Wei Fang

MiroMind 人工智能研究科学家

prof_pic.jpg

wei.fang at miromind.ai

fangwei123456g at gmail.com

我目前是 MiroMind 的人工智能研究科学家。

我在北京大学计算机学院获得博士学位,指导老师为田永鸿教授。博士期间,我也与北京大学的余肇飞教授、法国国家科学研究中心的 Timothée Masquelier 研究员、中国科学院自动化研究所的李国齐教授长期合作。

我的主要研究方向包括脉冲神经网络的学习算法和网络结构设计。

欢迎对我研究感兴趣的团队联系我。

English homepage · 中文简历 · English CV

教育和工作经历

部分奖励荣誉

  • 2023 年度“石青云院士优秀论文奖”
  • 2024 年度北京大学优秀毕业生
  • 2024 年度北京市普通高等学校优秀毕业生
  • 2024 年度北京大学优秀博士学位论文
  • 2025 年度 CCF 博士学位论文激励计划(CCF 优博)

项目

更多内容见论文列表项目页博客

news

May 09, 2026 Homepage refreshed with the al-folio theme.

latest posts

May 09, 2026 Site refresh

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
  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
  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.
  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
  5. Event2Vec: Processing Neuromorphic Events Directly by Representations in Vector Space
    Wei Fang and Priyadarshini Panda
    In International Conference on Machine Learning, 2026