Fengqi You

Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering

Smith School of Chemical and Biomolecular Engineering

Biography

Fengqi You is the Roxanne E. and Michael J. Zak Professor at Cornell University, and he is affiliated with the Graduate Fields of Chemical Engineering, Electrical and Computer Engineering, Operations Research and Information Engineering, Systems Engineering, Mechanical Engineering, Civil and Environmental Engineering, and Applied Mathematics. He also serves as Chair of Ph.D. Studies in Cornell Systems Engineering, Associate Director of Cornell Energy Systems Institute, and Associate Director of Cornell Institute for Digital Agriculture. He was on the faculty of Northwestern University and worked at Argonne National Laboratory before joining Cornell in 2016. He has an h-index of 67 and published over 200 refereed articles in journals, such as Science, Nature Sustainability, Nature Communications, and Science Advances. Some of his research results have been editorially highlighted in Science and Nature, featured on journal covers (e.g., Energy & Environmental Science), and covered by major media outlets (e.g., The New York Times, BBC, Reuters, The Wall Street Journal, Daily Mail, Newsweek, BusinessWeek, New Scientist, and National Geographic). His recent awards include American Institute of Chemical Engineers (AIChE) W. David Smith, Jr. Publication Award (2011), Northwestern-Argonne Early Career Investigator Award (2013), National Science Foundation CAREER Award (2016), AIChE Environmental Division Early Career Award (2017), AIChE Research Excellence in Sustainable Engineering Award (2017), Computing and Systems Technology (CAST) Outstanding Young Researcher Award from AIChE (2018), Cornell Engineering Research Excellence Award (2018), ACS Sustainable Chemistry & Engineering Lectureship Award (2018), AIChE Excellence in Process Development Research Award (2019), AIChE Young Investigator Award for Innovations in Green Process Engineering (2020), Mr. & Mrs. Richard F. Tucker Excellence in Teaching Award (2020), Curtis W. McGraw Research Award from American Society for Engineering Education (ASEE) (2020), and American Automatic Control Council (AACC) O. Hugo Schuck Award (2020), AIChE Sustainable Engineering Forum Education Award (2021), as well as a number of best paper awards. He is an editor of Computers & Chemical Engineering, an associate editor of AAAS journal Science Advances and IEEE Transactions on Control Systems Technology, a consulting editor of AIChE Journal, a guest editor of Energy and Renewable & Sustainable Energy Reviews, and an editorial board member of ACS Sustainable Chemistry & Engineering, Industrial & Engineering Chemistry Research, PRX Energy, etc. His research focuses on novel computational models, optimization algorithms, statistical machine learning methods, and multi-scale systems analytics tools for smart manufacturing, digital agriculture, energy systems, and sustainability.

For more information about his research group: www.peese.org

Research Interests

We are an interdisciplinary systems engineering and artificial intelligence research group that focuses on the development of advanced computational models, optimization algorithms, statistical machine learning methods, and multi-scale systems analysis tools for smart manufacturing, digital agriculture, data analytics, energy systems, and sustainability. We seek to provide a balance between theory, computation and real-world applications through our synergistic research that includes both fundamentals and applications. At the fundamental level, we focus on the development of novel and advanced mathematical, computing, and artificial intelligence technologies. At the application level, we concentrate our efforts on process, energy, and environmental systems engineering. Particular research interests lie in (1) decarbonization, carbon-neutrality, and sustainable design of energy systems, including biofuels, photovoltaics, waste-to-energy, carbon capture and separation, shale gas, geothermal, and battery systems, (2) systems analysis, modeling and optimization for the food-energy-water-waste nexus and circular economy, (3) industrial ecology and life cycle sustainability assessment of nanotechnology and advanced materials, (4) material informatics and computer-aided molecular design, (5) supply chain optimization and smart logistics, smart manufacturing, planning, scheduling and control for complex engineering systems, (6) industrial big data analytics and machine learning for soft sensor and IoT, (7) grey-box digital twins and hybrid modeling based on mechanistic and data-driven approaches, and (8) quantum computing and quantum artificial intelligence.

Teaching Interests

Computational Optimization, Industrial Big Data Analytics and Machine Learning, Deep Learning, Quantum Computing and Artificial Intelligence, Life Cycle Assessment and Industrial Ecology, Energy Systems Engineering, and Process Design

Selected Publications

Shang, C., & You, F. (2021). A Posteriori Probabilistic Bounds of Convex Scenario Programs with Validation Tests. IEEE Transactions on Automatic Control, 66, 9, 4015-4028.
Ajagekar, A., & You, F. (2021). Quantum Computing based Hybrid Deep Learning for Fault Diagnosis in Electrical Power Systems. Applied Energy, 303, 117628.
Ning, C., & You, F. (2021). Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems. Automatica, 125, 109402.
Tian, X., Stranks, S.D., Fengqi You. 2020. “Life-cycle energy use and environmental implications of high-performance perovskite tandem solar cells.” Science Advances, 6, eabb0055.
Shang, C., Chen, W., Abraham Duncan Stroock, Fengqi You. 2020. “Robust Model Predictive Control of Irrigation Systems with Active Uncertainty Learning and Data Analytics.” IEEE Transactions on Control Systems Technology, 28, 1493-1504.
Zhao, S., Fengqi You. 2020. “Distributionally Robust Chance Constrained Programming with Generative Adversarial Networks (GANs).” AIChE Journal, 66, e16963.
Ajagekar, A., Humble, T., Fengqi You. 2020. “Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems.” Computers & Chemical Engineering, 132, 106630.

For a complete list of publications please visit: https://www.peese.org/publications/

Selected Awards and Honors

AIChE Sustainable Engineering Forum Education Award, 2021
Fellow of the Royal Society of Chemistry (FRSC), 2021
Mr. & Mrs. Richard F. Tucker Excellence in Teaching Award, 2020
American Automatic Control Council (AACC) O. Hugo Schuck Award, 2020
Curtis W. McGraw Research Award, ASEE, 2020
AIChE Program Committee’s Young Investigator Award for Innovations in Green Process Engineering, 2020
AIChE Excellence in Process Development Research Award, 2019
Cornell Engineering Research Excellence Award, 2018
Computing and Systems Technology (CAST) Outstanding Young Researcher Award of AIChE, 2018
ACS Sustainable Chemistry & Engineering Lectureship Award 2018
AIChE Sustainable Engineering Research Excellence Award 2017
AIChE Environmental Division Early Career Award 2017
National Science Foundation CAREER Award 2016
Northwestern-Argonne Early Career Investigator Award for Energy Research 2013

Education

B.Eng. Tsinghua University, 2005

Ph.D. Carnegie Mellon University, 2009