张铁林-中国科学院大学-UCAS
[中文]
[English]
招生信息
教育背景
工作经历
教授课程
专利与奖励
出版信息
科研活动
合作情况
指导过的学生或实习生
基本信息
张铁林 男 硕导 中国科学院自动化研究所电子邮件： tielin.zhang@ia.ac.cn通信地址： 北京市海淀区中关村东路95号邮政编码： 100190
研究领域
张铁林副研究员，隶属于复杂系统认知与决策国家实验室的智能机制机理研究部，任认知机理与类脑学习方向PI；同属类脑智能研究中心，攻关类脑脉冲神经网络模型及面向类脑芯片、脑机接口的相关应用。小组现有职工3人，学生10人，已在多尺度可塑性、工作记忆、认知抉择、多感觉融合、侵入式脑机接口算法、类脑决策博弈等多项交叉学科方向展开深入研究。未来将通过数学、计算、控制、物理、认知、心理等多学科的深入交叉，在复杂系统智能认知与决策的基础理论、类脑智能机制机理等方面实现突破。张铁林十分关注新型类脑脉冲神经网络（Spiking Neural Network，SNN），提出了自组织可塑性传播模型在ANN和SNN上助力高效学习（2020，Science子刊Science Advances，一作）；提出了基于多巴胺奖赏传播的SNN高效学习方法(2021，IEEE TNNLS，一作)；提出基于多尺度可塑性的SNN架构体系，实现了非BP方法的合理优化（2018，AAAI，一作）；提出基于SNN的多脑区联合控制系统（2021，IEEE TNNLS，通讯）。作为主要贡献者之一参与大规模小鼠脑全脑SNN的计算仿真模拟（含7100万神经元和213脑区）；完成了基于高尔基染色大鼠脑光学切片的神经元重建及分类（含250万神经元形态）；承接上海市级重大专项中的高通量脑机接口SNN算法，提出采用天然生物合理的SNN算法高效识别和调控多尺度的生物脉冲信号；参与所级新型SNN芯片系统的类脑软件研发。研究组已在Science Advances、IEEE Transactions on Neural Networks、IEEE Transactions on Cybernetics、iScience、Cognitive Computation、Frontiers系列刊物等AI期刊和AAAI、IJCAI、ICASSP等AI会议上发表高水平论文39篇，拥有专利10余项。承担科技部科技创新2030新一代人工智能旗舰项目和重点项目，中科院战略先导计划A类和B类项目，国家自然科学基金委项目、装备发展部项目、北京市科委类脑专项、上海脑机接口重大专项、中科院青年创新促进会等。目前所在团队总负责人为徐波研究员，科研积累雄厚，科研经费充足。因工作需要，科研小组同时招聘对智能机制机理研究感兴趣的研究助理、博士后、工程师、实习生等人员若干，可以直接发邮件联系（tielin.zhang@ia.ac.cn），此信息长期有效。
招生信息
招收博士后、硕士研究生（保研或联培）、实习生（本科或硕士）等，强调做事踏实、主动汇报、乐观开朗、基础能力平衡（理论基础、代码能力、英文写作等）。
招生专业
081104-模式识别与智能系统081203-计算机应用技术085400-电子信息
招生方向
类脑学习与认知决策脑机接口脉冲神经网络
教育背景
2013-09--2016-07 中科院自动化所 博士2010-09--2013-07 北京工业大学 硕士2006-09--2010-07 北京工业大学 本科
工作经历
工作简历
2019-10~现在, 中科院自动化所, 副研究员2016-07~2019-10,中科院自动化所, 助理研究员
社会兼职
2022-12-01-今,Artificial Intelligence Advances 期刊, Editorial board member2022-12-01-2026-12-01,指挥与控制学会-云控制与决策专委会, 委员2016-12-20-2020-02-20,指挥与控制学会-认知与行为专委会, 副总干事
教授课程
系统与计算神经科学-类脑模型、架构与机器人应用类脑智能导论-人工神经元与浅层网络
专利与奖励
奖励信息
（1）&nbsp中国科学院青年创新促进会会员,&nbsp院级,&nbsp2022
专利成果
[1] 张铁林, 刘洪星, 徐波. 基于生物自组织反向传播的神经网络训练方法及装置.&nbspCN:&nbspCN113837380A,&nbsp2021-12-24.[2] 张铁林, 刘洪星, 徐波. 脉冲神经网络奖励优化方法、装置、电子设备和存储介质.&nbspCN:&nbspCN113822416A,&nbsp2021-12-21.[3] 张铁林, 曾毅, 史梦婷, 赵东城. 基于膜电位调控脉冲神经网络的图像分类方法、系统.&nbspCN:&nbspCN110826602A,&nbsp2020-02-21.[4] 张铁林, 曾毅, 史梦婷, 赵东城. 基于生物神经网络的智能机器人控制方法、系统、装置.&nbspCN:&nbspCN110826437A,&nbsp2020-02-21.[5] 赵菲菲, 张铁林, 曾毅. 基于脑发育机制的自适应神经网络模型的构建方法及系统.&nbspCN:&nbspCN110766138A,&nbsp2020-02-07.[6] 王寓巍, 张铁林, 曾毅. 基于类脑语义层次时序记忆推理模型的问答方法、系统.&nbspCN:&nbspCN109657036A,&nbsp2019-04-19.[7] 孔庆群, 张铁林, 鲁恩萌, 曾毅. 类脑多模态融合方法及装置.&nbspCN:&nbspCN108229540A,&nbsp2018-06-29.[8] 曾毅, 王东升, 张铁林. 基于语义网本体数据的集成方法.&nbspCN:&nbspCN105224630A,&nbsp2016-01-06.
出版信息
2023:[40] 张铁林*, 李澄宇, 王刚, 张马路, 余磊, 徐波. 适合类脑脉冲神经网络的应用任务范式分析与展望. 电子与信息学报(中文核心), Under Review, 2023.[Recommended][39] Qingyu Wang, Tielin Zhang*, Minglun Han, Yi Wang, and Bo Xu. Complex dynamic neurons improved spiking transformer network for efficient automatic speech recognition. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), Washington, DC, USA, Feb 7-14, 2023.[Recommended]2022:[38] Xiang Cheng, Tielin Zhang*, Shuncheng Jia, and Bo Xu. Meta neurons improve spiking neural networks for efficient spatio-temporal learning. NeuroComputing, 2022.