Scholar
Xinghao Dong
Google Scholar ID: xttYlC4AAAAJ
University of Wisconsin-Madison
Citations & Impact
Citations
13
H-index
2
i10-index
1
Publications
6
Co-authors
2
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator' accepted by Journal of Computational Physics; Presented work at DTE & AICOMAS 2025, AGU24, APS/DFD 2024, and selected for DFD-Interact which features top submissions.
Research Experience
- Spent a few months working on proving the Morrey’s Conjecture by providing several numerical examples at UCLA.
Education
- PhD Candidate, Computer Sciences, University of Wisconsin-Madison; Bachelor of Science, Applied Mathematics + Specialization in Computing, University of California, Los Angeles (UCLA).
Background
- Research Interests: Developing efficient data-driven models for complex systems that are multi-scale, multi-physics, and chaotic in nature. Current research focuses on stochastic modeling using advanced generative approaches, including diffusion models, flow matching, and their variants. Also interested in nonlocal modeling and continuous spatiotemporal representations.
