Jun Wang
Algorithm Developer at Applied Materials
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolJun Wang is an Algorithm Developer with 8 years of experience bridging optics, high-performance computing, and applied physics. With a PhD from Stanford and a background in physics from Peking University, he specializes in probing electron dynamics with attosecond light sources while writing high-performance code in Python, Julia, and MATLAB. Currently at Applied Materials after developing precision metrology diagnostics during an internship at KLA, he translates complex experimental problems into production-ready algorithms. Jun’s work sits at the intersection of cutting-edge ultrafast science and scalable computational methods, bringing lab-grade modeling into industrial tooling environments.
9 years of coding experience
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Peking UniversityDoctor of Philosophy - PhD, Applied Physics, Doctor of Philosophy - PhD, Applied Physics at Stanford University
Github Skills (17)
generative-ai9
generative9
modeling9
matrix8
pytorch7
quantum-computing6
algorithm6
quantum-algorithms6
core-library6
machine-learning5
computational-physics5
command-line4
python4
cpp4
transform2
Programming languages (5)
Github contributions (5)
congzlwag/scuff-em
Apr 2020 - Jul 2023
A comprehensive and full-featured computational physics suite for boundary-element analysis of electromagnetic scattering, fluctuation-induced phenomena (Casimir forces and radiative heat transfer), nanophotonics, RF device engineering, electrostatics, and more. Includes a core library with C++ and python APIs as well as many command-line applications.
Contributions:57 pushes, 1 branch in 3 years 3 months
command-linecomputational-physicscore-librarycpppython
congzlwag/spook
Dec 2021 - Nov 2022
Spooktroscopy package containing various versions of spooktroscopy classes
Contributions:15 releases, 1 review, 110 commits in 11 months
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