Zongren Zou - Postdoctoral Scholar Research Associate

Zongren Zou

Postdoctoral Scholar Research Associate

Pasadena, California, United States

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Summary

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Senior

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Top School

Zongren Zou is a Postdoctoral Scholar Research Associate at Caltech with eight years of experience at the intersection of scientific computing, machine learning, and uncertainty quantification. He earned advanced degrees from Brown and Harvard and applies rigorous applied-math training to kernel methods and computational graph completion in physics-informed ML. At Brown he combined research and teaching roles, and as an open-source ML engineer contributed substantial TensorFlow backend enhancements to the widely used deepxde library—adding PDE loss support, inverse problem tooling, dropout, and forward-mode AD. Colleagues value his ability to translate theoretical methods into practical libraries and robust computational workflows that tackle real-world inverse and PDE-constrained problems.

8 years of coding experience

4 years of employment as a software developer

Doctor of Philosophy, Master of Science, Applied Mathematics, Doctor of Philosophy, Master of Science, Applied Mathematics at Brown University

Master of Science, Computational Science and Engineering, Master of Science, Computational Science and Engineering at Harvard University

Bachelor of Science, Theoretical and Applied Mechanics, 3.64/4.00, Bachelor of Science, Theoretical and Applied Mechanics, 3.64/4.00 at Peking University

Secondary School, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, Secondary School, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES at Capital Normal University High School

Github Skills (7)

neural-network10

deep-learning10

tensorflow10

scientific-machine-learning10

pde9

jax9

pytorch7

Programming languages (1)

Python

Github contributions (5)

lululxvi/deepxde

Jul 2021 - Jun 2022

A library for scientific machine learning and physics-informed learning

Role in this project:

ML Engineer

Contributions:15 reviews, 15 commits, 28 PRs in 11 months

Contributions summary:Zongren primarily focused on enhancing the TensorFlow backend of the deepxde library, adding support for key features like PDE loss calculation, inverse problems, and model prediction. The contributions extended to incorporate auxiliary variables, dropout regularization, and forward-mode automatic differentiation within the TensorFlow framework. These changes aimed to expand the library's functionality and improve its ability to handle various scientific machine learning tasks.

deeponetoperatorpaddlescientific-machine-learningtensorflow

Crunch-UQ4MI/neuraluq

Aug 2022 - Jan 2023

Contributions:24 commits, 17 PRs, 1 push in 5 months

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