Rui Fang

Rui Fang

Visiting Assistant Professor at The Ohio State University, Ph.D. in Mathematics, University of Pittsburgh

Publications and Talks

Publications

  1. A. Çıbık, R. Fang, and W. Layton, “Modular data assimilation for flow prediction,” Numerical Methods for Partial Differential Equations, vol. 42, no. 1, e70066, 2026, https://doi.org/10.1002/num.70066.
  2. R. Fang, “Numerical analysis of penalty-based ensemble methods,” Numerical Algorithms, vol. 101, pp. 509–542, 2026, https://doi.org/10.1007/s11075-025-02014-y.
  3. A. Çıbık, R. Fang, W. Layton, and F. Siddiqua, “Data assimilation with model errors,” Computers & Mathematics with Applications, accepted, 2026, https://arxiv.org/abs/2504.16291.
  4. R. Fang, “Numerical analysis of locally adaptive penalty methods for the Navier–Stokes equations,” SeMA Journal, online first, 2025, https://doi.org/10.1007/s40324-025-00394-8.
  5. A. Çıbık, R. Fang, W. Layton, and F. Siddiqua, “Adaptive parameter selection in nudging-based data assimilation,” Computer Methods in Applied Mechanics and Engineering, vol. 433, Art. 117526, 2025, https://doi.org/10.1016/j.cma.2024.117526.
  6. R. Fang, W. Han, and W. Layton, “On a 1/2-equation model of turbulence,” International Journal of Numerical Analysis and Modeling, vol. 22, no. 2, pp. 139–156, 2025, https://doi.org/10.4208/ijnam2025-1007.
  7. W. Han, R. Fang, and W. Layton, “Numerical analysis of a 1/2-equation model of turbulence,” Physica D: Nonlinear Phenomena, vol. 471, Art. 134428, 2025, https://doi.org/10.1016/j.physd.2024.134428.
  8. R. Fang, “Penalty ensembles for Navier–Stokes equations with random initial conditions and forcing,” in Addressing Modern Challenges in the Mathematical, Statistical, and Computational Sciences, Springer Proc. Math. Stat., vol. 494, Springer, Cham, 2025, https://doi.org/10.1007/978-3-031-84869-8_38.
  9. R. Fang, H. Schreiner, M. Sokoloff, C. Weisser, and M. Williams, “A hybrid deep learning approach to vertexing,” Journal of Physics: Conference Series, vol. 1525, Art. 012079, 2020, https://doi.org/10.1088/1742-6596/1525/1/012079.
  10. (preprint) R. Fang and A. Pakzad, “Global recovery from local data: Interior nudging for 2D Navier–Stokes equations in a physical domain,” submitted, 2026, https://arxiv.org/abs/2601.11831.

Conference Talks

  1. Recent Advancements in Numerical Methods for Fluid Dynamics, Joint Mathematics Meetings (JMM), Washington, DC, 2026.
  2. The Ohio State University Computational Math Seminar, Columbus, OH, October 30, 2025,
  3. Frontiers in Applied Analysis, Carnegie Mellon University, Pittsburgh, PA, June 3-6, 2025.
  4. Recent Advancements in the Numerical Analysis of Nonlinear Partial Differential Equations, Joint Mathematics Meetings (JMM), Seattle, 2025.
  5. The 42nd Southeastern-Atlantic Regional Conference on Differential Equations (SEARCDE), West Virginia University, Morgantown, November 9-10, 2024.
  6. Mathematical Models and Numerical Methods for Multi-Physics Systems, Pittsburgh, PA, May 2024.
  7. Finite Element Circus, Brown University, Providence, RI, April 2024.
  8. Association for Women in Mathematics, University of Pittsburgh, Pittsburgh, PA, September 2023.
  9. The VI AMMCS (Applied Mathematics, Modeling and Computational Science) International Conference, Waterloo, ON, Aug 2023.