我的主要研究领域为类脑认知智能，研究目标旨在构建脑启发的脉冲神经网络，揭示大脑结构和功能的发育和演化机理，实现多脑区、多认知功能的自组织协同，探索动态环境下的在线学习、多任务连续学习、复杂决策，并将其应用于机器人、人机交互等多智能体复杂社会决策场景。

具体的研究方向包括：

1、类脑脉冲神经网络：多尺度生物可塑性协同的类脑脉冲神经网络、类脑发育与自然演化脉冲神经网络。

2、社会认知与道德决策：类脑心理揣测脉冲神经网络、脑与心智启发的道德决策脉冲神经网络。

   

081104-模式识别与智能系统

多尺度可塑性启发的类脑脉冲神经网络，类脑演化与发育脉冲神经网络，多任务连续学习与决策，自然启发的社会智能

2014-09--2019-06   中国科学院自动化研究所   博士学位
2010-09--2014-06   东北大学   学士学位

博士研究生

博士学位

   

2022-04~现在, 中国科学院自动化研究所, 副研究员
2019-07~2022-04,中国科学院自动化研究所, 助理研究员

2022-12-16-今,中国人工智能学会心智计算专业委员会, 副秘书长

系统与计算神经科学（助教）

   

（ 1 ） 基于全局反馈以及局部突触可塑的脉冲神经网络优化方法, 发明专利, 2020, 第 3 作者, 专利号: CN112085198A

（ 2 ） 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, 发明专利, 2020, 第 1 作者, 专利号: CN110766138A

（ 3 ） 基于自主决策脉冲神经网络的响应动作确定方法及系统, 发明专利, 2019, 第 1 作者, 专利号: CN109919305A

（ 4 ） 基于多脑区协同计算的人类动作意图识别训练方法, 发明专利, 2018, 第 4 作者, 专利号: CN108304767A

（ 5 ） 基于多模态融合的多脑区协同自主决策方法, 发明专利, 2018, 第 1 作者, 专利号: CN108197698A

（ 6 ） 基于视觉恐惧反应脑机制的应急避障方法, 专利授权, 2017, 第 1 作者, 专利号: CN106815550A

（ 7 ） 复杂环境下无人机自动障碍物检测和避障方法, 专利授权, 2017, 第 2 作者, 专利号: CN106708084A

（ 8 ） 运动检测方法及躲避和跟踪运动目标的方法, 专利授权, 2017, 第 3 作者, 专利号: CN106651921A

   

