Sunash Sharma

Graduate Research Aide

Pasadena, California, United States
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Summary

👤
Senior
🎓
Top School
Sunash 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.
code10 years of coding experience
bookDoctor of Philosophy - PhD, EECS, Doctor of Philosophy - PhD, EECS at University of California, Berkeley
bookCalifornia Institute of Technology
languagesEnglish, Spanish
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Github Skills (9)

electrical-engineering10
snl-applications9
portal6
mpc5
openai-gym5
deep-reinforcement-learning3
reinforcement-learning3
gymnasium3
openai2

Programming languages (3)

DockerfileTeXPython

Github contributions (5)

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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
gym-environmentsreinforcement-learninggymnasiumdeep-reinforcement-learningopenai
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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