Navneeth Gokul
Software Research Engineer Scientist at Intel Corporation
Hillsboro, Oregon, United States
Summary
👤
Senior🎓
Top SchoolNavneeth Gokul is a Software Research Engineer and Scientist with nine years of experience building production-grade machine learning and computational geometry systems, currently at Intel's Computational and Modeling Technology group in Hillsboro. He combines C++ and Python expertise with optimization and ML to compress and model billions of convex polygons for semiconductor photomasks, achieving over 50% file-size reduction and 60% runtime improvements through algorithmic reformulation and custom regularization. His background spans academic research—from DFT and Monte Carlo simulations to RNNs and AlphaFold2—bringing a rare blend of physics-informed modeling and modern deep learning. He has a strong track record of turning research prototypes into CI/CD-backed production features, authoring test suites that caught critical logic bugs and earning multiple department awards. Notably, he applied explainable-AI techniques (Shapley values) to molecular models and introduced neural approximations to reduce cost in high-order virial coefficient calculations, demonstrating a knack for creative, cross-disciplinary solutions. Based in the Portland area, he pairs a PhD in Chemical Engineering with hands-on software craftsmanship to solve high-stakes problems in semiconductor and molecular modeling.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Technology - BTech, Chemical Engineering, 8.24/10.00, Bachelor of Technology - BTech, Chemical Engineering, 8.24/10.00 at Vishwakarma Institute Of TechnologyDoctor of Philosophy - PhD, Chemical Engineering, 3.55/4.00, Doctor of Philosophy - PhD, Chemical Engineering, 3.55/4.00 at University at BuffaloMaster of Science - MS, Chemical Engineering, 3.62/4.00, Master of Science - MS, Chemical Engineering, 3.62/4.00 at University of Florida
English, Hindi
Github Skills (20)
genetics10
predict9
molecular-simulation9
simulation9
molecule9
simulation-framework9
proteins9
systems-biology9
java8
materials-informatics7
rdkit6
drug-discovery6
benchmark3
evaluation3
machine-learning2
Programming languages (3)
Github contributions (5)
ur-whitelab/nlcc-data
Sep 2021 - Sep 2021
Benchmark dataset and evaluation for large language models that generate code
Contributions:19 reviews, 8 PRs, 8 pushes in 19 days
large-language-modelsdeep-learningdatasetevaluationmachine-learning
etomica/etomica
Oct 2016 - Aug 2020
Etomica is a molecular simulation framework written in Java, developed at the Department of Chemical & Biological Engineering at the University at Buffalo.
Contributions:101 commits, 12 PRs, 36 pushes in 3 years 10 months
geneticssimulation-frameworkchemicalsystems-biologysimulation
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