计算机科学与工程学院（网络空间安全学院）
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| 导师代码： |
20675
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| 导师姓名： |
张马路
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| 性 别： |
男 |
| 特 称： |
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| 职 称： |
研究员
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| 学 位： |
工学博士学位
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| 属 性： |
专职 |
| 电子邮件： |
maluzhang@uestc.edu.cn
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| 学术经历：
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2014年-2019年 电子科技大学 计算机科学与工程学院 博士; 2017年-2019年 新加坡国立大学 国家公派博士生； 2019年-2021年 新加坡国立大学 Research Fellow; 2022年-至今 电子科技大学 研究员、博导。
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| 个人简介：
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研究领域: 类脑计算、深度学习。
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| 科研项目：
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【1】 国家自然科学基金青年科学基金项目，基于深度 Spiking 神经网络的多模态类脑模型研究，
2022-01 至 2024-12，30 万，主持。
【2】中国博士后科学基金（一等资助），2020M680148，具有多模态感知能力的深度 Spiking 神经
网络类脑模型研究，2020-11 至 2022-12，12 万，主持
【3】CCF-海康威视斑头雁基金，基于脉冲神经网络的编码和算法研究，2022-1 至 2023-11，30 万，主持。
【4】之江实验室国际青年人才基金，类脑 Spiking 神经网络模型研究，2021-1 至 2022-1，3 万，在研，主持。
【5】科技创新 2030-“新一代人工智能”重大项目-课题二，2018AAA0100202，神经元和模块功能
特异化研究，2019-07 至 2023-12，154 万，主研。
【6】国家自然科学基金，61976043，具有模块功能特异化性质的新型 Spiking 神经网络模型研究，
2020-01 至 2023-12，64 万，在研，参与。
【7】国家自然科学基金青年基金，61806040，具有时序迁移能力的 Spiking-Transfer learning (脉
冲-迁移学习) 方法研究，2019-01 至 2021-12，20 万，主研。
【8】中央JW 科技委，GF 科技创新特区，2118Y29091A，类脑芯片基础理论xxxx 模型研究，2018-
12 至 2020-12，100 万，主研。
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| 研究成果：
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期刊论文：
[1]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.
[2]Zhang, Malu, Shuai Wang, Jibin Wu, Wenjie Wei, Dehao Zhang, Zijian Zhou, Siying Wang, Fan Zhang and Yang Yang，Toward Energy-Efficient Spike-Based Deep Reinforcement Learning with Temporal Coding, IEEE Computational Intelligence Magazine,2025.
[3]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.
[4]Pengfei, Sun, De Winne J, Malu Zhang*, Paul Devos, Dick Botteldooren. Delayed knowledge transfer: Cross-modal knowledge transfer from delayed stimulus to EEG for continuous attention detection based on spike-represented EEG signals[J]. Neural Networks, 2025.
[5]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.
[6]Zeng, Dingyi, Yichen Xiao Wanlong Liu, Huilin Du, Enqi Zhang, Dehao Zhang, and Yuchen Wang, Malu Zhang* and Wenyu Chen. Efficient Automatic Modulation Classification in Non-Terrestrial Networks With SNN-Based Transformer[J]. IEEE Internet of Things Journal, 2024.
[7]Sun, Pengfei, Jibin Wu, Malu Zhang*, Paul Devos and Dick Botteldooren. Delay learning based on temporal coding in Spiking Neural Networks[J]. Neural Networks, 2024, 180: 106678.
[8]Xie, Xiurui, Yansong Chua, Guisong Liu*, Malu Zhang*, Guangchun Luo, and Huajin Tang. Event-Driven Spiking Learning Algorithm Using Aggregated Labels[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023.
[9]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[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022.
[10]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[J]. IEEE transactions on neural networks and learning systems, 2021, 33(5): 1947-1958.
[11]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.
[12]Pan, Zihan, Malu Zhang#, Jibin Wu, Jiadong Wang, and Haizhou Li. Multi-tone phase coding of interaural time difference for sound source localization with spiking neural networks[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021, 29: 2656-2670.
