This is the 3rd major international award that Professor You has received recently, in addition to the 2017 AIChE Environmental Division Early Career Award and the 2017 AIChE Sustainable Engineering Research Excellence Award.Read more
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, the Operations Research and Information Engineering Field, Center of Applied Mathematics, and the Systems Engineering Program. He served 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 100 peer-reviewed articles in leading journals, and has an h-index of 40. 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). He received the 2011 W. David Smith, Jr. Publication Award from American Institute of Chemical Engineers (AIChE), the 2013 Northwestern-Argonne Early Career Investigator Award, an 2016 National Science Foundation CAREER Award, the 2017 AIChE Environmental Division Early Career Award, the 2017 AIChE Sustainable Engineering Research Excellence Award, and 2018 ACS Sustainable Chemistry & Engineering Lectureship Award, 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 advanced computational models, optimization algorithms, statistical machine learning methods, and systems analysis tools for process manufacturing, infrastructure, smart agriculture, energy systems, 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
Carnegie Mellon University 2009
In the News
The title of their poster presentation is “Handling Uncertain Feedstock Compositions in Shale Gas Processing Systems Design with Simulation-based Robust Optimization Algorithm.”Read more
This award is presented by AIChE to honor an individual with outstanding contributions in Environmental Chemical Engineering in the early stages of the career.Read more