Qi Zhang

Qi Zhang

Assistant Professor
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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. We focus on the systematic decision making and the discovery of decision-making mechanisms in complex process systems. To that end, we develop mathematical models and algorithms capable of considering both continuous and discrete decisions, incorporating uncertainty, capturing the interaction of multiple agents, and solving large-scale real-world optimization problems.

Our work is highly quantitative and interdisciplinary. We apply our tools to solve a wide range of problems of industrial and scientific relevance. In particular, we are interested in the design and operation of sustainable energy and process systems, advanced manufacturing, supply chain optimization, data analytics, and systems biology.

Awards

  • W. David Smith Jr. Graduate Publication Award (2019)
  • 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.

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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