Wei Fang

AI Research Scientist at MiroMind

prof_pic.jpg

wei.fang at miromind.ai

fangwei123456g at gmail.com

I am currently an AI research scientist at MiroMind.

I received my Ph.D. degree from the School of Computer Science, Peking University, supervised by Prof. Yonghong Tian. During my Ph.D. career, I closely cooperated with Prof. Zhaofei Yu of Peking University, Researcher Timothée Masquelier of CNRS, and Prof. Guoqi Li of the Institute of Automation, Chinese Academy of Sciences.

My recent research interests include learning algorithms and network structures for Spiking Neural Networks.

Please contact me if you are interested in my research.

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selected publications

  1. Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
    Wei Fang, Zhaofei Yu, Yanqi Chen, Timothée Masquelier, Tiejun Huang, and Yonghong Tian
    In IEEE/CVF International Conference on Computer Vision, 2021
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  2. Deep Residual Learning in Spiking Neural Networks
    Wei Fang, Zhaofei Yu, Yanqi Chen, Tiejun Huang, Timothée Masquelier, and Yonghong Tian
    In Advances in Neural Information Processing Systems, 2021
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  3. SpikingJelly: An Open-source Machine Learning Infrastructure Platform for Spike-based Intelligence
    Wei Fang, Yanqi Chen, Jianhao Ding, Zhaofei Yu, Timothée Masquelier, Ding Chen, Liwei Huang, Huihui Zhou, Guoqi Li, and Yonghong Tian
    Science Advances, 2023
    Recommended by Nature Computational Science in the Research Highlight article: A Full-stack Platform for Spiking Deep Learning.
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  4. Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies
    Wei Fang, Zhaofei Yu, Zhaokun Zhou, Ding Chen, Yanqi Chen, Zhengyu Ma, Timothée Masquelier, and Yonghong Tian
    In Advances in Neural Information Processing Systems, 2023
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  5. Event2Vec: Processing Neuromorphic Events Directly by Representations in Vector Space
    Wei Fang and Priyadarshini Panda
    In International Conference on Machine Learning, 2026
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