1. Educational Background (in reverse chronological order)：

• 2017-2019: National University of Singapore, Electrical and Computer Engineering (Joint-Training Visiting PhD Student, sponsored by China Scholarship Council)
• 2014-2019: University of Electronic Science and Technology of China, Computer Science and Technology, Doctor of Philosophy

2. Work Experience (in reverse chronological order)：

• 2022-Present: University of Electronic Science and Technology of China, School of Computer Science and Engineering, Professor, Doctoral Supervisor
• 2019-2021: National University of Singapore, Research Fellow

Joint-appointed Professor and Ph.D. Supervisor at Shenzhen Hetao College, he has long been dedicated to fundamental theories and key technologies in the field of brain-inspired intelligence. Over the past five years, he has achieved a series of research results in brain-inspired perception, learning, and modeling, publishing over 100 academic papers in internationally authoritative journals and top-tier conferences. Among these, 40 papers were published as first/corresponding author in journals ranked in the Chinese Academy of Sciences (CAS) Zone 1 and CCF-A category conferences, including IEEE TPAMI, 5 papers in NeurIPS, 3 papers in ICLR, and 7 papers in IEEE TNNLS. Several papers were selected as Oral presentations at AAAI (acceptance rate 4.6%), Oral presentations at CVPR (acceptance rate 0.7%), and Spotlight presentations at NeurIPS (acceptance rate 3.2%). His research findings have received positive evaluations and citations from Professor Wulfram Gerstner, Academician Hong Qiao of the Chinese Academy of Sciences, Academician Yaochu Jin of the European Academy of Sciences, and multiple IEEE Fellows.
Currently, he serves as an Associate Editor for two academic journals: IEEE Transactions on Emerging Topics in Computational Intelligence and IEEE Transactions on Cognitive and Developmental Systems, and as an Area Chair for top-tier conferences such as ICLR 2026. In terms of research projects, he has led key military projects (funding: 5.4 million yuan), National Natural Science Foundation of China (NSFC) General Program, NSFC Youth Program, Sichuan Provincial Key R&D Program, China Postdoctoral Science Foundation First-Class Funding (only 4 recipients nationwide), Hikvision Bantouyan Fund, and Zhejiang Lab International Young Talent Fund. As a core member, he has participated in 5 national-level projects, including the Ministry of Science and Technology’s Major Program and NSFC Key Program. He has also applied for 5 Chinese technological invention patents. Additionally, from 2024 to 2025, the applicant was seconded to the National Development and Reform Commission, actively contributing to the advancement of artificial intelligence in China.

[1] Wu, Jibin, Chenglin Xu, Xiao Han, Daquan Zhou, Malu Zhang*, Haizhou Li, and Kay Chen Tan. Progressive tandem learning for pattern recognition with deep spiking neural networks [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 44(11): 7824–7840. (SCI 1区，DOI: 10.1109/TPAMI.2021.3114196)

[2] Xiao Yichen, Wang Shuai, Zhang Dehao, Wei Wenjie, Shan Yimeng, Liu Xiaoli, Jiang Yulin and Zhang Malu*. Rethinking Spiking Self-Attention Mechanism: Implementing a-XNOR Similarity Calculation in Spiking Transformers. Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR-2025) (Oral Paper). DOI: 10.1109/CVPR52734.2025.00512.

[3] Wang, Shuai, Malu Zhang*, Jingya Wang, Dehao Zhang, Yimeng Shan, Jieyuan Zhang, Yichen Xiao, Honglin Cao, Haonan Zhang, Zeyu Ma, Yang Yang, Haizhou Li. Bipolar Self-attention for Spiking Transformers. 39th Conference on Neural Information Processing Systems (NeurIPS-2025) (Spotlight Paper).

[4] Wenjie Wei, Malu Zhang*, Jieyuan Zhang, Ammar Belatreche, Shuai Wang, Yimeng Shan, Hanwen Liu, Honglin Cao, Guoqing Wang, Yang Yang, Haizhou Li. S2NN: Sub-bit Spiking Neural Networks. 39th Conference on Neural Information Processing Systems (NeurIPS-2025). DOI: https://doi.org/10.48550/arXiv.2509.24266

[5] Zhang Dehao, Malu Zhang*, Shuai Wang, Jingya Wang, Wenjie Wei, Zeyu Ma, Guoqing Wang, Yang Yang, Haizhou Li. Dendritic Resonate-and-Fire Neuron for Effective and Efficient Long Sequence Modeling. 39th Conference on Neural Information Processing Systems (NeurIPS-2025). DOI: https://doi.org/10.48550/arXiv.2509.17186

[6] Jieyuan Zhang, Xiaolong Zhou, Wenjie Wei, Hanwen Liu, Qian Sun, Shuai Wang, Malu Zhang*, Yang Yang, Haizhou Li. Unveiling the Spatial-temporal Effective Receptive Fields of Spiking Neural Networks. 39th Conference on Neural Information Processing Systems (NeurIPS-2025). DOI: https://doi.org/10.48550/arXiv.2510.21403

[7] Zhang, Dehao, Shuai Wang, Ammar Belatreche, Wenjie Wei, Yichen Xiao, Haorui Zheng, Zijian Zhou, Malu Zhang* and Yang Yang. Spike-based Neuromorphic Model for Sound Source Localization. The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS-2024).

