معرفی
Jesse Chan is an Associate Professor in the Department of Computational Applied Mathematics and Operations Research at Rice University. He earned his Ph.D. from the University of Texas at Austin and a bachelor's degree from Rice University. His research focuses on high-order numerical methods for partial differential equations, including discontinuous Galerkin (DG) methods, entropy stability, and efficient implementations on modern architectures. He has received the NSF CAREER Award (2020) and leads the development of open-source software like Trixi.jl and StartUpDG.jl.
Education:
- Ph.D., Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin (2013)
- B.A., Computational and Applied Mathematics, Rice University (2008)
Research Interests:
- Numerical Methods for PDEs
- High-Order Finite Element and DG Methods
- Entropy Stability and Conservation Laws
- Scientific Computing and HPC
- Wave Propagation and Fluid Dynamics
Recent Work Trends: His publications emphasize robust entropy-stable schemes, cut-cell methods, and reduced-order modeling for nonlinear conservation laws, with applications to fluid dynamics and wave propagation. He also explores GPU acceleration for DG methods.
Awards:
- NSF CAREER Award (2020)
Advising & Grants:
- Advised students Brian Christner and Raymond Park (recent MA theses)
- Funded by NSF grants DMS-CAREER-1943186 and DMS-2231482
Labs/Teams: Active contributor to the Trixi.jl framework and collaborator on open-source DG tools like StartUpDG.jl.
