Sunash Sharma
Graduate Research Aide
Pasadena, California, United States
Summary
👤
Senior🎓
Top SchoolSunash Sharma is a PhD candidate in EECS at UC Berkeley and a Graduate Research Aide at Argonne National Laboratory focused on optimization strategies for power systems under deep uncertainty and large-scale grid capacity expansion. With a Caltech background in applied physics and computer science and membership in the inaugural Schmidt Academy, he blends rigorous modeling, software engineering, and reproducible research to build simulation platforms for EV charging and algorithms for optimal battery dispatch. His work spans theory-to-practice—from integrating grid reliability assessments with capacity planning to implementing Python simulations in fluid dynamics and quantum annealing experiments—reflecting a decade of interdisciplinary research experience. Sunash is seeking industry roles starting Fall 2026 and brings uncommon cross-domain fluency that helps translate advanced optimization methods into deployable tools for energy systems.
10 years of coding experience
Doctor of Philosophy - PhD, EECS, Doctor of Philosophy - PhD, EECS at University of California, BerkeleyCalifornia Institute of Technology
English, Spanish
Github Skills (5)
snl-applications10
electrical-engineering10
openai-gym6
algorithms5
reinforcement-learning4
Programming languages (3)
Github contributions (5)
caltech-netlab/gym-acnportal
Apr 2020 - May 2022
OpenAI Gym environments and utilities for reinforcement learning with ACN-Portal
Contributions:8 PRs, 39 pushes, 6 branches in 2 years 1 month
openai-gymreinforcement-learning
zach401/acnportal
Aug 2019 - Jun 2021
Research tools for the Adaptive Charging Network
Contributions:2 releases, 41 reviews, 544 commits in 1 year 10 months
snl-applicationsadaptivechargingelectrical-engineering
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