Gary Cheng
Co-Founder at Amplify Renewables
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolGary Cheng is a machine-learning researcher-turned-founder with 11 years of experience applying optimization and personalized ML to real-world problems, now accelerating the renewable energy transition as Co-Founder of Amplify Renewables. He completed a PhD at Stanford (advised by John Duchi) with internships at Google (federated learning) and Max Planck (causal inference), and has contributed to Google Research’s federated learning codebase—working on FedAvg, weight-delta projection, and efficiency/privacy-minded operations. His background blends theory (dataset summarization, stochastic optimization) and production-facing engineering (Amazon forecasting, full-stack integrations), enabling him to bridge research and deployment. Based in the San Francisco Bay Area, he is actively exploring climate-tech opportunities and publishes his work and bio at garycheng.me.
10 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
Github Skills (6)
machine-learning10
deep-learning10
tensorflow10
python10
federated-learning10
keras9
Programming languages (1)
Github contributions (5)
google-research/federated
Aug 2021 - Sep 2021
A collection of Google research projects related to Federated Learning and Federated Analytics.
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 12 commits, 1 PR in 1 month
Contributions summary:Gary contributed to the development and testing of federated learning systems, particularly focusing on large model training. Their commits demonstrate involvement in implementing and testing Federated Averaging (FedAvg) algorithms. The changes include code restructuring to support shrink and unshrink operations, and the addition of projection functionality to weight deltas to potentially improve model efficiency or privacy.
analyticsfederated-analyticsmachine-learningkubernetesfederated-learning
garyxcheng/garyxcheng.github.io
Oct 2015 - Nov 2023
Contributions:108 pushes, 3 branches in 8 years 2 months
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