[1] Wenxuan Pan, Feifei Zhao, Bing Han, Yiting Dong, Yi Zeng. Emergence of brain-inspired small-world spiking neural network through neuroevolution. ISCIENCE. 2024, 27(2): http://dx.doi.org/10.1016/j.isci.2024.108845.
[2] 赵卓雅, 赵菲菲, 赵宇轩, 曾毅, 孙胤乾. A brain-inspired theory of mind spiking neural network improves multi-agent cooperation and competition. Patterns[J]. 2023, https://www.cell.com/patterns/fulltext/S2666-3899(23)00126-5.
[3] Yi Zeng, Dongcheng Zhao, Feifei Zhao, Guobin Shen, Yiting Dong, Enmeng Lu, Qian Zhang, Yinqian Sun, Qian Liang, Yuxuan Zhao, Zhuoya Zhao, Hongjian Fang, Yuwei Wang, Yang Li, Xin Liu, Chengcheng Du, Qingqun Kong, Zizhe Ruan, Weida Bi. BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation. PATTERNS. 2023, 4(8): http://dx.doi.org/10.1016/j.patter.2023.100789.
[4] Zhao, Zhuoya, Lu, Enmeng, Zhao, Feifei, Zeng, Yi, Zhao, Yuxuan. A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents. FRONTIERS IN NEUROSCIENCE[J]. 2022, 16: http://dx.doi.org/10.3389/fnins.2022.753900.
[5] Feifei Zhao, Yi Zeng, Bing Han, Hongjian Fang, Zhuoya Zhao. Nature-inspired self-organizing collision avoidance for drone swarm based on reward-modulated spiking neural network. PATTERNS[J]. 2022, 3(11): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676561/.
[6] 曾毅, 张倩, 赵菲菲, 赵东城, 李金东, 毕韦达. 从认知脑的计算模拟到类脑人工智能. 人工智能[J]. 2022, 28-40, [7] Fang, Hongjian, Zeng, Yi, Zhao, Feifei. Brain Inspired Sequences Production by Spiking Neural Networks With Reward-Modulated STDP. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE[J]. 2021, 15: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921721/.
[8] Zhao, Feifei, Zeng,Yi. Dynamically Optimizing Network Structure Based on Synaptic Pruning Mechanism in the Brain. Frontiers in System Neuroscience[J]. 2021, https://www.frontiersin.org/articles/10.3389/fnsys.2021.620558/full.
[9] Zhao Feifei, Zeng, Yi, Bai, Jun. Toward a Brain-Inspired Developmental Neural Network Based on Dendritic Spine Dynamics. Neural Computation. MIT Press[J]. 2021, [10] Zeng, Yi, Zhao, Yuxuan, Zhang, Tielin, Zhao, Dongcheng, Zhao, Feifei, Lu, Enmeng. A Brain-Inspired Model of Theory of Mind. FRONTIERS IN NEUROROBOTICS[J]. 2020, 14: https://doaj.org/article/eb3e2c8e57514e6fa56a1fa903365cb0.
[11] Zhao, Feifei, Zeng, Yi, Guo, Aike, Su, Haifeng, Xu, Bo. A neural algorithm for Drosophila linear and nonlinear decision-making. SCIENTIFIC REPORTS[J]. 2020, 10(1): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596070/.
[12] Zhao, Dongcheng, Zeng, Yi, Zhang, Tielin, Shi, Mengting, Zhao, Feifei. GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE[J]. 2020, 14: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689090/.
[13] Zhao, Feifei, Kong, Qingqun, Zeng, Yi, Xu, Bo. A Brain-Inspired Visual Fear Responses Model for UAV Emergent Obstacle Dodging. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS[J]. 2020, 12(1): 124-132, http://dx.doi.org/10.1109/TCDS.2019.2939024.
[14] Bai, Jun, Zeng, Yi, Zhao, Yuxuan, Zhao, Feifei, IEEE. Training a V1 Like Layer Using Gabor Filters in Convolutional Neural Networks. 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)null. 2019, [15] Zhao, Feifei, Zeng, Yi, Xu, Bo. A Brain-Inspired Decision-Making Spiking Neural Network and Its Application in Unmanned Aerial Vehicle. FRONTIERS IN NEUROROBOTICS[J]. 2018, 12(12): http://ir.ia.ac.cn/handle/173211/23363.
[16] Zhao, Feifei, Zeng, Yi, Wang, Guixiang, Bai, Jun, Xu, Bo. A Brain-Inspired Decision Making Model Based on Top-Down Biasing of Prefrontal Cortex to Basal Ganglia and Its Application in Autonomous UAV Explorations. COGNITIVE COMPUTATION[J]. 2018, 10(2): 296-306, http://ir.ia.ac.cn/handle/173211/23556.
[17] Zhao Feifei, Zhang Tielin, Xu Bo, Zeng,Yi. Towards a Brain-inspired Developmental Neural Network by Adaptive Synaptic Pruning. 2017, http://ir.ia.ac.cn/handle/173211/23557.
[18] Zeng Yi, Zhao Feifei, Wang Guixiang, Zhang Lingyu, Xu Bo, Ascoli GA, Hawrylycz M, Ali H, Khazanchi D, Shi Y. Brain-Inspired Obstacle Detection Based on the Biological Visual Pathway. BRAININFORMATICSANDHEALTHnull. 2016, 9919: 355-364, 

   

（ 1 ） 基于自主演化的类脑决策脉冲神经网络模型研究, 负责人, 国家任务, 2022-01--2024-12