Group Members and Alumni
Research group in applied and computational mathematics, with emphasis on finite element methods, porous media, data assimilation, optimal control, and scientific machine learning.
Postdoctoral Researchers
-
Dr. Kapil ChawlaResearch Associate supported by DOE Earthshot, 2025–2027Research topics: machine learning and multiscale methods
- Kapil Chawla, Youngjoon Hong, Jaeyong Lee, and Sanghyun Lee, Discontinuous Galerkin finite element operator network for solving non-smooth PDEs.
- Kapil Chawla, Sanghyun Lee, and Yeonjong Shin, A Parallel and Adaptive Mesh-Free Method for Heterogeneous Porous Media.
Graduate Students
-
Seungmin LeePh.D. student, 2023–present; supported by DOE EarthshotResearch topics: data assimilation, porous media flow, and Biot's equation
- Seungmin Lee and Sanghyun Lee, Convergence and Numerical Simulations of the Continuous Data Assimilation for Biot's Poroelasticity System, Computers and Mathematics with Applications, Volume 202, 15 January 2026, Pages 20–37.
-
Jonathan ValyouPh.D. student, 2023–present; co-advised with Hristo Chipilski, Department of Scientific Computing; supported by DOE EarthshotResearch topics: optimal control and data assimilation
- Jonathan Valyou, Jeremy Brandman, and Sanghyun Lee, Optimal mean-time path planning for unmanned underwater vehicles: a Hamilton-Jacobi approach.
- Sanghyun Lee, Zhengqi Liu, Jonathan Valyou, and Ludmil Zikatanov, A Conjugate Gradient Formulation of the EnKF Algorithm.
-
Latira CampbellPh.D. student, 2023–present; co-advised with Nicholas Dexter, Department of Scientific ComputingResearch topic: graph neural networks
Group Alumni
-
Dr. SeongHee JeongPostdoctoral Researcher, Department of Mathematics, 2023–2025Research topic: optimal control
- SeongHee Jeong and Sanghyun Lee, Optimal Control for Darcy's Flow in a Heterogeneous Porous Medium, Applied Numerical Mathematics, Volume 207, January 2025, Pages 303–322.
-
Yi-Yung YangPh.D. student, 2021–August 2026; supported by NSF DMS-2208402, NSF DMS-2327841, and DOE EarthshotResearch topics: enriched Galerkin methods and hyperbolic PDEs
- Dmitri Kuzmin, Sanghyun Lee, and Yi-Yung Yang, Bound-preserving and entropy stable enriched Galerkin methods for nonlinear hyperbolic equations, Journal of Computational Physics, Volume 541, 5 November 2025, 114323.
- Hyun-Geun Shin, Yi-Yung Yang, and Sanghyun Lee, A Posteriori Error Estimation for Parabolic Equations with Enriched Galerkin Finite Element Methods.
- Yi-Yung Yang, Sanghyun Lee, and Dmitri Kuzmin, Heat Transfer Modeling in Enhanced Geothermal Energy: A Three-Temperature Approach for Solid, Injected, and Residing Fluids.
-
Sanjeeb PoudelPh.D. student, 2022–August 2026; co-advised with Xiaoqiang Wang, Department of Scientific Computing; supported by DOE EarthshotResearch topics: data assimilation, enriched Galerkin methods, and machine learning
- Sanjeeb Poudel, Teeratorn Kadeethum, and Sanghyun Lee, Enhancing neural network extrapolation in thermo-fluid systems using steady-state solutions.
- Sanjeeb Poudel, Sanghyun Lee, and Lin Mu, Pressure-robust enriched Galerkin finite element methods for coupled Navier-Stokes and heat equations.
- Sanjeeb Poudel, Xiaoqiang Wang, and Sanghyun Lee, A novel technique for minimizing energy functional using neural networks, Engineering Applications of Artificial Intelligence, Volume 133, Part D, July 2024, 108313.
- Ryuou Hu, Sanjeeb Poudel, Feng Bao, and Sanghyun Lee, Ensemble Score Filter for Data Assimilation of Two-Phase Flow Models in Porous Media, Journal of Computational Physics, Volume 544, 1 January 2026, 114416.
-
Ruth LopezPh.D. student, 2022–April 2026; co-advised with Feng BaoResearch topics: ensemble score filter and data assimilation
-
Dabin ParkVisiting Ph.D. student, 2023–2024Research topic: machine learning and finite element methods for inverse elliptic PDEs
- Dabin Park, Sanghyun Lee, and Sunghwan Moon, A Machine Learning and Finite Element Framework for Inverse Elliptic PDEs via Dirichlet-to-Neumann Mapping, Journal of Computational and Applied Mathematics, Volume 486, November 2026, 117679.
Open Positions
Undergraduate Students
Undergraduate mathematics majors enrolled in the FSU mathematics program and interested in computational and numerical mathematics research are welcome to contact me about participating in current research projects.
Graduate Students
Graduate students already enrolled in an FSU graduate program, either master's or Ph.D., and interested in our research projects can contact me directly.