| Coarse-scale PDEs from fine-scale observations via machine learning S Lee, M Kooshkbaghi, K Spiliotis, CI Siettos, IG Kevrekidis Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (013141), 2020 | 68 | 2020 |
| Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion S Lee, F Dietrich, GE Karniadakis, IG Kevrekidis Interface focus 9 (3), 20180083, 2019 | 36 | 2019 |
| Some manifold learning considerations toward explicit model predictive control RJ Lovelett, F Dietrich, S Lee, IG Kevrekidis AIChE Journal 66 (5), e16881, 2020 | 15 | 2020 |
| A general CFD framework for fault-resilient simulations based on multi-resolution information fusion S Lee, I Kevrekidis, G, G Karniadakis, E Journal of Computational Physics 347, 290-304, 2017 | 13 | 2017 |
| A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion S Lee, I Kevrekidis, G, G Karniadakis, E journal of computational physics 344, 516-533, 2017 | 11 | 2017 |
| Numerical simulation of atomic layer deposition for thin deposit formation in a mesoporous substrate L Zhuang, P Corkery, DT Lee, S Lee, M Kooshkbaghi, Z Xu, G Dai, ... AIChE Journal 67 (8), e17305, 2021 | 8 | 2021 |
| Learning black-and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data S Lee, YM Psarellis, CI Siettos, IG Kevrekidis Journal of Mathematical Biology 87 (1), 15, 2023 | 4 | 2023 |
| Data-driven blended equations of state for condensed-phase explosives K Lee, AM Hernández, DS Stewart, S Lee Combustion Theory and Modelling 25 (3), 413-435, 2021 | 4 | 2021 |
| Data-driven discovery of chemotactic migration of bacteria via machine learning YM Psarellis, S Lee, T Bhattacharjee, SS Datta, JM Bello-Rivas, ... arXiv preprint arXiv:2208.11853, 2022 | 3 | 2022 |
| Resilient algorithms for reconstructing and simulating gappy flow fields in CFD S Lee, IG Kevrekidis, GE Karniadakis Fluid Dynamics Research 47 (5), 051402, 2015 | 3 | 2015 |
| Prediction of dislocation-grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods JD Gravell, J Cho, S Lee, S Aubry, I Ryu Materialia 31, 101874, 2023 | | 2023 |
| A physics-informed machine learning model for go/no-go criteria on reactive metamaterials. S Lee, K Lee, A Hernández, D Stewart Bulletin of the American Physical Society 67, 2022 | | 2022 |
Ioannis KevrekidisJohns Hopkins UniversityVerified email at jhu.edu
