Can Li

Dr. Can Li is an Assistant Professor in the Department of Chemical Engineering at Purdue University's College of Engineering. He earned his Ph.D. in Chemical Engineering from Carnegie Mellon University and completed a postdoctoral fellowship at Polytechnique Montreal, focusing on process systems engineering and machine learning applications.

Research Interests: Dr. Li specializes in Process Systems Engineering, with a strong emphasis on Machine Learning techniques applied to High-Energy Physics and Computational Methods. His work bridges engineering principles with advanced computational frameworks, addressing challenges in particle physics experiments and environmental modeling.

Publication Trends: Dr. Li's recent work spans machine learning infrastructure (e.g., SuperSONIC), particle detector development (e.g., ATLAS and CMS experiments), and cosmic ray analysis (e.g., ENDA and LHAASO hybrid detection). His research also extends to anomaly detection in science and optimization of high-energy physics workflows.