Research¶

Research Experience¶

Research Intern, Georgia Institute of Technology
Supervisor: Prof. Qi Tang, 2025.12-2026.04

• Collaborated weekly on structure-preserving operator learning for problems in plasma and fusion modeling.
• Designed a solution embedding a semi-Lagrangian discretization into a Fourier Neural Operator to bridge advection and diffusion-dominated regimes.
• Developed and validated a single model for both sharp shock structures and smooth convection-diffusion behavior.

Research Intern, Southern University of Science and Technology
Supervisor: Prof. Kailiang Wu, 2025.07-2025.08

• Translated an operator-splitting and machine-learning correction framework into a computational model for model-reality gaps.
• Studied stability and approximation properties of the proposed operator-learning framework.
• Implemented and benchmarked the framework on Navier-Stokes, FitzHugh-Nagumo, and one-dimensional compressible Euler systems.

Research Projects¶

Zhejiang Province SRTP Project: Application and Optimization of Classical Computational Methods and Machine Learning Techniques in Flow Field Simulation
Supervisor: Prof. Heyu Wang, 2024.03-2025.05

• Worked with a finite-element program for solving the Navier-Stokes equations and gained hands-on experience in computational fluid dynamics.
• Explored the integration of classical computational methods with machine learning to improve simulation accuracy and reduce computational cost.
• Investigated optimization techniques and loss functions for Physics-Informed Neural Network models.