Kamil Khan

Dr. Kamil Khan is an Associate Professor of Chemical Engineering at McMaster University, part of the Faculty of Engineering. His research focuses on deterministic global optimization, nonsmooth optimization, and dynamic optimization of chemical process systems, integrating applied mathematics and algorithm development. He holds a B.S.E. from Princeton University, M.S. and Ph.D. from MIT, and completed a postdoc at Argonne National Laboratory.

He teaches CHEM ENG 4E03/6E03: Digital Computer Process Control, covering digital control systems and model predictive control. His lab, the Khan Research Group, explores topics like convex relaxations, automatic differentiation, and adjoint sensitivity analysis for process optimization.

Recent work includes advancements in computational methods for dynamic systems, membrane fouling prediction in water treatment plants, and subgradient evaluation for global optimization. His research bridges theoretical mathematics with practical engineering challenges.