[13]Zhang, Malu, Xiaoling Luo, Yi Chen, Jibin Wu, Ammar Belatreche, Zihan Pan, Hong Qu, and Haizhou Li. An efficient threshold-driven aggregate-label learning algorithm for multimodal information processing[J]. IEEE Journal of Selected Topics in Signal Processing, 2020, 14(3): 592-602.
[14]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[J]. IEEE transactions on neural networks and learning systems, 2019, 30(1): 123-137.
[15]Zhang, Malu, Jibin Wu, Ammar Belatreche, Zihan Pan, Xiurui Xie, Yansong Chua, Guoqi Li, Hong Qu, and Haizhou Li. Supervised learning in spiking neural networks with synaptic delay-weight plasticity[J]. Neurocomputing, 2020, 409: 103-118.
[16]Zhang, Malu, Hong Qu, Xiurui Xie, and Jürgen Kurths. Supervised learning in spiking neural networks with noise-threshold[J]. Neurocomputing, 2017, 219: 333-349.
会议论文：
[1]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,2025.
[2]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,2025.
[3]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,2025.
[4]Liang, Yu, Wenjie Wei, Ammar Belatreche, Honglin Cao, Zijian Zhou, Shuai Wang, Malu Zhang*, Yang Yang. Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism. Proceedings of the AAAI conference on artificial intelligence, 2025.
[5]Zeng, DingYi, Yuchen Wang, Honglin Cao, Wanlong Liu, Yichen Xiao, ChengzhuoLu, Wenyu Chen, Malu Zhang*, Guoqing Wang, Yang Yang. Leveraging Asynchronous Spiking Neural Networks for Ultra Efficient Event-Based Visual Processing. Proceedings of the AAAI conference on artificial intelligence, 2025.
[6]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, 2024.
[7]Wang, Jiadong, Zexu Pan, Malu Zhang*, Robby T Tan and Haizhou Li. Restoring Speaking Lips from Occlusion for Audio-Visual Speech Recognition. Proceedings of the AAAI Conference on Artificial Intelligence, 2024, 38(17): 19144-19152.
[8]Zhang, Chen, Luis Fernando D'Haro, Yiming Chen, Malu Zhang* and Haizhou Li. A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators. Proceedings of the AAAI Conference on Artificial Intelligence, 2024, 38(17): 19515-19524.
[9]Wei, Wenjie, Yu Liang, Ammar Belatreche, Yichen Xiao, Honglin Cao, Zhenbang Renand, Guoqing Wang, Malu Zhang*, and Yang Yang. Q-snns: Quantized spiking neural networks. Proceedings of the 32nd ACM International Conference on Multimedia, 2024.
[10]Jin, Yeying, Xin Li, Jiadong Wang, Yan Zhang and Malu Zhang*. Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removal. European Conference on Computer Vision, 2024.
[11]Wei, Wenjie, Malu Zhang*, Hong Qu, Ammar Belatreche, Jian Zhang, and Hong Chen. Temporal-coded spiking neural networks with dynamic firing threshold: Learning with event-driven backpropagation[C]. Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023: 10552-10562.
[12]Wang, Yuchen, Kexin Shi, Chengzhuo Lu, Yuguo Liu, Malu Zhang*, and Hong Qu. Spatial-temporal self-attention for asynchronous spiking neural networks[C]. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23. 2023, 8: 3085-3093.
[13]Zhang, Malu, Jibin Wu, Yansong Chua, Xiaoling Luo, Zihan Pan, Dan Liu, and Haizhou Li. MPD-AL: An efficient membrane potential driven aggregate-label learning algorithm for spiking neurons[C]. Proceedings of the AAAI conference on artificial intelligence. 2019, 33(01): 1327-1334.
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| 专业研究方向：
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| 专业名称 |
研究领域/方向 |
招生类别 |
| 081200计算机科学与技术 |
01计算理论，02机器智能与模式识别，06云计算与大数据处理 |
博士学术学位 |
| 085400电子信息 |
01“计算机科学与技术”研究组，03“计算机科学与技术”研究组（非全） |
博士专业学位 |
| 081200计算机科学与技术 |
01计算理论，02机器智能与模式识别，06云计算与大数据处理 |
硕士学术学位 |
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