He Jia - Graduate Research Fellow

He Jia

Graduate Research Fellow

New Jersey, United States

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Summary

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Senior

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Top School

He Jia is a Princeton PhD candidate and Graduate Research Fellow who blends quantitative portfolio management with astrophysics research on black holes, bringing eight years of scientific and engineering experience. He has a strong open-source footprint in numerical and probabilistic computing—contributing to flagship projects like NumPy, SciPy, and TensorFlow Probability by implementing and testing core statistical functions and improving linear algebra routines. Comfortable across ML frameworks (JAX) and scientific Python, he translates theoretical models into robust, tested code used by broad communities. His background includes visiting research roles at UC Berkeley and a BS in Physics from Peking University, reflecting a trajectory that spans fundamental science and production-grade software. An uncommon asset: he actively bridges high-energy astrophysics and practical quantitative tooling, making complex probabilistic methods accessible and performant.

8 years of coding experience

1 year of employment as a software developer

Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Peking University

High School Diploma, General, High School Diploma, General at Shenzhen Middle School

Doctor of Philosophy - PhD, Astrophysical Sciences, Doctor of Philosophy - PhD, Astrophysical Sciences at Princeton University

Github Skills (20)

algorithms10

scipy10

probabilistic-programming10

python10

statistics10

machine-learning10

numpy10

tensorflow10

statistical-models10

jax10

linear-algebra10

scientific-computing10

data-science9

pytest9

documentation9

Programming languages (9)

TypeScriptShellC++CJavaScriptJupyter NotebookCythonPython

Github contributions (5)

jax-ml/jax

Jan 2019 - Oct 2022

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Role in this project:

ML Engineer

Contributions:3 PRs, 7 comments, 4 issues in 3 years 9 months

Contributions summary:He primarily contributed to the implementation of statistical functions within the JAX ecosystem. Their work involved adding PDF calculations for various probability distributions from SciPy, including norm, beta, expon, gamma, and uniform. They also implemented the multivariate_normal logpdf and pdf functions. Furthermore, the user added testing functions for these newly implemented statistics functions.

gpujittpujax

scipy/scipy

Mar 2019 - Aug 2022

SciPy library main repository

Role in this project:

Data Scientist

Contributions:7 commits, 4 PRs, 22 comments in 3 years 6 months

Contributions summary:He primarily contributed to the `scipy/scipy` repository by modifying and extending the `stats` module, specifically the `gaussian_kde` class. Their work involved bug fixes, code optimization, and the addition of a new method to calculate and return marginal distributions. Furthermore, the user's commits include updates to the test suite demonstrating their focus on ensuring the accuracy and reliability of the statistical functionalities within the library. They also addressed issues related to PPoly and example code.

scipypythonscientific-computing

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