Professor, Korea Advanced Institute of Science and Technology(KAIST). > Participating Panellists

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댓글 0건 조회 16회 작성일 20-02-03 16:50

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Jay H. Lee

Professor, Korea Advanced Institute of Science and Technology(KAIST).

Jay H. Lee is a professor of chemical & biomolecular engineering. His research includes state estimation, robust control, model predictive control, planning, and approximate dynamic programming with applications to energy and carbon management systems.


Jay H. Lee obtained his B.S. degree in Chemical Engineering from the University of Washington, Seattle, in 1986, and his Ph.D. degree in Chemical Engineering from California Institute of Technology, Pasadena, in 1991.  From 1991 to 1998, he was with the Department of Chemical Engineering at Auburn University, AL, as an Assistant Professor and an Associate Professor.  From 1998-2000, he was with School of Chemical Engineering at Purdue University, West Lafayette and then with the School of Chemical Engineering at Georgia Institute of Technology, Atlanta. In 2010, he joined Korea Advanced Institute of Science and Technology (KAIST) as the Head of the Chemical and Biomolecular Engineering Department. He recently served as the Associate Vice President of International Office and is currently serving the role of International Relations Advisor to the President. He is also the founding director of Saudi Aramco-KAIST CO2 Management Center. 
He was a recipient of the National Science Foundation’s Young Investigator Award in 1993 and also the AIChE CAST Computing in Chemical Engineering Award in 2013.  He was elected as an IEEE Fellow in 2011, an IFAC Fellow in 2011, and an AIChE Fellow in 2013. He is a member of both the Korean National Academy of Science and Technology (KAST) and the National Academy of Engineering Korea (NAEK)... He was also the 29th Roger Sargent Lecturer in 2016.  He published over 200 manuscripts in SCI journals with more than ~15000 Google Scholars citations (with h-index of 55)... His research interests are in the areas of state estimation, robust control, model predictive control, planning/scheduling, and approximate dynamic programming with applications to energy systems and carbon management systems.  

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