Fengqi You is the Roxanne E. and Michael J. Zak Professor at Cornell University, and is affiliated with the Smith School of Chemical and Biomolecular Engineering and the graduate fields of Operations Research and Information Engineering, Electrical and Computer Engineering, Civil and Environmental Engineering, Mechanical Engineering, Center of Applied Mathematics, and Systems Engineering Program. He 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 120 peer-reviewed articles in leading journals, and has an h-index of 43. Some of his research results have been editorially highlighted in Nature, featured on journal covers (e.g. Energy & Environmental Science, ACS Sustainable Chemistry & Engineering, and Industrial & Engineering Chemistry Research), and covered by major media outlets (e.g. The New York Times, BBC, BusinessWeek, 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 Sustainable Engineering Research Excellence Award (2017), and ACS Sustainable Chemistry & Engineering Lectureship Award (2018), as well as a number of best paper awards and most-cited article recognitions. He is currently an Associate Editor of Computers & Chemical Engineering, a Consulting Editor of AIChE Journal, and an editorial board member of several leading journals (e.g. ACS Sustainable Chemistry & Engineering). His research focuses on the development of novel computational models, optimization algorithms, statistical machine learning methods, and systems analysis tools for smart manufacturing, energy systems, digital agriculture, and sustainability.
Our research focuses on the development of advanced computational models, optimization algorithms, statistical machine learning methods, and systems analysis tools for practically important and fundamental problems on process manufacturing, infrastructure, smart agriculture, 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 application level, we concentrate our efforts on process, energy, and environmental systems engineering. Particular research interests lie in (1) Sustainable design and synthesis of energy systems, including biofuels, photovoltaics, algae based biorefinery, carbon capture and separation, and shale gas, (2) Systems analysis, modeling and optimization for the food-energy-water-waste nexus, (3) Smart manufacturing, planning, scheduling and control of advanced manufacturing systems, (4) Life cycle sustainability assessment of nanotechnology and advanced materials, (5) Supply chain optimization and smart logistics, (6) Infrastructure design, planning and optimization, (7) Smart agriculture, smart water and smart energy, and (8) Industrial big data analytics and data-driven decision-making under uncertainty. At the fundamental level, we focus on the development of advanced mathematical, computing, and artificial intelligence technologies to support research in the aforementioned application areas.
Computational Optimization, Industrial Big Data Analytics and Machine Learning, Energy Systems Engineering, and Process Design
Fengqi You CV
- 2017. "Data-driven Adaptive Nested Robust Optimization: General Modeling Framework and Efficient Computational Algorithm for Decision Making Uncertainty." AIChe Journal 63: 3790-3817. .
- 2016. "Integrating Hybrid Life Cycle Assessment with Multiobjective Optimization: A Modeling Framework." Environmental Science & Technology 50: 1501-1509. .
- 2017. "Data-Driven Robust Optimization Based on Kernel Learning." Computers & Chemical Engineering 106: 464-479. .
- 2017. "Economic and Environmental Life Cycle Optimization Based on Noncooperative Supply Chains and Product Systems: Modeling Framework, Mixed-Integer Bilevel Fractional Programming Algorithm, and Shale Gas Application." ACS Sustainable Chemistry & Engineering 5: 3362-3381. .
- 2015. "Perovskite Photovoltaics: Life-Cycle Assessment of Energy and Environmental Impacts." Energy & Environmental Science 8: 1953-1968. .
Selected Awards and Honors
- 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
- BEng Tsinghua University, 2005
- Ph D Carnegie Mellon University, 2009