Wei Fang’s Homepage

I am currently the Postdoc Association in Electrical & Computer Engineering, Yale University, mentored by Prof. Priya Panda.

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

My recent research interests are learning and network structure of Spiking Neural Network.

Please contact me (fangwei123456g at gmail.com) if you are interested in my research.

Last update: 2025.03.11

Education and Working Experience

2015.9 - 2019.6, bachelor, Department of Automation, Tsinghua University
2019.9 - 2024.6, Ph.D., School of Computer Science, Peking University
2024.7 - 2025.2, Research Assistant Professor, School of Electronic and Computer Engineering, Peking University
2025.3 - Now, Postdoc Association, Electrical & Computer Engineering, Yale University

Publications

First/Corresponding-author Papers

Wei Fang, Zhaofei Yu, Yanqi Chen, Timothée Masquelier, Tiejun Huang, Yonghong Tian, Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks, ICCV 2021
Wei Fang, Zhaofei Yu, Yanqi Chen, Tiejun Huang, Timothée Masquelier, Yonghong Tian, Deep Residual Learning in Spiking Neural Networks, NeurIPS 2021
Wei Fang, Yanqi Chen, Jianhao Ding, Zhaofei Yu, Timothée Masquelier, Ding Chen, Liwei Huang, Huihui Zhou, Guoqi Li, Yonghong Tian, SpikingJelly: An Open-source Machine Learning Infrastructure Platform for Spike-based Intelligence, Science Advances
- Recommended by Nature Computational Science in the Research Highlight article: A Full-stack Platform for Spiking Deep Learning
Wei Fang, Zhaofei Yu, Zhaokun Zhou, Ding Chen, Yanqi Chen, Zhengyu Ma, Timothée Masquelier, Yonghong Tian, Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies, NeurIPS 2023

Other Papers

Yanqi Chen, Zhaofei Yu, Wei Fang, Tiejun Huang, Yonghong Tian, Pruning of Deep Spiking Neural Networks through Gradient Rewiring, IJCAI 2021
Tong Bu, Wei Fang, Jianhao Ding, PengLin Dai, Zhaofei Yu, Tiejun Huang, Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks, ICLR 2022
Yanqi Chen, Zhaofei Yu, Wei Fang, Zhengyu Ma, Tiejun Huang, Yonghong Tian, State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks, ICML 2022
Yaoyu Zhu, Zhaofei Yu, Wei Fang, Xiaodong Xie, Tiejun Huang, Timothée Masquelier, Training Spiking Neural Networks with Event-driven Backpropagation, NeurIPS 2022
Yanqi Chen, Zhengyu Ma, Wei Fang, Xiawu Zheng, Zhaofei Yu, Yonghong Tian, A Unified Framework for Soft Threshold Pruning, ICLR 2023
Yaoyu Zhu, Wei Fang, Xiaodong Xie, Tiejun Huang, Zhaofei Yu, Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks, NeurIPS 2023
Liuzhenghao Lv, Wei Fang, Li Yuan, Yonghong Tian, Optimal ANN-SNN Conversion with Group Neurons, ICASSP 2024
Man Yao, Ole Richter, Guangshe Zhao, Ning Qiao, Yannan Xing, Dingheng Wang, Tianxiang Hu, Wei Fang, Tugba Demirci, Michele De Marchi, Lei Deng, Tianyi Yan, Carsten Nielsen, Sadique Sheik, Chenxi Wu, Yonghong Tian, Bo Xu, Guoqi Li, Spike-based Dynamic Computing with Asynchronous Sensing-Computing Neuromorphic Chip, Nature Communications
Haonan Qiu, Munan Ning, Zeyin Song, Wei Fang, Yanqi Chen, Tao Sun, Zhengyu Ma, Li Yuan, Yonghong Tian, Self-architectural Knowledge Distillation for Spiking Neural Networks, Neural Networks

Projects

SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN). I am one of the main contributors.
Python JPEG Encoder, which starts from scratch to create a standardized JPEG file.
Tello GUI Controller, a GUI controller based on Qt5 for the Tello UAV.

Contact

fangwei123456g at gmail.com
wei.fang at yale.edu