[Recommended][37] Dengpeng Xing, Yiming Yang, Tielin Zhang, and Bo Xu. A Brain-Inspired Approach for Probabilistic Estimation and Efficient Planning in Precision Physical Interaction. IEEE Transactions on Cybernetics (SCI-Q1, IF 11.4), 2022.[Recommended][36] Shuncheng Jia#, Ruichen Zuo#, Tielin Zhang#*, Hongxing Liu, Bo Xu*. Motif-topology and Reward-learning improved Spiking Neural Network for Efficient Multi-sensory Integration. International Conference on Acoustics, Speech, & Signal Processing (ICASSP 2022, CCF-C), May 22 to May 27, 2022, Singapore.[Recommended][35] Duzhen Zhang#, Tielin Zhang#*, Shuncheng Jia, Bo Xu*. Multiscale Dynamic Coding improved Spiking Actor Networkfor Reinforcement Learning. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022, CCF-A), Feb 22 to Mar 1, 2022, Virtual conference. [Recommended][34] Xuan Han, Kebin Jia*, Tielin Zhang*. Mouse-Brain Topology improved Evolutionary Neural Network for Efficient Reinforcement Learning. International Conference on Intelligence Science (ICIS 2022), October 28-31, 2022.[33] Xiang Cheng, Xuan Han, Yu Song, Tielin Zhang*, Bo Xu*. Artificial Neural Network-assisted Amplitude Thresholding Improves Spike Detection. The 11th International Conference on Computing and Pattern Recognition (ICCPR 2022), 2022.2021:[32] Tielin Zhang, Xiang Cheng, Shuncheng Jia, Mu-ming Poo, Yi Zeng, Bo Xu*. Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks. Science Advances (SCI-Q1, IF 14.1), doi: 10.1126/sciadv.abh0146, Oct 20, 2021. [Recommended][31] Tielin Zhang*, Shuncheng Jia, Xiang Cheng, and Bo Xu*. Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward Propagation. IEEE Transactions on Neural Networks and Learning Systems (SCI-Q1, IF 10.4), doi: 10.1109/TNNLS.2021.3085966, June 14, 2021, 1-11. [Recommended][30] Dengpeng Xing, Jiale Li, Tielin Zhang*, Bo Xu. A Brain-Inspired Approach for Collision-Free Movement Planning in the Small Operational Space. IEEE Transactions on Neural Networks and Learning Systems (SCI-Q1, IF 10.4), doi: 10.1109/TNNLS.2021.3111051, Sep 14, 2021, 1-12[29] Tielin Zhang, and Bo Xu*. 脉冲神经网络研究现状及展望. 计算机学报 (中文核心), Vol. 44, No. 9, 1767-1785, Sep 2021. [Recommended][28] Shuncheng Jia#, Tielin Zhang#,*, Xiang Cheng, Hongxing Liu, Bo Xu*. Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural Networks. Frontiers in Neuroscience (SCI-Q2, IF 4.6), 15:654786, 2021[27] Tielin Zhang*, Yi Zeng*, Yue Zhang, Xinhe Zhang, Mengting Shi, Likai Tang, Duzhen Zhang and Bo Xu. Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks. Scientific Reports (SCI-Q1, IF 4.3), 11, 7291, Mar 31, 2021. [Recommended][26] Qinglai Wei*, Liyuan Han, Tielin Zhang. Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems. IEEE Transactions on Neural Networks and Learning Systems (SCI-Q1, IF 10.4), June 18, 2021, 1-11. [Recommended][25] Qinglai Wei*, Liyuan Han, Tielin Zhang. Spiking Adaptive Dynamic Programming with Poisson Process. International Conference on Swarm Intelligence (ICSI 2021, EI), 07 July 2021, 10.1007/978-3-030-78811-7_49.