Eric Qu

Research Intern at Lawrence Berkeley Labs

Berkeley, California, United States
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Summary

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Eric Qu is a second-year Computer Science PhD student at UC Berkeley (BAIR) and a research intern at NVIDIA with a focused trajectory in Geometric Deep Learning and AI for Science. He combines rigorous academic training—from a dual BS in Data Science at Duke/Duke Kunshan—to hands-on research stints at Meta FAIR and Microsoft Research Asia, applying mathematical principles to scale ML models for complex scientific problems. Advised by leaders like Aditi Krishnapriyan and collaborating with industry groups at FAIR and NVIDIA, he bridges foundational research with practical chemistry and physics-informed ML projects. With nine years of research experience and active roles across top labs, he brings both deep theoretical insight and experience deploying research within interdisciplinary scientific teams. An under-the-radar strength is his knack for translating mathematical ideas into scalable model architectures suited to real-world scientific datasets.
code9 years of coding experience
job5 years of employment as a software developer
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Berkeley
bookBachelor of Science - BS, Data Science, Bachelor of Science - BS, Data Science at Duke University
bookBachelor of Science - BS, Data Science, Bachelor of Science - BS, Data Science at Duke Kunshan University
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Stackoverflow

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Github Skills (21)

machine-learning9
utility9
swiftui8
python8
deep-learning8
menubar8
statusbar8
tensorflow7
convex-hull7
swift7
macos6
neural-network6
hackintosh6
opencore6
deep-neural-networks5

Programming languages (6)

C++SwiftASLJupyter NotebookPythonStylus

Github contributions (5)

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Contributions:11 commits, 11 pushes, 6 comments in 1 year 7 months
EricZQu/fairchem

Sep 2024 - Apr 2026

FAIR Chemistry's library of machine learning methods for chemistry
Contributions:35 pushes, 6 branches in 1 year 7 months
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