| Large‐scale hydraulic tomography and joint inversion of head and tracer data using the principal component geostatistical approach (PCGA) J Lee, PK Kitanidis Water Resources Research 50 (7), 5410-5427, 2014 | 108 | 2014 |
| Principal component geostatistical approach for large‐dimensional inverse problems PK Kitanidis, J Lee Water resources research 50 (7), 5428-5443, 2014 | 85 | 2014 |
| Predictor selection for downscaling GCM data with LASSO D Hammami, TS Lee, TBMJ Ouarda, J Lee Journal of Geophysical Research: Atmospheres 117 (D17), 2012 | 71 | 2012 |
| Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen–Loève expansion AK Saibaba, J Lee, PK Kitanidis Numerical Linear Algebra with Applications 23 (2), 314-339, 2016 | 61 | 2016 |
| Imaging geochemical heterogeneities using inverse reactive transport modeling: An example relevant for characterizing arsenic mobilization and distribution S Fakhreddine, J Lee, PK Kitanidis, S Fendorf, M Rolle Advances in Water Resources 88, 186-197, 2016 | 52 | 2016 |
| A learning-based data-driven forecast approach for predicting future reservoir performance H Jeong, AY Sun, J Lee, B Min Advances in Water Resources 118, 95-109, 2018 | 50 | 2018 |
| A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks T Kadeethum, D O’Malley, JN Fuhg, Y Choi, J Lee, HS Viswanathan, ... Nature Computational Science 1 (12), 819-829, 2021 | 48 | 2021 |
| Bayesian inversion with total variation prior for discrete geologic structure identification J Lee, PK Kitanidis Water Resources Research 49 (11), 7658-7669, 2013 | 44 | 2013 |
| Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging J Lee, H Yoon, PK Kitanidis, CJ Werth, AJ Valocchi Water Resources Research 52 (7), 5213-5231, 2016 | 42 | 2016 |
| Improved characterization of heterogeneous permeability in saline aquifers from transient pressure data during freshwater injection PK Kang, J Lee, X Fu, S Lee, PK Kitanidis, R Juanes Water Resources Research 53 (5), 4444-4458, 2017 | 33 | 2017 |
| Reactive fronts in chemically heterogeneous porous media: experimental and modeling investigation of pyrite oxidation M Battistel, M Muniruzzaman, F Onses, J Lee, M Rolle Applied Geochemistry 100, 77-89, 2019 | 32 | 2019 |
| Microfluidic Investigation of Salinity-Induced Oil Recovery in Porous Media during Chemical Flooding S Park, J Lee, H Yoon, S Shin Energy & Fuels 35 (6), 4885-4892, 2021 | 31 | 2021 |
| Value of information as a context-specific measure of uncertainty in groundwater remediation X Liu, J Lee, PK Kitanidis, J Parker, U Kim Water Resources Management 26, 1513-1535, 2012 | 30 | 2012 |
| Recent developments in fast and scalable inverse modeling and data assimilation methods in hydrology H Ghorbanidehno, A Kokkinaki, J Lee, E Darve Journal of Hydrology 591, 125266, 2020 | 27 | 2020 |
| Integration of artificial recharge and recovery systems for impaired water sources in urban settings: Overcoming current limitations and engineering challenges J Regnery, J Lee, P Kitanidis, T Illangasekare, JO Sharp, JE Drewes Environmental Engineering Science 30 (8), 409-420, 2013 | 24 | 2013 |
| Improved characterization of DNAPL source zones via sequential hydrogeophysical inversion of hydraulic‐head, self‐potential and partitioning‐tracer data X Kang, A Kokkinaki, PK Kitanidis, X Shi, A Revil, J Lee, A Soueid Ahmed, ... Water Resources Research 56 (8), e2020WR027627, 2020 | 22 | 2020 |
| PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication R Wang, C Chen, J Lee, E Darve Journal of Parallel and Distributed Computing 154, 64-73, 2021 | 21* | 2021 |
| Hydrogeophysical Characterization of Nonstationary DNAPL Source Zones by Integrating a Convolutional Variational Autoencoder and Ensemble Smoother X Kang, A Kokkinaki, PK Kitanidis, X Shi, J Lee, S Mo, J Wu Water Resources Research 57 (2), e2020WR028538, 2021 | 18 | 2021 |
| Longitudinal dispersion coefficients for numerical modeling of groundwater solute transport in heterogeneous formations J Lee, M Rolle, PK Kitanidis Journal of contaminant hydrology 212, 41-54, 2018 | 18 | 2018 |
| Application of deep learning to large scale riverine flow velocity estimation M Forghani, Y Qian, J Lee, MW Farthing, T Hesser, PK Kitanidis, EF Darve Stochastic Environmental Research and Risk Assessment 35, 1069-1088, 2021 | 16 | 2021 |
Peter K. KitanidisProfessor, Stanford UniversityVerified email at stanford.edu