[24] Yinqian Sun, Yi Zeng, Tielin Zhang. Quantum Superposition Inspired Spiking Neural Network. iScience (SCI-Q1, IF 5.4), Vol. 24, Iss. 8, 102880, 10.1016/j.isci.2021.102880, Aug 20, 2021.[23] Qian Zhang, Yi Zeng, Tielin Zhang, Taoyi Yang. Comparison Between Human and Rodent Neurons for Persistent Activity Performance: A Biologically Plausible Computational Investigation. Frontiers in System Neuroscience, 15:628839, 10.3389/fnsys.2021.628839, Sep 9, 2021.2020:[22] Dongcheng Zhao, Yi Zeng, Tielin Zhang, Mengting Shi, Feifei Zhao. GLSNN: A Multi-layer Spiking Neural Network based on Global Feedback Alignment and Local STDP Plasticity. Frontiers in Computational Neuroscience (SCI-Q2, IF 2.3), 14:576841, Nov 12, 2020.[21] Yi Zeng, Yuxuan Zhao, Tielin Zhang, Dongcheng Zhao, Feifei Zhao, and Enmeng Lu. A Brain-Inspired Model of Theory of Mind. Frontiers in Neurorobotics (SCI-Q3, IF 2.6), Aug 28, 2020.[20] Tielin Zhang, Yi Zeng, Ruihan Pan, Mengting Shi, Enmeng Lu. Brain-Inspired Active Learning Architecture for Procedural Knowledge Understanding Based on Human-Robot Interaction. Cognitive Computation (SCI-Q1, IF 5.4), July 3, 2020.[19] Tielin Zhang, Yang Yang, Yi Zeng, Yuxuan Zhao. Cognitive Template-clustering Improved LineMod for Efficient Multi-object Pose Estimation. Cognitive Computation (SCI-Q1, IF 5.4), 2020.[18] Guoyu Zuo, Tingting Pan, Tielin Zhang. SOAR Improved Artificial Neural Network for Multistep Decision-Making Tasks. Cognitive Computation (SCI-Q1, IF 5.4), 13:612-625, Feb 5, 2020.[17] Mengting Shi#, Tielin Zhang#, Yi Zeng. A Curiosity-Based Learning Method for Spiking Neural Networks. Frontiers in Computational Neuroscience (SCI-Q2, IF 2.3), Feb 07, 2020, 14:7.2018:[16] Tielin Zhang, Yi Zeng, Dongcheng Zhao, Bo Xu. Brain-inspired Balanced Tuning for Spiking Neural Networks. The 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, CCF-A), July 13-19, 2018, Stockholm, Sweden. [Recommended][15] Tielin Zhang, Yi Zeng, Dongcheng Zhao, Mengting Shi. A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks, Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018, CCF-A), February 2-7, 2018, New Orleans, Louisiana, USA. [Recommended][14] Dor Mizrahi, Ilan Laufer, Inon Zuckerman, Tielin Zhang. The Effect of Culture and Social Orientation on Player's Performances in Tacit Coordination Games, International Conference on Brain Informatics(BI 2018), Springer, Cham, 2018: 437-447.2017:[13] Tielin Zhang, Yi Zeng, Bo Xu. A computational approach towards the microscale mouse brain connectome from the mesoscale. Journal of Integrative Neuroscience (SCI-Q4, IF 2.1), Mar 3, 2017, 16(3): 291-306.