Welcome to my website

I’m Rui Fang, a Ph.D. candidate in Mathematics at the University of Pittsburgh, working under the guidance of Prof. William Layton (webpage) in the numerical analysis group. I develop accurate and efficient numerical algorithms to extend the predictability horizon for the simulation of turbulent flows by addressing data uncertainty and the chaotic behavior of flows. Advancements in these methods are essential for studying climate patterns, energy production, and global warming.

My research interests include data assimilation, machine learning, deep learning, probabilistic graphical models, deep reinforcement learning, numerical analysis, scientific computing, computational fluid dynamics, finite element methods, ensemble simulations, and turbulence modeling.

Summary (Download my CV)

• Improved fluid flow simulation predictability, accuracy, and efficiency by addressing data uncertainty and flows’ chaotic behavior.
• Authored 7 peer-reviewed publications including 3 solo, with 2 are currently under review (Publications, Research Gate). One project on data assimilation will soon appear on arXiv.
• Delivered 4 conference talks in the United States and internationally.
• Awards: Andrew W. Mellon Fellow 2023-2024.
• 2nd Place in 3-Minute Thesis competition, Math Department, University of Pittsburgh.
• President of AWM (Association for Women in Mathematics), Officer of Math GSO (Graduate Student Organization).
• Referee for the Pittsburgh Interdisciplinary Mathematics Review (PIMR), a peer-reviewed open-access journal.