Jiajin Li

Jiajin Li is an Assistant Professor in the Operations and Logistics Division at the UBC Sauder School of Business, concurrently affiliated with the Institute of Applied Mathematics (IAM) at the University of British Columbia. He holds a BSc in Statistics from Chongqing University and a PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong (CUHK). Prior to joining UBC, he was a postdoctoral researcher at Stanford University's Department of Management Science and Engineering.

His research focuses on continuous optimization, design and analysis of optimization algorithms, and machine learning, with emphasis on nonsmooth/nonconvex optimization, minimax problems, and distributionally robust optimization. His work bridges theoretical foundations with applications in graph data analysis and algorithmic stability.

He teaches courses including Logistics and Operations Management (BCom), Seminar on Theoretical Developments in Management (PhD), and Optimization Theory and Applications (PhD). He actively seeks PhD students with strong mathematical or coding backgrounds through UBC Sauder or IAM programs.

Key research contributions include advancements in primal-dual balancing for minimax optimization, stability evaluation via distributional perturbation analysis, and outlier-robust algorithms for graph data. His methodologies often integrate optimal transport theory and subdifferential analysis.

He is affiliated with multiple research communities, including the IEEE and conferences like NeurIPS, ICML, and ICLR. His work emphasizes algorithmic robustness and scalability in complex optimization landscapes.