Fengbin Tu
Associate Director, HKUST And Intel Joint Laboratory
Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolFengbin Tu is an associate director and assistant professor at HKUST specializing in AI chips, computing-in-memory, computer architecture, and reconfigurable computing, with a decade of experience bridging academia and industry collaborations such as the HKUST–Intel Joint Laboratory. He earned his PhD from Tsinghua and completed postdoctoral work at UC Santa Barbara’s SEAL lab and Hong Kong’s ACCESS center, where he helped develop the AC-Transformer—the first Hong Kong AI chip presented at ISSCC. His research has produced award-winning AI chips (Thinker, ReDCIM) recognized by ISLPED and China’s semiconductor community, and he’s a recipient of NSFC Excellent Young Scientists Fund and MIT Technology Review TR35 Asia-Pacific. Known for translating cutting-edge circuit and architecture ideas into tangible silicon, he combines strong theoretical grounding with hands-on chip design and system integration. Based in Hong Kong, he maintains an active research presence and public portfolio at fengbintu.github.io.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS Electronic Science and Technology, Bachelor of Science - BS Electronic Science and Technology at Beijing University of Posts and TelecommunicationsDoctor of Philosophy - PhD Electronic Science and Technology, Doctor of Philosophy - PhD Electronic Science and Technology at Tsinghua University
Github Skills (12)
neural-network10
markdown10
machine-learning10
deep-learning10
tensorflow10
github-pages10
gitpod10
jekyll10
architecture10
computer-architecture10
pytorch5
deep-neural-networks3
Programming languages (1)
Github contributions (5)
fengbintu/fengbintu.github.io
Jan 2022 - Jan 2023
Contributions:144 commits, 111 pushes, 1 branch in 1 year
fengbintu/Neural-Networks-on-Silicon
Jan 2016 - Dec 2022
This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.
Contributions:247 commits, 17 PRs, 237 pushes in 6 years 11 months
deep-learningneural-networksmachine-learningneural-networkaccelerators
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