Qi Zhang

Qi Zhang

Assistant Professor
Contact Information
Education
  • B.S., Mechanical Engineering, RWTH Aachen University, 2011
  • M.S., Chemical Engineering, Imperial College London, 2012
  • Ph.D., Chemical Engineering, Carnegie Mellon University, 2016

Research Areas

Recent News:

Research Interests

Our research in the area of process systems engineering lies at the intersection of chemical engineering and operations research. Leveraging the power of mathematical modeling and optimization, we develop enabling technologies that enhance decision making in complex engineering systems. In particular, our work focuses on solving problems of scientific and industrial interest in the following areas:

  • process modeling and optimization
  • design of integrated process and energy systems
  • planning and scheduling
  • network and supply chain optimization
Nonlinear process behavior, discrete decisions, large problem size, and uncertain information are only some of the factors that make these problems challenging. To obtain optimal solutions in light of such complexity, we strive to develop efficient computational methods and advance theory in:

  • mixed-integer linear/nonlinear programming
  • large-scale optimization
  • decision making under uncertainty

Awards

  • Mark Dennis Karl Teaching Assistant Award (2014, 2016)
  • Geoffrey Hewitt Prize (2012)
  • Dr. J├╝rgen Ulderup Fellowship (2011)
  • DAAD ISAP Fellowship (2009)

Selected Publications

  • Zhang, Q., Sundaramoorthy, A., Grossmann, I. E., & Pinto, J. M. (2017). Multiscale Production Routing in Multicommodity Supply Chains with Complex Production Facilities. Computers & Operations Research, 79, 207-222.
  • Zhang, Q. & Grossmann, I. E. (2016). Enterprise-wide Optimization for Industrial Demand Side Management: Fundamentals, Advances, and Perspectives. Chemical Engineering Research & Design, 116, 114-131.
  • Zhang, Q., Lima, R. M., & Grossmann, I. E. (2016). On the Relation Between Flexibility Analysis and Robust Optimization for Linear Systems. AIChE Journal, 62(9), 3109-3123.
  • Zhang, Q., Morari, M. F., Grossmann, I. E., Sundaramoorthy, A., & Pinto, J. M. (2016). An Adjustable Robust Optimization Approach to Scheduling of Continuous Industrial Processes Providing Interruptible Load. Computers & Chemical Engineering, 86, 106-119.
  • Zhang, Q., Grossmann, I. E., Sundaramoorthy, A., & Pinto, J. M. (2016). Data-driven Construction of Convex Region Surrogate Models. Optimization & Engineering, 17(2), 289-332.
  • Zhang, Q., Grossmann, I. E., Heuberger, C. F., Sundaramoorthy, A., & Pinto, J. M. (2015). Air Separation with Cryogenic Energy Storage: Optimal Scheduling Considering Electric Energy and Reserve Markets. AIChE Journal, 61(5), 1547-1558.
  • Zhang, Q., Shah, N., Wassick, J., Helling, R., & Van Egerschot, P. (2014). Sustainable Supply Chain Optimisation: An Industrial Case Study. Computers & Industrial Engineering, 74, 68-83.

Contact Information

Department of Chemical Engineering and Materials Science

421 Washington Ave. SE, Minneapolis, MN 55455-0132

P: 612-625-1313 | F: 612-626-7246

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