Paper:2019 ACC Paper (Application): Data-Driven Adaptive Robust Optimization Framework for Unit Commitment under Renewable Energy Generation Uncertainty
Chao Ning received the B.Eng. degree in Automation from University of Electronic Science and Technology of China in 2012, and M.S. degree in Control Science and Engineering from Tsinghua University, China, in 2015. He is currently working toward the Ph.D. degree at Cornell University, USA. His research interests include data-driven optimization under uncertainty, learning for dynamics and control, big data analytics and machine learning, power systems operations, and renewable energy systems.
Fengqi You is the Roxanne E. and Michael J. Zak Professor at Cornell University (Ithaca, New York), and 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 Cornell Systems Engineering PhD Studies and Associate Director of Cornell Energy Systems Institute. He earned a B.Eng. from Tsinghua University and received his Ph.D. from Carnegie Mellon University. Fengqi was on the faculty of Northwestern University from 2011 to 2016, and worked at Argonne National Laboratory as an Argonne Scholar from 2009 to 2011. He has published more than 150 peer-reviewed journal articles, and has an h-index of 57. Some of his research results have been editorially highlighted in Science and Nature, featured on multiple journal covers, and reported by major media outlets (e.g. The New York Times, BBC, BusinessWeek, and National Geographic). His recent awards include an NSF CAREER Award, W. Curtis McGraw Research Award from ASEE, Cornell Engineering Research Excellence Award, and ACS Sustainable Chemistry & Engineering Lectureship Award, as well as W. David Smith, Jr. Publication Award, Sustainable Engineering Research Excellence Award, Environmental Division Early Career Award, Computing and Systems Technology (CAST) Outstanding Young Researcher Award, and Excellence in Process Development Research Award from AIChE. He is currently an Editor of Computers & Chemical Engineering, an Associate Editor of AAAS Journal Science Advances, a Consulting Editor of AIChE Journal, and an editorial board member of several other journals. 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.
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