risk Management; SIG = Special Interest Group)

Publications

Moderate deviations inequalities for Gaussian process regression.

Jialin Li, and Ilya Ryzhov

Journal of Applied Probability 61(1): 172–197.

This paper has been selected for inclusion in the February 2025 Applied Probability Collection on the topic of Gaussian processes. This collection features ten notable articles published by the Applied Probability Trust, showcasing cutting-edge developments in the field. I am grateful for this recognition.

Convergence rates of epsilon-greedy global optimization under radial basis function interpolation.

Jialin Li, and Ilya Ryzhov

Stochastic Systems 13(1): 59–92.

Other Preprints

Guaranteed simultaneous asymmetric tensor decomposition via alternating subspace iteration.

Furong Huang, Jialin Li, and Xuchen You

To be submitted within a finite period of time.