Joshua Vita
Postdoctoral Researcher at Lawrence Livermore National Laboratory
Tucson, Arizona, United States
Summary
👤
Senior🎓
Top SchoolJoshua Vita is a Sr. Computational Materials Scientist with nine years of experience building production-ready ML systems that accelerate scientific discovery, currently applying that expertise at Elemynt after a postdoc at Lawrence Livermore National Laboratory. He designs scalable training and inference pipelines for HPC environments, led multi-institution teams to deploy cluster-based Bayesian optimization and ensemble uncertainty frameworks that produced large accuracy and speed gains, and has deep experience integrating Python ML stacks with high-performance C++ simulation codes. Joshua has a strong track record building large scientific data infrastructure—e.g., ColabFit, which hosts billions of training points and tens of thousands of downloads—and routinely bridges research and engineering to deliver reproducible, deployable tools. Based in Tucson, AZ, he combines domain knowledge in materials science with practical software engineering and open collaboration to turn complex physical problems into robust, auditable ML workflows.
9 years of coding experience
3 years of employment as a software developer
The University of ArizonaUniversity of Illinois Urbana-Champaign
Github Skills (38)
simulation10
docking10
lammps9
javascript9
materials-informatics9
datasets9
open-source9
api8
specification8
rest7
rest-api7
react6
databases6
toolbox6
optimization5
Programming languages (5)
Github contributions (5)
TrinkleGroup/svreg
Sep 2020 - Jun 2021
A package for constructing interatomic potentials using symbolic regression with "structure vectors" (svreg = Structure Vector REGression).
Contributions:2 PRs, 174 pushes, 32 branches in 8 months
regressioninteratomic-potentialsvectorssymbolic-regressionmachine-learning
TrinkleGroup/s-meam
Apr 2018 - Nov 2020
Contributions:365 pushes, 57 branches, 2 issues in 2 years 7 months
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