Charles Guo
Quantum ML Scientist at University of Technology Sydney
Australia
Summary
👤
Senior🎓
Top SchoolCharles Guo is a Quantum ML Scientist with a PhD in Electrical Engineering from UNSW and a decade of experience applying advanced ML, reinforcement learning, and non-convex optimisation to wireless systems and quantum hardware. He developed the internationally awarded GJC matrix multiple-beamforming architecture during his PhD and translated that work into novel deep RL methods for 6G antenna design. After industry and research roles spanning Telstra and UTS—where he built generative AI models for antenna architectures and led collaborations with major Australian agencies—he now focuses on quantum machine learning at Silicon Quantum Computing to demonstrate quantum advantage and improve chip design. Known for bridging theoretical rigor with practical deployment, he combines physics, materials science and ML expertise to solve interdisciplinary engineering problems. An often-overlooked strength is his track record of moving academic innovations into industry-relevant tools and prototypes.
10 years of coding experience
5 years of employment as a software developer
University of California, San DiegoThe University of SydneyUNSW Sydney
Github Skills (1)
batch4
Github contributions (5)
charlesguo/sg-wdi-2-materials
Feb 2016 - May 2016
Contributions:14 pushes, 1 branch in 2 months
K2GFA/Tradist
Apr 2016 - Apr 2016
Contributions:12 pushes, 18 branches in 6 days
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