Haibiao Chen
Professor at Shenzhen Polytechnic
Shenzhen, Guangdong Province, China
Summary
🤩
Rockstar🎓
Top SchoolHaibiao Chen is a professor and materials scientist with eight years of post-PhD academic and research experience and a two-decade track record bridging materials engineering, catalyst development, and automation. He has held roles from development engineer and materials scientist in industry to research professor and current faculty at Shenzhen Polytechnic, applying sol-gel, self-assembly and microreactor expertise to practical systems. Recently he has extended his technical reach into computational tools, contributing to the SpikingJelly spiking neural network framework by improving its simulator and documentation to make fast simulation options more usable and explainable. Based in Shenzhen with degrees from Tsinghua and a PhD from Stevens Institute of Technology, he combines deep experimental know-how with hands-on software contribution—an unusual cross-disciplinary mix that helps translate materials research into automated, simulation-driven solutions.
8 years of coding experience
11 years of employment as a software developer
Bachelor, Materials Science and Engineering, Bachelor, Materials Science and Engineering at Tsinghua UniversityPh.D., Materials Science and Engineering, Ph.D., Materials Science and Engineering at Stevens Institute of Technology
Github Skills (4)
documentation10
deep-learning10
pytorch10
python9
Programming languages (5)
Github contributions (5)
fangwei123456/spikingjelly
Feb 2020 - Jul 2022
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
Role in this project:
Back-end Developer & Technical Writer
Back-end Developer & Technical WriterContributions:213 commits, 6 PRs, 176 pushes in 2 years 5 months
Contributions summary:Haibiao primarily contributed to the documentation and functionality of the SpikingJelly framework's simulator module. They added detailed explanations of the simulation principles, including time-driven models and fast simulation options. In addition, they modified the source code of the simulator to include fast simulation capabilities and integrated documentation for better understanding. Their work appears to be focused on improving the usability and explainability of the simulator module.
pytorchspiking-neural-networksdeep-learningdvsmachine-learning
Yanqi-Chen/Yanqi-Chen.github.io
Feb 2019 - Apr 2021
Contributions:92 commits, 96 pushes, 1 branch in 2 years 2 months
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