[12] Yi Zeng#, Tielin Zhang#, Bo Xu. Improving multi-layer spiking neural networks by incorporating braininspired rules. Science China-Information Sciences (SCI-Q2, IF 4.3), 2017, 60(5): 052201:01-12, doi: 10.1007/s11432-016-0439-4. [Recommended][11] Feifei Zhao, Tielin Zhang(Co-first), Yi Zeng and Bo Xu. Towards a Brain-Inspired Developmental Neural Network by Adaptive Synaptic Pruning. The 24th international Conference on Neural Information Processing (ICONIP 2017, CCF-C), November 14-18, Guangzhou, China, 2017.2016:[10] Xin Liu, Yi Zeng, Tielin Zhang, Bo Xu. Parallel Brain Simulator: A Multi-scale and Parallel Brain-inspired Neural Network Modeling and Simulation Platform. Cognitive Computation (SCI-Q1, IF 5.4), Springer, 2016.[9] Tielin Zhang, Yi Zeng, and Bo Xu. HCNN: A Neural Network Model for Combining Local and Global Features towards Human-like Classification. International Journal of Pattern Recognition and Artificial Intelligence (SCI-Q4, IF 1.3), 30(1), 1655004:01-19, 2016.[8] Tielin Zhang, Yi Zeng, Dongcheng Zhao, Liwei Wang, Yuxuan Zhao, Bo Xu. HMSNN: Hippocampus inspired Memory Spiking Neural Network. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016, CCF-C), Budapest, Hungary, October 9-12, 2016. [Recommended]2015:[7] Tielin Zhang, Yi Zeng and Bo Xu. Biological Neural Network Structure and Spike Activity Prediction based on Multi-neuron Spike Train Data. International Journal of Intelligence Science, 5(2), 102-111, 2015.2014:[6] Yi Zeng, Dongsheng Wang, Tielin Zhang and Bo Xu. Linked Neuron Data (LND): A Platform for Integrating and Semantically Linking Neuroscience Data and Knowledge. Frontiers in Neuroinformatics. Conference Abstract: The 7th Neuroinformatics Congress (Neuroinformatics 2014), Leiden, the Netherlands, August 25-27, 2014.[5] Yi Zeng, Tielin Zhang, and Hongwei Hao. Active Recommendation of Tourist Attractions based on Visitors Interests and Semantic Relatedness. Proceedings of the 2014 International Conference on Active Media Technology (AMT 2014), Lecture Notes in Computer Science 8610, 263-273, Springer, Warsaw, Poland, August 11-14, 2014.[4] Yi Zeng#, Tielin Zhang#, Bo Xu. Neural Pathway Prediction based on Multi-neuron Spike Train Data. The Twenty-Third Annual Computational Neuroscience Meeting (CNS 2014), Québec City, Canada, July 26-31, 2014, BMC Neuroscience, 15(Suppl 1): P6, 2014.[3] Tielin Zhang, Yi Zeng, Bo Xu. Neural Spike Prediction based on Spreading Activation. The Twenty-Third Annual Computational Neuroscience Meeting (CNS 2014), Québec City, Canada, July 26-31, 2014, BMC Neuroscience, 15(Suppl 1): P7, 2014.2013:[2] Yi Zeng, Dongsheng Wang, Tielin Zhang, Hao Wang, Hongwei Hao, Bo Xu. CASIA-KB: A Multi-source Chinese Semantic Knowledge Base Built from Structured and Unstructured Web Data. Proceedings of the 3rd Joint International Semantic Technology Conference (JIST 2013), Lecture Notes in Computer Science, 8388, 75–88, Springer, Seoul, Korea, November 28-30, 2013.[1] Yi Zeng, Dongsheng Wang, Tielin Zhang, Hao Wang, Hongwei Hao. Linking Entities in Short Texts based on a Chinese Semantic Knowledge Base. Proceedings of the 2nd Conference on Natural Language Processing and Chinese Computing (NLP&CC 2013), Communications in Computer and Information Science, 400, 266-276, Chongqing, China, November 15-19, 2013.All citations: 369, H-index:15, 2022-11-21.
