Welcome to my website
I’m Rui Fang, a Zassenhaus Assistant Professor in the Department of Mathematics at The Ohio State University (since Aug. 2025), where I work with Prof. Yulong Xing (webpage). I completed my Ph.D. in Mathematics at the University of Pittsburgh under the guidance of Prof. William Layton (webpage).
Download my CV · Google Scholar · ResearchGate · Email
I work in numerical analysis and scientific computing, focusing on data assimilation, fluid dynamics, turbulence, scientific machine learning, optimization, the Navier–Stokes equations, and other nonlinear, coupled partial differential equations. Grounded in rigorous mathematical analysis and motivated by challenges in computational science, I develop and analyze accurate and efficient numerical methods for these problems, including data-informed, finite element, discontinuous Galerkin, adaptive, and structure-preserving techniques. I emphasize long-time accuracy, imperfect models and data, and computational efficiency to enable large-scale fluid simulations.
Research Highlights
- Authored 12 peer-reviewed research papers: 9 published, 1 accepted for publication, and 2 under review. Of those, 3 solo-authored papers (Publications, Research Gate).
- 2 projects on data assimilation and 1 on structure-preserving using optimization will soon appear on arXiv.
- Delivered 11 conference talks in the United States and internationally.
- Upcoming: Joint Mathematics Meetings (JMM) in Chicago, January 12–15, 2027.
Research Interests: Numerical Analysis and Scientific Computing
Data Assimilation and Uncertainty Quantification
- Data assimilation and ensemble simulation
- Monte Carlo methods and model uncertainty
- Computational fluid dynamics and turbulence modeling
Numerical Methods for PDEs
- Finite element and discontinuous Galerkin methods
- Adaptive and penalty-based algorithms
- Structure-preserving and optimization-based methods
Scientific Machine Learning
- Data-driven numerical methods
- Learning-assisted scientific computing
- Deep learning for scientific applications
Fellowships, Awards, and Training
- Selected for the 2025 Argonne Training Program on Extreme-Scale Computing (ATPESC), funded by Argonne National Laboratory.
- 2025 Joint Mathematics Meetings Graduate Student Travel Grant from the American Mathematical Society ($1430).
- Awards: Andrew W. Mellon Predoctoral Fellow, University of Pittsburgh, 2023–2024.
- 2nd Place in 3-Minute Thesis competition, Math Department, University of Pittsburgh.
- Arts and Sciences Fellowships, University of Pittsburgh, Spring 2020.
Leadership and Service
- Association for Women in Mathematics, University of Pittsburgh, President, 2024-2025, Vice President, 2023–2024; Treasurer, 2022–2023
- Officer of Math Graduate Student Organization, University of Pittsburgh.
- Referee for the Pittsburgh Interdisciplinary Mathematics Review (Undergraduate student-run journal)
Refereeing Service
- Journal of Numerical Mathematics
- Numerical Algorithms
- International Journal of Numerical Analysis and Modeling
- Physics of Fluids
Education
Ph.D. in Mathematics, August 2019 -August 2025
University of Pittsburgh, PA, United States
Advisor: William J. Layton (wjl@pitt.edu)
Dual B.S. in Mathematics, September 2015 - August 2019
University of Cincinnati, OH, United States
Capital Normal University, Beijing, China
