Luo Mai
Associate Professor (Reader)
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolLuo Mai is an Associate Professor (Reader) at the University of Edinburgh who leads the Large-Scale Machine Learning Systems Group and co-leads national efforts in training and scaling AI compute. Over 11+ years in research and engineering roles at Edinburgh, Imperial College London, and Microsoft, Luo focuses on full-stack AI systems co-designs that target orders-of-magnitude gains in efficiency, scalability, and reliability. His work bridges theory and practice—publishing, open-sourcing system libraries that have amassed 20,000+ GitHub stars, and co-editing the open textbook Machine Learning Systems: Design and Implementation. A Google‑funded PhD alumnus with hands-on contributions to projects like TensorLayer and HyperPose, he combines rigorous cloud-computing foundations with practical code- and doc-level improvements. Colleagues know him for translating large-scale ML research into robust, production-ready tooling and for an uncommon emphasis on documentation and knowledge exchange alongside systems innovation.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Imperial College LondonBachelor of Engineering (BEng), Bachelor of Engineering (BEng) at Xidian University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
computer-vision10
rs10
tensorflow10
restructuredtext10
python10
pose-estimation10
documentation10
refactor9
refactoring9
tensorlayer9
deep-learning8
neural-network8
reinforcement-learning8
artificial-neural-networks8
configuration-management7
Programming languages (7)
Github contributions (5)
tensorlayer/HyperPose
Sep 2018 - Jun 2021
Library for Fast and Flexible Human Pose Estimation
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:5 reviews, 105 commits, 53 PRs in 2 years 10 months
Contributions summary:Luo primarily focused on refactoring and cleaning the codebase, improving the code's readability and maintainability. They made modifications to the `train.py`, `models.py`, `test_inference.py`, `uff-runner.py`, `export.py`, `config.py` files, indicating a broad involvement across the project. Their changes touch on data augmentation, model definition, and training configurations, demonstrating a focus on improving the core functionality of the human pose estimation library.
flexiblehuman-posetensorlayerdeep-learningcomputer-vision
tensorlayer/TensorLayer
Sep 2016 - Jan 2020
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Role in this project:Technical Writer
Technical WriterContributions:5 releases, 401 commits, 121 PRs in 3 years 4 months
Contributions summary:Luo primarily contributed to the project's documentation by updating and refining the `index.rst` file. Their work involved restructuring the document, correcting typos, and improving the clarity and organization of the content. The user also made edits to reflect changes in the `README` file, ensuring consistency between the project's documentation and its overview. These updates focused on improving the user guide and design philosophy descriptions within the TensorLayer documentation.
tensorflow-tutorialscientistspythongoogledeep-reinforcement-learning
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