Zukui Li

Zukui Li is a Professor in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering, where he leads a research group focused on mathematical optimization, machine learning, and process systems engineering. His work spans oil sands extraction, steel production, biomedical applications, and advanced optimization methods.

Education:

• Ph.D. in Chemical Engineering, Rutgers University (2010)
• M.Sc. in Control Theory and Control Engineering, University of Science and Technology of China (2005)
• B.Sc. in Automatic Control, University of Science and Technology of China (2002)

Postdoctoral Training: Princeton University (2010-2012)

Research Focus: Dr. Li's research integrates mathematical optimization and machine learning for complex process systems. His primary areas include:

• Advanced optimization techniques (robust, stochastic, and distributionally robust optimization)
• Machine learning applications in process monitoring and biomedical systems
• Industrial applications in energy, manufacturing, and resource extraction

Specific innovations include physics-informed ML for anemia treatment, adaptive optimization for steel production, and distributionally robust methods for uncertainty management.

Publication Trends (2019-2023): Recent articles demonstrate a strong focus on uncertainty-aware optimization methods, with increasing integration of machine learning techniques. Dominant themes include distributionally robust optimization, adaptive decision-making under uncertainty, neural network approximations for complex constraints, and applications in industrial process control and biomedical systems. Theoretical advancements are consistently coupled with practical implementations in energy and manufacturing sectors.

Research Group: Leads an active team developing optimization frameworks and machine learning solutions for process engineering challenges. Group website: Dr. Zukui Li's Research Group