Rachel Smith
AI Specialist at Xanadu
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolRachel Smith is an AI specialist with a PhD in elementary particle physics from Stanford and nine years of experience applying machine learning to massive scientific datasets, most notably analyses of LHC data with the ATLAS detector. She developed differentiable vertex-fitting algorithms in PyTorch/JAX and built neural solutions for b-tagging and background modeling, translating domain physics into deployable ML components. Now at Xanadu in Palo Alto, she brings strong engineering chops in Python, PyTorch, JAX, and data tooling to bridge research-grade algorithms and production scientific computing. Rachel’s work uniquely blends rigorous statistical thinking from high-energy physics with practical differentiable programming techniques that accelerate detector-level inference.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Physics, 3.96/4.00, Bachelor of Science - BS, Physics, 3.96/4.00 at University of Illinois Urbana-ChampaignDoctor of Philosophy - PhD, Elementary Particle Physics, 4.00/4.00, Doctor of Philosophy - PhD, Elementary Particle Physics, 4.00/4.00 at Stanford University
English, Spanish, French
Github Skills (9)
state-space7
bayesian6
jax6
gpu6
jit5
backend5
tpu3
ssms2
inference2
Programming languages (2)
Github contributions (5)
lindermanlab/S5
Jul 2022 - Dec 2022
Contributions:2 reviews, 19 commits, 1 PR in 4 months
jimmysmith1919/RNNs
Jul 2019 - May 2020
Contributions:78 pushes in 9 months
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