Chi-Guhn Lee, PhD, P.Eng.

Professor, Industrial Engineering
Associate Chair of Graduate Studies

Research: Various logistics problems; sequential decision making theories; financial theories applied in manufacturing and service sectors; market-driven conflict resolution; optimal pricing; marketing; information system control and design.

Laboratory: Dynamic Optimization & Operations Management Laboratory

Email: cglee@mie.utoronto.ca | Tel: 416-946-7867 | Office: MC322

Research Areas

  1. Operations Research


Chi-Guhn Lee is a professor in the Department of Mechanical and Industrial Engineering at the University of Toronto. He received his Ph.D. in the area of Industrial & Operations Engineering from the University of Michigan, Ann Arbor, and joined the University of Toronto faculty in 2001. Prior to his Ph.D. studies, he spent over three years at Samsung SDS in Seoul, Korea, leading a project of re-usable OOP library for fast prototyping of system integration software. Professor Lee has done both theoretical and applied research in dynamic optimization under uncertainty. His theoretical works involve accelerated value iteration algorithm for Markov decision processes, progressive basis-function approximation for value function space, multi-variate Bayesian control chart optimization, and optimal learning using Multi-armed Bandit Model. His interest in application is diverse from supply chain optimization to financial engineering, to dynamic pricing and to healthcare optimization. In the past years, he and his team have actively adopted machine learning algorithms into their research portfolio. In particular, he is currently active in reinforcement learning, inverse reinforcement learning, and deep reinforcement learning.

Professor Lee holds positions as associate editor - Enterprise Information System and International Journal of Industrial Engineering - and serves as a member in a few editorial boards.
Xinyu Liu, PhD, P.Eng.

Associate Professor, Mechanical Engineering

Research: Microfluidics and lab-on-a-chip technologies; micro and nano biosensors; bioMEMS; robotics and automation at the micro and nanoscales; point-of-care diagnostics; environmental pollution testing; C. elegans biology; and large-scale gene screening.

Email: xyliu@mie.utoronto.ca | Tel: 416-946-0558 | Office: MC312

Research Areas

  1. Biomedical Engineering
  2. Robotics, Mechatronics and Instrumentation
  3. Thermal and Fluid Sciences Engineering


Xinyu Liu is an Associate Professor in the Department of Mechanical and Industrial Engineering. Prior to joining the University of Toronto, he was an Associate Professor and the Canada Research Chair in Microfluidics and BioMEMS (tier II) in the Department of Mechanical Engineering at McGill University. He obtained his B.Eng. and M.Eng. from Harbin Institute of Technology in 2002 and 2004, respectively, and his Ph.D. from the University of Toronto in 2009, all in Mechanical Engineering. He then completed an NSERC Postdoctoral Fellowship in the Department of Chemistry and Chemical Biology at Harvard University in 2009–2011.

Xinyu’s research interests are at the interfaces of microfluidics, bioMEMS (bio-microelectromechanical systems), and robotics. His research group is developing integrated micro/nanodevices and systems to target a variety of exciting applications in biology, medicine, and environment. Applications of their recent technologies include point-of-care diagnostics, large-scale gene screening, neural basis of behaviour, high-throughput drug screening, and environmental pollution monitoring.

He received the 2012 Rising Star in Global Health Award from Grand Challenge Canada, the 2012 Douglas R. Colton Metal for Research Excellence from CMC Microsystems, the 2013 Award of Excellence for Basic Science Research from the McGill Surgery Department, the 2017 Christophe Pierre Award for Research Excellence (Early Career) from McGill Faculty of Engineering, and seven Best Paper Awards at major engineering and biomedical conferences.

Xinyu is an Associate Editor of IEEE Transactions on Automation Science and Engineering, IEEE Robotics & Automation Letters, and the International Journal of Advanced Robotic Systems. He also served on editorial boards of the three major international conferences (ICRA, IROS, and CASE) of the IEEE Robotics and Automation Society (RAS), and serves on the Steering Committee of the International Conference on Manipulation, Automation and Robotics at the Small Scales (MARSS).