科研活动
科研项目
（ 1 ）&nbsp基于时空信息融合的多任务脉冲神经网络研究, 负责人, 国家任务, 2019-01--2021-12（ 2 ）&nbsp类脑智能模型安全研究, 负责人, 国家任务, 2020-06--2023-05（ 3 ）&nbsp类脑决策博弈模型, 负责人, 中国科学院计划, 2020-07--2024-12（ 4 ）&nbsp基于生物可塑性规则启发的多任务脉冲神经网络学习方法研究, 负责人, 地方任务, 2019-01--2022-12（ 5 ）&nbsp类脑学习与决策的认知计算模型, 参与, 中国科学院计划, 2018-01--2022-12（ 6 ）&nbsp类脑计算与认知系统核心技术研究, 参与, 地方任务, 2018-08--2020-07（ 7 ）&nbsp类脑感知与决策的演化, 参与, 中国科学院计划, 2017-01--2017-12（ 8 ）&nbsp类脑认知功能计算模型, 参与, 中国科学院计划, 2015-07--2017-06（ 9 ）&nbsp意识与麻醉的类脑认知, 参与, 企业委托, 2018-01--2019-12（ 10 ）&nbsp超脑网络系统原型, 参与, 企业委托, 2018-01--2020-12（ 11 ）&nbsp基于脉冲神经网络算法研究领域的学术研究资助, 参与, 企业委托, 2018-10--2020-10（ 12 ）&nbsp基于物理启发式学习算法的非线性动力系统建模技术, 负责人, 地方任务, 2022-10--2024-12（ 13 ）&nbsp青年创新促进会专项, 负责人, 中国科学院计划, 2022-01--2025-12
合作情况
与上海神经所、上海脑智卓越中心、临港实验室等多个团队展开广泛的合作，如蒲慕明组、李澄宇组、顾勇组、徐宁龙组、杜久林组、穆宇组、赵郑拓组等。
指导过的学生或实习生
博士生
赵烜乐（2022，SNN）王岩松（2022，脑模拟）贾顺程（2020，SNN）李曦云（2020，SNN）夏万年（2020，人机融合）张笃振（2019，SNN）程翔（2018，SNN）吴浩然（2018，人机融合）
硕士生
姚王梓（2023，SNN）王庆宇（2022，SNN）宋昱（2022，SNN）史梦婷（2020，SNN，毕业去向：华为）
实习生
王翊 （吉林大学，2022，在线实习）韩轩（北京工业大学，2022，结束）郑寒璐 （北京邮电大学，2022，结束）左睿辰 （北京理工大学，2021，结束）马国庆 （山东大学，2021，结束）王怀瑾 （北京邮电大学，2019，结束）汪宏毅 （北京大学，2019，结束）唐李锴 （清华大学，2019，结束）张悦 （北京大学，2019，结束）张瑞宣 （北京大学，2019，结束）杨洋 （北京大学，2019，结束）王超明 （北京交通大学，2019，结束）王立伟 （北京大学，2018，结束）
2013 中国科学院大学，网络信息中心.