Zongren Zou

Zongren Zou is a Postdoctoral Scholar Research Associate at the California Institute of Technology, specializing in computational methods and machine learning applications in science and engineering. His work includes contributions to physics-informed neural networks (PINNs), uncertainty quantification (UQ), and scientific machine learning (SciML).

Key research areas include:

• Neural networks for solving Hamilton-Jacobi PDEs
• Multi-time uncertainty quantification in scientific computing
• Computational mathematics applications in engineering

He has developed open-source repositories such as NeuroSEM and MHPINN to advance methodologies in these domains.