Fengqi You is the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering at Cornell University, and he is affiliated with the Graduate Fields of Chemical Engineering, Computer Science, 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, Co-director of the Cornell University AI for Science Institute (CUAISci), Co-lead of Schmidt AI in Science Program at Cornell, Associate Director of Cornell Energy Systems Institute, and Co-Director of Cornell Institute for Digital Agriculture (CIDA). He was a faculty member at Northwestern University and worked at Argonne National Laboratory before joining Cornell in 2016. His research focuses on fundamental theory and methods in systems engineering and artificial intelligence, as well as their applications to materials informatics, smart manufacturing, quantum computing, energy systems, and sustainability. Fengqi has an h-index of 77 and published over 250 refereed articles in journals such as Science, Nature Sustainability, Nature Communications, Science Advances, and PNAS. Some of his research results have been editorially highlighted in Science and Nature, featured on dozens of 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, Fortune, Agence France-Presse, Newsweek, BusinessWeek, New Scientist, Popular Science, and National Geographic). He is an award-winning scholar and teacher, having received over 20 major national/international awards over the past six years from the American Institute of Chemical Engineers (AIChE), American Chemical Society (ACS), Royal Society of Chemistry (RSC), American Society for Engineering Education (ASEE), American Automatic Control Council (AACC), in addition to multiple best paper awards. Selected ones include NSF 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 Innovations in Green Process Engineering Award (2020), Mr. & Mrs. Richard F. Tucker Excellence in Teaching Award (2020), ASEE Curtis W. McGraw Research Award (2020), O. Hugo Schuck Award from AACC (2020), AIChE Sustainable Engineering Forum Education Award (2021), AIChE George Lappin Award (2022), and Stratis V. Sotirchos Lectureship Award by Foundation for Research & Technology – Hellas (FORTH) (2022). He is an elected Fellow of the Royal Society of Chemistry (FRSC), Fellow of the AIChE, and Fellow of the American Association for the Advancement of Science (AAAS). He serves as 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 subject editor of Advances in Applied Energy, a guest editor of Energy, Journal of Cleaner Production, and Renewable & Sustainable Energy Reviews, and an editorial board member of ACS Sustainable Chemistry & Engineering, Industrial & Engineering Chemistry Research, PRX Energy, etc.
His research group has around 20 Ph.D. students and postdoctoral fellows, in addition to dozens of master's students. For more information about his research group, please visit: www.peese.org
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.
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
For a complete list of publications please visit: https://www.peese.org/publications/
B.Eng. Tsinghua University, 2005
Ph.D. Carnegie Mellon University, 2009
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