Shenggan Cheng
Singapore
Summary
🤩
Rockstar🎓
Top SchoolShenggan Cheng is a PhD student at the National University of Singapore and an experienced research engineer with nine years in HPC and AI systems, grounded in a Bachelor’s from Shanghai Jiao Tong University. He has applied low-level CUDA expertise to accelerate large-model training, contributing optimized kernels for dropout and activation functions to the widely used ColossalAI project. Previously he worked at Shanghai Jiao Tong University’s Center for HPC and interned at SenseTime, blending academic research with industry-scale computer vision and systems experience. Based in Singapore, Shenggan combines deep systems programming skills with a research mindset focused on making large AI models cheaper and faster. An understated strength is his track record of cleaning and refactoring GPU code, improving both performance and maintainability for production-ready open-source tooling.
9 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Shanghai Jiao Tong UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at National University of Singapore
Github Skills (9)
cuda10
pytorch10
deep-learning10
ai9
machine-learning9
cprogramming-language7
distributed-computing7
c-language7
parallelization5
Programming languages (11)
Github contributions (5)
hpcaitech/ColossalAI
Dec 2021 - Jan 2023
Making large AI models cheaper, faster and more accessible
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 8 commits, 9 PRs in 1 year
Contributions summary:Shenggan contributed to the `colossalai` repository, focused on large AI models. They implemented CUDA kernels for dropout and activation functions, optimizing the performance of deep learning models. The commits demonstrate a strong understanding of CUDA programming and deep learning fundamentals. The user also refactored and polished code style in existing CUDA kernels.
heterogeneous-trainingcolossal-aifinetuningdeep-learninginference
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