[8] Liang Yu, Yang Yu, Wei Wenjie, Belatreche Ammar, Wang Shuai, Malu Zhang* and Yang Yang. BSO: Binary Spiking Online Optimization Algorithm. Forty-second International Conference on Machine Learning (ICML-2025). DOI: https://doi.org/10.48550/arXiv.2511.12502

[9] Qiu, Xuerui, Malu Zhang*, Jieyuan Zhang, Wenjie Wei, Honglin Cao, Junsheng Guo, Rui-Jie Zhu, Yimeng Shan, Yang Yang and Haizhou Li. Quantized Spike-driven Transformer. International Conference on Learning Representations (ICLR-2025). DOI: https://doi.org/10.48550/arXiv.2501.13492

[10] Wang, Shuai, Malu Zhang*, Dehao Zhang, Ammar Belatreche, Yichen Xiao, Yu Liang, Yimeng Shan, Qian Sun, Enqi Zhang, and Yang Yang. Spiking Vision Transformer with Saccadic Attention. International Conference on Learning Representations (ICLR-2025). DOI: https://doi.org/10.48550/arXiv.2502.12677

[11] Wei, Wenjie, Malu Zhang*, Zijian Zhou, Ammar Belatreche, Yimeng Shan, Yu Liang, Honglin Cao, Jieyuan Zhang and Haizhou Li. QP-SNN: Quantized and Pruned Spiking Neural Networks. International Conference on Learning Representations (ICLR-2025). DOI: https://doi.org/10.48550/arXiv.2502.05905

[12] Zhang, Jiqing, Malu Zhang, Yuanchen Wang, Qianhui Liu, Baocai Yin, Haizhou Li and Xin Yang. Spiking Neural Networks with Adaptive Membrane Time Constant for Event-Based Tracking. IEEE Transactions on Image Processing, 2025. (SCI 1区，DOI: 10.1109/TIP.2025.3533213)

[13] Shuai Wang, Haorui Zheng, Yukun Chen, Ammar Belatreche, Malu Zhang*, Yang Yang and Haizhou Li. SNN-FT: Temporal-Coded Spiking Neural Networks for Fourier Transform. IEEE Transactions on Neural Networks and Learning Systems, 2026. (SCI 1区，DOI: 10.1109/TNNLS.2025.3622893)

[14] Zhang, Malu, Xiaoling Luo, Jibin Wu*, Ammar Belatreche, Siqi Cai, Yang Yang and Haizhou Li. Towards Building Human-Like Sequential Memory using Brain-Inspired Spiking Neural Models. IEEE Transactions on Neural Networks and Learning Systems, 2025. (SCI 1区，DOI: 10.1109/TNNLS.2025.3543673)

[15] Zhu, Rui-Jie, Malu Zhang, Qihang Zhao, Haoyu Deng, Yule Duan and Liang-Jian Deng. TCJA-SNN: Temporal-channel Joint Attention for Spiking Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 2024. (SCI 1区，DOI: 10.1109/TNNLS.2024.3377717)

[16] Xie, Xiurui, Yansong Chua, Guisong Liu, Malu Zhang, Guangchun Luo, and Huajin Tang. Event-Driven Spiking Learning Algorithm Using Aggregated Labels. IEEE Transactions on Neural Networks and Learning Systems, 2023. (SCI 1区，DOI: 10.1109/TNNLS.2023.3306749)

[17] Luo, Xiaoling, Hong Qu, Yuchen Wang, Zhang Yi, Jilun Zhang, and Malu Zhang. Supervised Learning in Multilayer Spiking Neural Networks with Spike Temporal Error Backpropagation. IEEE Transactions on Neural Networks and Learning Systems, 2022. (SCI 1区，DOI: 10.1109/TNNLS.2022.3164930)

[18] Malu Zhang, Jiadong Wang, Jibin Wu, Ammar Belatreche, Burin Amornpaisannon, Zhixuan Zhang, Venkata Pavan Kumar Miriyala et al. Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 2021, 33(5): 1947–1958. (SCI 1区，DOI: 10.1109/TNNLS.2021.3110991)

[19] Zhang, Malu, Hong Qu, Ammar Belatreche, Yi Chen, and Zhang Yi*. A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(1): 123–137. (SCI 1区，DOI: 10.1109/TNNLS.2018.2833077)

[20] Malu Zhang, Wenjie Wei, Zijian Zhou, Wanlong Liu, Jie Zhang*, Ammar Belatreche and Yang Yang. Spike-Driven Lightweight Large Language Model with Evolutionary Computation. IEEE Transactions on Evolutionary Computation, 2025. (SCI 1区，DOI: 10.1109/TEVC.2025.3606613)