I am Kexin Lin, a Ph.D. Candidate in Business Administration at the WPI Business School. My research lies at the intersection of operations research and machine learning, with a focus on performance evaluation and decision support. I integrate data envelopment analysis (DEA), mathematical optimization, and learning methods to develop approaches for performance benchmarking, clustering, and recommendation systems.
My work examines how performance information can guide learning and support business decisions, connecting methodological development with applications in digital platforms and sustainability. My research has appeared in Annals of Operations Research, Computers & Industrial Engineering, Journal of Cleaner Production, and Environment, Development and Sustainability, covering topics including recommendation systems, urban energy efficiency, and smart manufacturing.
My teaching interests include operations management, business analytics, operations research, and performance analytics. I have delivered instruction in DEA and machine learning, emphasizing the connection between analytical concepts and practical business problems. I also serve as an ad hoc reviewer for Annals of Operations Research, Journal of the Operational Research Society, and Ecological Indicators.
