Nathan Zhao
Staff ML Scientist at XPENG
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolNathan Zhao is a staff ML scientist with 11 years of experience combining applied physics, numerical methods, and machine learning to solve real-world autonomy and robotics problems. With a PhD in applied physics from Stanford, he has built ML-driven motion prediction and collision risk systems for self-driving vehicles and now leads generative AI efforts for humanoid robotics at XPENG. His expertise spans linear algebra/PDE solvers, electrodynamics simulations, and scalable neural-network pipelines for AR/VR and perception stacks, reflecting a rare blend of theoretical and production-focused skills. Nathan has a strong track record of industry research at Cruise and Facebook Reality Labs and early-stage quantitative work at Akuna, plus hands-on experimental physics experience from Columbia, MIT, and Caltech. He is an active open-source practitioner—his GitHub collects numerical and ML projects that bridge simulation, optimization, and applied engineering.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (B.A.) Physics/Mathematics, Bachelor of Arts (B.A.) Physics/Mathematics at Columbia UniversityDoctor of Philosophy (PhD) Applied physics, Doctor of Philosophy (PhD) Applied physics at Stanford University
English
Github Skills (48)
fenics10
algorithms10
scipy10
spin10
python10
wave10
maxwell10
scientific-computing10
chemical-engineering9
matrix9
photonics9
expansion9
julia9
numba8
segmentation8
Programming languages (4)
Github contributions (5)
zhaonat/FDFD_modules
Aug 2018 - May 2019
personal set of FDFD codes used for my research. Much of this has been inspired by Yu (Jerry) Shi and Wonseok Shin
Contributions:61 commits, 2 PRs, 50 pushes in 8 months
fdfd
zhaonat/orbital_dynamics
Mar 2018 - Apr 2018
Contributions:28 commits, 25 pushes, 1 branch in 27 days
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