Summary
Navneeth 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 Technology
Doctor of Philosophy - PhD, Chemical Engineering, 3.55/4.00, Doctor of Philosophy - PhD, Chemical Engineering, 3.55/4.00 at University at Buffalo
Master 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