Lei Gao
AI Research Scientist at University of Southern California
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolLei Gao is an AI research scientist and PhD candidate in electrical engineering at USC with nine years of experience bridging ML research and hardware-aware deployment. Currently at Microsoft and previously at USC’s SCIP Lab and TensorOpera AI, Lei has worked on federated learning, mobile neural network model conversions, and cross-device ML orchestration—contributing to the widely used FedML project for scalable distributed training. His background in SoC and ML ASIC internships plus a stint as an SoC design engineer gives him rare end-to-end fluency from chip-level acceleration to large-scale AI systems. Lei’s work focuses on making state-of-the-art models practical for constrained devices and cross-cloud inference, combining rigorous research with production-minded engineering. He is based in Los Angeles and brings a track record of translating academic ideas into deployable ML infrastructure.
9 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Electrical Enginnering, Doctor of Philosophy - PhD, Electrical Enginnering at University of Southern CaliforniaBachelor's degree, Electrical Engineering, Bachelor's degree, Electrical Engineering at University of California, Santa Barbara
Chinese, English
Github Skills (11)
continuous-deployment10
pytorch10
machine-learning10
distributed-training10
deep-learning10
python10
federated-learning10
ml-deployment10
tensorflow9
cifar1009
mnist9
Programming languages (4)
Github contributions (5)
FedML-AI/FedML
Jun 2021 - Jul 2022
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
Role in this project:
ML Engineer
ML EngineerContributions:147 commits, 4 PRs, 81 pushes in 1 year 1 month
Contributions summary:Lei contributed to the implementation and modification of machine learning models within the FedML framework, specifically focusing on federated learning and mobile deployment. They updated and created model definitions for MNN (Mobile Neural Network) format, including ResNet20 and LeNet5 models. Further contributions include integrating datasets like CIFAR10 and MNIST, and server-side MNN integration to the cross-device framework.
inference-enginepythonsimulationdecentralizedsilo
leigao97/leigao97.github.io
Apr 2023 - Dec 2024
Contributions:35 pushes, 1 branch in 1 year 8 months
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