JONGHYUN “HARRY” LEE
 |
Jonghyun “Harry” Lee |
Research Interests
Scalable numerical modeling of subsurface flow and reactive transport in HPC
Fast inverse modeling and data assimiliation with uncertainty quantification
Stochastic optimization and optimal control
Physics-informed deep learning and big data analytics
Numerical linear algebra
Recent News
[04/22/2023] Our paper “Improved methodology for deep aquifer characterization using hydrogeological, self-potential, and magnetotellurics data” posted in arXiv
AAAI 2021 Fall Symposium on Science-guided AI (SGAI-AAAI-21)
PBBFMM3D: Parallel Black-Box Fast Multipole Method for Non-oscillatory Kernels for scalable O(N) matrix-vector multiplication
pyPCGA: Python package for Principal Component Geostatistical Approach released in public
Education
Ph.D. in Civil and Environmental Engineering, Stanford University, 2014
Advisor : Peter K. Kitanidis
M.S. in Civil and Environmental Engineering, Colorado State University, 2009
Advisor : Domenico Bau
B.S. in Civil, Urban and Geosystem Engineering, Seoul National University, 2007
Awards
Oak Ridge Institute for Science and Education (ORISE) Faculty Fellow, 2018-Current
Google Cloud Platform Research Credits, 2020-2023
Amazon Web Services Educate Credits for CEE696 Deep Learning in CEE and ES, 2019
Amazon Web Services Cloud Credits for Research Program, 2016-2018
Oak Ridge Institute for Science and Education (ORISE) Fellowship, 2016-2017
One of 15 early career researchers accepted for IdeaLab 2015: Inverse Problems and Uncertainty Quantification, Institute for Computational and Experimental Research in Mathematics, Brown University, Rhode Island, USA, July 6-10, 2015
Charles H. Leavell Graduate Student Fellowship, Stanford University, 2012-2014
Borland Hydrology New Graduate Student Scholarship, Colorado State University, 2008
Editorial Board
Associate Editor in Journal of Hydrology (Elsevier): 2018 - Present