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jesse.chan@oden.utexas.edu
Office Location: POB 6.342
Jesse Chan
Associate Professor
Department Research Areas:
Computational Engineering
Education:
Ph.D., The University of Texas at Austin
Research Interests:
- Finite element and discontinuous Galerkin methods
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Structure-preserving discretizations
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Reduced order modeling
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Scientific computing
Jesse Chan received his Ph.D. in computational science, engineering, and mathematics (CSEM) from The University of Texas at Austin in 2013, working on high order adaptive finite element methods for steady compressible fluid flows. He served as a Pfieffer postdoctoral instructor at Rice University from 2013-2015 and as a postdoctoral researcher at Virginia Tech from 2015-2016, working on structure-preserving and low-complexity high order numerical methods for wave propagation in heterogeneous media. From 2016 to 2025, Chan served as faculty in the Department of Computational Applied Mathematics and Operations Research (previously Computational and Applied Mathematics) at Rice University.
In Fall 2025, Chan joined ASE/EM and the Oden Institute for Computational Engineering and Sciences as an associate professor. His recent research has focused on the accurate and efficient numerical solution of time-dependent hyperbolic partial differential equations, in particular the construction, analysis, and efficient implementation of structure-preserving discretizations for fluid dynamics, such as high order discontinuous Galerkin methods and reduced order models. This work has been supported by the National Science Foundation (NSF), including through a CAREER award.
Chan works in simulations of high-speed fluid flows over complex geometries, which are key steps in the evaluation and optimization of aerodynamic designs, such as aircraft and wind turbines. Similar computational models are used within computational weather and flood prediction models, as well as in the modeling and design of plasma and fusion.
