Felicia Guo
Postdoctoral Researcher at University of California, Berkeley
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolFelicia Guo is a postdoctoral researcher at UC Berkeley specializing in domain-specific machine learning for analog-mixed-signal (AMS) circuit design, with eight years of experience spanning academia and industry. Her PhD work produced reinforcement-learning methods and a codified generator framework to create novel AMS circuit topologies, and her research is grounded by hands-on circuit design across six tapeouts. She combines supervised, semi-supervised, physics-informed and RL techniques to accelerate circuit exploration and optimization, bridging theory with practical verification from internships at Cadence and hardware roles at Apple and Astranis. Based in Berkeley, she brings a rare mix of deep ML methodology and practical RF/optical hardware testbench experience, often translating automated measurement data into algorithmic improvements.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Electrical Engineering, Doctor of Philosophy - PhD Electrical Engineering at University of California, BerkeleyBachelor of Science - BS Electrical and Computer Engineering, Bachelor of Science - BS Electrical and Computer Engineering at Cornell University
Github Skills (20)
bag9
strava6
gpx5
designer5
xbase5
layout5
circuit4
schematic3
layout-engine3
version-control3
electrical-engineering3
testing2
vlsi2
pdk2
5g2
Programming languages (3)
Github contributions (5)
ucb-art/skywater-pdk-libs-sky130_bag3_pr
Jan 2022 - May 2024
BAG (BAG AMS Generator) Primitives Library for SKY130
Contributions:23 pushes, 12 branches in 2 years 4 months
bagsky130primitivesams
ieeecornell/website
Mar 2019 - Aug 2019
Website 2019
Contributions:10 commits, 6 pushes, 2 branches in 5 months
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