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Can Li is an Assistant Professor in the Davidson School of Chemical Engineering at Purdue University. He received his Bachelor of Engineering in Chemical Engineering from Tsinghua University in 2016 and his Ph.D. in Chemical Engineering from Carnegie Mellon University in 2021. His research interests focus on developing theory, algorithms, models, and software for large-scale optimization and machine learning applications in energy, chemical, and biological systems. He is particularly interested in creating optimization-inspired neural networks that enforce physical and logical constraints, and building large language model-powered interfaces for optimization machine learning models. Can Li has received multiple awards, including the National Science Foundation CAREER Award in 2025 and the Ralph W. Grace M. Showalter Research Trust Grant in 2024. He is dedicated to advancing the field of chemical engineering through innovative approaches that enhance collaboration and trust among stakeholders in industrial decision problems.
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