about
Hello👋! This is Wenjie Wei（卫文杰）. I am currently a Ph.D. student (from fall 2022) in the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (Chengdu, Sichuan). I am supervised by Prof. Malu Zhang（张马路）. Prior to joining UESTC, I obtained my Bachelor’s degree from Zhengzhou University in 2021.
My research interests broadly encompass Brain-inspired Computing, Spiking Neural Networks, Model Compression, Neuromorphic Vision, etc. I have published more than 20 papers at the top international AI conferences/journals.
💬 Academic Services
- Journal Reviewer: Neural Networks, IEEE TETCI, IEEE TCDS, IEEE TBioCAS, Neurocomputing, Frontiers in Neuroscience, etc.
- Conference Reviewer: NeurIPS, ICLR, ICML, CVPR, AAAI, IJCAI, etc.
- Invited Oral Presentation titled “Event-Driven Learning for Spiking Neural Networks”, at the 11th IEEE International Conference on CIS-RAM Young Scholars Workshop.
- Core Contributor of the WeChat Official Account named “Progress in Brain-Inspired Intelligence”, regularly shares the latest developments in the Brain-Inspired Intelligence field.
🔥 News
- 2025.09: 🎉🎉 Three papers are accepted by NeurIPS-2025.
📝 Publications
Survey Papers
Spiking Neural Networks for EEG Signal Analysis: From Theory to Practice 
Siqi Cai, Zheyuan Lin, Xiaoli Liu, Wenjie Wei✉, Shuai Wang, Malu Zhang, Tanja Schultz, Haizhou Li
- The review encompasses foundational knowledge of SNNs, detailed implementation strategies for EEG analysis, and challenges inherent to SNN-based methods.
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What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips 
Renjie Li†, Qi Xin†, Wenjie Wei, Xiaoli Liu, Sixuan Mao, Erik Ma, Zijian Chen, Malu Zhang, Haizhou Li, Zhaoyu Zhang
- This review surveys emerging photonic hardware optimized for next-generation generative AI computing.
Selected Papers
S2NN: Sub-bit Spiking Neural Networks 
Wenjie Wei, Malu Zhang✉, Jieyuan Zhang, Ammar Belatreche, Shuai Wang, Yimeng Shan, Hanwen Liu, Honglin Cao, Guoqing Wang, Yang Yang, Haizhou Li
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This work introduces sub-bit SNNs, which compress synaptic weights to below one bit using outlier-aware sub-bit quantization and membrane potential-based feature distillation, achieving state-of-the-art efficiency and performance for edge computing applications.
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QP-SNNs: Quantized and Pruned Spiking Neural Networks
Wenjie Wei, Malu Zhang✉, Zijian Zhou, Ammar Belatreche, Yimeng Shan, Yu Liang, Honglin Cao, Jieyuan Zhang, Yang Yang
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This paper proposes QP-SNN, a lightweight and hardware-friendly model that combines weight rescaling-based quantization with singular value-based pruning for efficient edge deployment.
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Q-SNNs: Quantized Spiking Neural Networks
Wenjie Wei, Yu Liang, Ammar Belatreche, Yichen Xiao, Honglin Cao, Zhenbang Ren, Guoqing Wang, Malu Zhang✉, Yang Yang
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This paper introduces quantized spiking neural networks with binary weights and low-bit membrane potentials, along with a Weight-Spike Dual Regulation method, to achieve energy efficiency and high performance.
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Temporal-coded spiking neural networks with dynamic firing threshold: Learning with event-driven backpropagation
Wenjie Wei, Malu Zhang✉, Hong Qu, Ammar Belatreche, Jian Zhang, Hong Chen
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This paper introduces a dynamic firing threshold and direct training algorithm that enable temporal-coded SNNs to achieve high accuracy and energy efficiency.
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Others
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Temporal-coded Spiking Transformer.
Qian Sun, Chengzhuo Lu, Wenyu Chen, Wenjie Wei✉, Jingya Wang, Jieyuan Zhang, Xiaoli Liu, Yalan Ye, Yang Yang, Malu Zhang -
ESTSformer: Efficient Spatio-Temporal Spiking Transformer.
Chengzhuo Lu, Huilin Du, Wenjie Wei✉, Qian Sun, Yuchen Wang, Dingyi Zeng, Wenyu Chen, Malu Zhang, Yang Yang -
Spike-Driven Lightweight Large Language Model With Evolutionary Computation.
Malu Zhang, Wenjie Wei (Student First Author), Zijian Zhou, Wanlong Liu, Jie Zhang, Ammar Belatreche, Yang Yang -
Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism.
Yu Liang, Wenjie Wei, Ammar Belatreche, Honglin Cao, Zijian Zhou, Shuai Wang, Malu Zhang, Yang Yang -
BSO: Binary Spiking Online Optimization Algorithm.
Yu Liang, Yu Yang, Wenjie Wei, Ammar Belatreche, Shuai Wang, Malu Zhang, Yang Yang -
Binary Event-Driven Spiking Transformer.
Honglin Cao†, Zijian Zhou†, Wenjie Wei, Ammar Belatreche, Yu Liang, Dehao Zhang, Malu Zhang, Yang Yang, Haizhou Li -
Quantized Spike-driven Transformer.
Xuerui Qiu†, Malu Zhang, Jieyuan Zhang†, Wenjie Wei, Honglin Cao, Junsheng Guo, Rui-Jie Zhu, Yimeng Shan, Yang Yang, Haizhou Li -
Rethinking Spiking Self-Attention Mechanism: Implementing a-XNOR Similarity Calculation in Spiking Transformers.
Yichen Xiao†, Shuai Wang†, Dehao Zhang, Wenjie Wei, Yimeng Shan, Xiaoli Liu, Yulin Jiang, Malu Zhang -
Spike-based Neuromorphic Model for Sound Source Localization.
Dehao Zhang†, Shuai Wang†, Ammar Belatreche, Wenjie Wei, Yichen Xiao, Haorui Zheng, Zijian Zhou, Malu Zhang, Yang Yang -
Towards Energy-Efficient Spike-Based Deep Reinforcement Learning With Temporal Coding.
Malu Zhang, Shuai Wang, Jibin Wu, Wenjie Wei, Dehao Zhang, Zijian Zhou, Siying Wang, Fan Zhang, Yang Yang -
Memory-Free and Parallel Computation for Quantized Spiking Neural Networks.
Dehao Zhang, Shuai Wang, Yichen Xiao, Wenjie Wei, Yimeng Shan, Malu Zhang, Yang Yang -
Ternary spike-based neuromorphic signal processing system.
Shuai Wang, Dehao Zhang, Ammar Belatreche, Yichen Xiao, Hongyu Qing, Wenjie Wei, Malu Zhang, Yang Yang -
Sdtrack: A baseline for event-based tracking via spiking neural networks. |
Yimeng Shan, Zhenbang Ren, Haodi Wu, Wenjie Wei, Rui-Jie Zhu, Shuai Wang, et al.
Spike-Driven Lightweight Large Language Model With Evolutionary Computation. 
Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism. 
Towards Energy-Efficient Spike-Based Deep Reinforcement Learning With Temporal Coding. 
Memory-Free and Parallel Computation for Quantized Spiking Neural Networks. 