I am an Assistant Professor in the School of Mathematical & Statistical Sciences at Clemson University (Subfaculty: Operations Research).
My research is in the intersection of optimization and economics, with a focus on energy markets and power systems. Classical economic equilibrium models often assume convexity and certainty, while in modern energy markets we need to consider nonconvex physical constraints and uncertainty of renewable production. One theme of my research is to develop market designs that address those issues with performance guarantees, leveraging duality theory and state-of-the-art conic programming methods. Additionally, power system optimization models are often large-scale and nonlinear, and as a result computationally difficult. Another theme of my research is to use decomposition and convex relaxation methods for mixed-integer nonlinear and robust optimization models, enabling more efficient computation of large-scale market optimization.
I obtained my Ph.D. in Industrial Engineering at University of Toronto in 2021, advised by Merve Bodur. I received M.S. in Operations Research from Columbia University in 2017, and my B.A. in Economics and B.S. in Mathematics from Wuhan University in 2015. I also visited Columbia University and worked on the DOE ARPA-E PERFORM project led by Daniel Bienstock. You can find my CV here.
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Note that I am not the only person called Cheng Guo at Clemson University. There is another Cheng Guo and he is a Ph.D. student in the School of Computing.
Application areas: Energy markets, Nonconvex market pricing, Capacity markets, Networked Cournot competition, Power systems optimization, Healthcare.
Methodologies: Copositive programming, Stochastic programming, Integer programming, Mixed-integer nonlinear programming, Decomposition methods.
INFORMS Annual Meeting, Atlanta, GA (October, 2025)
IEEE Power and Energy Society (PES) General Meeting, Austin, TX (July, 2025)
ICCOPT, Los Angeles, CA (July, 2025)