Nicholas Borda
Graduate Research Assistant
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolNicholas Borda is an electrical engineering PhD student and research engineer with eight years of experience advancing wireless communications, signal processing, and antenna array techniques across academia and industry. He has contributed to cutting-edge projects from phased-array beamforming and sparse angle-of-arrival estimation at MIT Lincoln Laboratory to RIS calibration and mmWave system design at UCLA, and built ML-based channel estimation models during an Apple internship. Currently a Graduate Research Assistant at UT Austin's Genesys Lab, he blends rigorous MATLAB prototyping with Python/TensorFlow for practical RF and AI/ML solutions. Nicholas’s background also includes hands-on makerspace mentorship and production-focused failure analysis at Tesla, evidencing both experimental rigor and an eye for manufacturable improvements. Colleagues describe him as a reliable collaborator who navigates theoretical research and applied engineering, often finding creative, non-obvious ways to exploit hardware constraints for robust wireless performance.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at The University of Texas at AustinBachelor of Science - BS, Electrical Engineering, Bachelor of Science - BS, Electrical Engineering at University of Massachusetts AmherstUniversity of California, Los Angeles
Github Skills (7)
nim-lang8
rewriting8
representations7
nim-language6
induction5
rust3
machine-learning3
Programming languages (1)
Github contributions (5)
na2021/term-rewriting-rs
Jun 2018 - Feb 2019
a Rust implementation of first-order term rewriting systems (TRS)
Contributions:96 pushes, 24 branches in 8 months
rustrewritingterm-rewritingfirst-orderterm
na2021/program-induction
Jul 2018 - Jun 2019
A library for program induction and learning representations.
Contributions:39 pushes, 5 branches in 10 months
program-inductionrepresentationsmachine-learninginductionrepresentations-learning
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