Changhong Mou
Physics and Astronomy · Purdue University West Lafayette
Publications
53
Citations
212
Est. group size
~2
Recurring co-author estimate
Active years
9
Publishing since 2018
Changhong Mou works on building efficient computer models for complex physical systems, especially fluid dynamics and climate-related processes like atmosphere-ocean-sea ice interactions. Much of the recent work combines physics knowledge with machine learning, developing neural network methods (such as neural operators and physics-informed neural networks) that can simulate or reduce the complexity of large-scale physical simulations. This blends applied mathematics, scientific computing, and machine learning to make climate and fluid dynamics simulations faster and more accurate.
Publication output has grown substantially over the last decade, rising from occasional papers before 2020 to a strong sustained pace in recent years, with a notable surge in 2026 output.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Morephy-Net: An Evolutionary Multi-objective Optimization for Replica-Exchange-based Physics-informed Neural Operator Learning Networks
SSRN Electronic Journal · 2026
- Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition
arXiv (Cornell University) · 2026
- Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition
arXiv (Cornell University) · 2026
- PIP<sup>2</sup> Net: Physics-informed partition penalty deep operator network
Electronic Research Archive · 2026
- Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey
UNC Libraries · 2026
- Data-driven correction reduced order models for the quasi-geostrophic equations: a numerical investigation
UNC Libraries · 2026
- AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training
arXiv (Cornell University) · 2026
- Muon-OGD: Muon-based Spectral Orthogonal Gradient Projection for LLM Continual Learning
arXiv (Cornell University) · 2026
- AdamFLIP: Adaptive Momentum Feedback Linearization Optimization for Hard Constrained PINN Training
arXiv (Cornell University) · 2026
- Muon-OGD: Muon-based Spectral Orthogonal Gradient Projection for LLM Continual Learning
arXiv (Cornell University) · 2026
- Physics-Aligned Canonical Equivariant Fourier Neural Operator under Symmetry-Induced Shifts
arXiv (Cornell University) · 2026
- Physics-Aligned Canonical Equivariant Fourier Neural Operator under Symmetry-Induced Shifts
arXiv (Cornell University) · 2026
- Morephy-Net: An evolutionary multi-objective optimization for replica-exchange-based physics-informed neural operator learning networks
Computer Methods in Applied Mechanics and Engineering · 2026
- ATLAS-NN: Adaptive Transfer Learnable Symplectic-aware Neural Network for Long-Time Hamiltonian Dynamics
arXiv (Cornell University) · 2026
- ATLAS-NN: Adaptive Transfer Learnable Symplectic-aware Neural Network for Long-Time Hamiltonian Dynamics
arXiv (Cornell University) · 2026
- arXiv (Cornell University)×24
- SSRN Electronic Journal×3
- Computer Methods in Applied Mechanics and Engineering×2
- Fluids×2
- Journal of Computational Physics×2
- Xihaier Luo
Physics and Astronomy · The Ohio State University
- Guang Lin
Physics and Astronomy · Purdue University West Lafayette
- Adithya Srinivasan
Physics and Astronomy · Purdue University West Lafayette
- Amirhossein Mollaali
Physics and Astronomy · Purdue University West Lafayette
- Christian Moya
Physics and Astronomy · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile