Portrait of Sanghyun Lee

Sanghyun Lee, Ph.D.

Associate Professor, Department of Mathematics, Florida State University
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Contact

Appointments

  • Fall 2023 - Associate Professor, Department of Mathematics, Florida State University
  • Spring 2024 Associate of Data Science, Florida State University [link]
  • Spring 2018 Associate of Geophysical Fluid Dynamics Institute, Florida State University [link]
  • Fall 2017 Assistant Professor, Department of Mathematics, Florida State University

Useful Links

News

2025
Paper Our paper is now accepted for publication in Journal of Compuational Physics
The paper is co-authored with Yi-Yung Yang and Dmitri Kuzmin (TU Dortmnud), and it is titled Bound-preserving and entropy stable enriched Galerkin methods for nonlinear hyperbolic equations. The arXiv is provided in below link
arXiv
Presentation Lee presented a Talk at MoST 2025 - Moselle Vally, Germany
The list of the participants and the photo is here link
The title of my talk was Bound-preserving and entropy stable enriched Galerkin methods for nonlinear hyperbolic equations
Slides (PDF) Abstract
New Member Kapil Chawla joined our group at FSU
Kapil Chawla has his Ph.D from Indiana University (2025). His Ph.D advisor is R. Temam. Kapil is funded by the DOE Earthshot program and will be working on developing machine learning based multi scale methods. Welcome!

Funded Projects

Active
  • Department of Energy DOE Science Foundations for the Energy Earthshots 10/2023-09/2026
    DE-SC0024703
    Advanced Multi-Physics Machine Learning for Subsurface Energy Systems Across Scales
    PI: University of Texas at El Paso; Co-PIs: Florida State University, Sandia National Labs, University of Utah
    DOE site
  • National Science Foundation National Science Foundation DMS 09/2024 - 08/2027
    NSF #2349382
    REU Site: Applied Mathematics in Real World Problems
    Senior Personel: lead project Data Assimilation and Parameter Prediction Algorithms for Subsurface Flows and simplified models in Fluid Dynamics
    Link-Webpage, NSF Web
Completed
  • National Science Foundation National Science Foundation DMS 06/2024 - 05/2025
    Supplemental: Geothermal INTERN
    Dear Colleague Letter: Non-Academic Research Internships for Graduate Students in Geothermal Energy
    Seungmin Lee visited Lawrence Livermore National Lab (Dr. Joshua White)
    DOE article
  • National Science Foundation National Science Foundation DMS 06/2023-05/2024
    Supplemental: Geothermal INTERN
    Dear Colleague Letter: Non-Academic Research Internships for Graduate Students in Geothermal Energy
    Yi-Yung Yang; Sandia National Lab (Dr. Hongkyu Yoon)
    DOE article
  • National Science Foundation National Science Foundation DMS 06/2022-06/2025
    Collaborative Research: DMS-2208402
    Physics-Preserving Adaptive Finite Element Methods for Thermo-Poroelasticity
    PI: Sanghyun Lee (collaborate PI: Son-Young Yi; The University of Texas at El Paso)
    NSF link
  • National Science Foundation National Science Foundation DMS 08/2019-07/2022
    DMS-1913016
    Fluid-filled Fracture Propagation with a Phase-Field Approach in Subsurface by Employing Nonlinear Strain-Limiting Models and Enriched Galerkin Methods
    PI: Sanghyun Lee
    NSF link
  • Florida State University Multidisciplinary Support 2020-2021
    MDS: #045490
    Studies for Degradation of Lignin-based Biodegradable Plastics to Prevent Marine Debris
    CRC link
  • Florida State University First Year Assistant Program (FYAP) 05/2018 - 08/2018
    CRC: 041950
    Optimal Error Estimate of Flow Problems with Dirac Sources in Subsurface for Discontinuous and Enriched Galerkin Methods




Upcoming Workshops/Conferences/Talks/Events

Upcoming
2025
Earlier (2024)
  • 12-16 Feb 2024
    ICERM: Numerical Analysis of Multiphysics Problems
    Brown University, Providence, link
  • 21 Mar 2024
    Affiliates Meeting
    The Center for Subsurface Modeling, UT Austin
  • 23-24 Mar 2024
    AMS Spring Southeastern Sectional Meeting
    Florida State University, link - FSU news
  • 5-7 Apr 2024
    Southeast Applied & Computational Math Student Workshop
    Georgia Institute of Technology, link
  • 20-21 Apr 2024
    The Eleventh Graduate Student Conference
    Clemson
  • 12 Apr 2024
    Machine Learning Seminar
    Department of Mathematics, Florida State University
  • May 2024
    Visiting
    Leibniz University Hannover, Germany
  • 14 May 2024
    Seminar
    Dortmund, Germany
  • 15 May 2024
    Seminar, Institut fur Baumechanik und Numerische Mechanik (IBNM)
    Leibniz University Hannover, Germany
  • 16 May 2024
    Seminar, Institute of Applied Mathematics
    Leibniz University Hannover, Germany
  • 8-12 Jul 2024
    SIAM Annual Meeting
    Spokane, Washington, link
  • 15-16 Jul 2024
    NSF PI Meeting
    Seattle, Washington
  • 21-26 Jul 2024
    WCCM & PACAM
    Vancouver, BC, Canada, link
  • 11-16 Aug 2024
    11th deal.II Workshop
    Colorado State University, Fort Collins, Colorado (link)
  • 19 Sep 2024
    Yonsei University
    Seoul, South Korea
  • 26-27 Sep 2024
    Kyungpook National University
    Daegu, South Korea
  • 11-13 Oct 2024
    SIAM Texas-Louisiana Section, 7th Annual Meeting
    Baylor University, link
  • 21-25 Oct 2024
    SIAM Conference on Mathematics of Data Science (MDS24)
    Atlanta, U.S.A, link
  • 14 Nov - 3 Dec 2024
    Technical University of Dortmund
    Germany




Research Team

Research Interests

  • Design, analysis, and implementation of numerical methods for partial differential equations.
  • Computational mathematics with high-performance computing for interdisciplinary multi-physics and multi-scale real-world problems. In particular, focus on subsurface applications.
  • Free-boundary multiphase problems using projection methods for Navier-Stokes and level set methods with adaptive finite elements. Video
  • Analysis and computation of physics preserving (local mass conservation, locking free, maximum principle, and so on) enriched Galerkin methods for coupling flow and transport in porous media.
  • Multi physical and multi scale problems in porous pedia, including fracture systems; phase-field fracture with Biot thermo-hydro-mechanic-chemical coupling.
  • Employing machine learning / deep learning / neural networks for solving inverse problems, and data assimilation problems based on physical partial differential equations.