基本信息
曾毅
中国科学院自动化研究所 研究员
中国科学院大学 岗位教授 博士生导师
电子邮件：yi.zeng@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
个人主页：http://bii.ia.ac.cn/~yizeng/
部门/实验室：类脑智能研究中心
研究领域实现并超越人类水平的智能是人工智能研究的终极目标。世界上除了人脑以外，目前没有任何一个智能系统能够高度协同多模态感知、决策、推理、预测、语言、动作等认知能力，具有高度自适应性、自主学习能力，甚至是自我意识，并稳定工作至少几十年。因此，研究脑信息处理原理，构建类脑智能计算模型，最终应用于人工智能系统研发，是实现人类水平人工智能，最终超越人类智能的重要途径。与此同时，我们要充分关注人工智能风险、安全与伦理，确保类脑人工智能的研究向对人类及社会有益的方向发展。

我的主要研究领域围绕类脑智能研究展开。主要涉及：
(1) 类脑认知计算模型: 类脑脉冲神经网络、类脑人工神经网络、类脑自主学习理论与算法，并将上述研究成果应用于类脑信息处理、类脑智能机器人的研究中。
(2) 人工智能伦理与治理：研究不同人工智能模型存在的风险、安全、伦理问题，并通过算法落地的形式研究低风险、高度安全、具有道德与伦理的有益人工智能模型。

招生信息
招生专业081104-模式识别与智能系统

招生方向类脑智能


教育背景
学历博士研究生学历
学位工学博士学位

工作经历现任中国科学院自动化研究所 研究员、类脑智能研究中心副主任
中国科学院大学 岗位教授 博士生导师
中国科学院脑科学与智能技术研究中心青年骨干

社会兼职2019-02-15-今,科技部新一代人工智能治理委员会, 委员
2018-10-14-2019-10-14,世界经济论坛全球未来理事会, 价值、伦理与创新委员会委员
2016-08-30-今,Cognitive Systems Research (Elsevier), Associate Editor
2016-01-30-今,中国指挥与控制学会认知与行为专委会, 常务委员


教授课程人工智能哲学与伦理
系统与计算神经科学
类脑智能导论


出版信息
发表论文（1）A Fast Contour Detection Model Inspired by Biological Mechanisms in Primary Vision System,Frontiers in Computational Neuroscience,2018,通讯作者
（2）A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks,The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18),2018,通讯作者
（3）Brain-inspired Balanced Tuning for Spiking Neural Networks,The 27th International Joint Conference on Artificial Intelligence (IJCAI-18),2018,通讯作者
（4）Efficient Coding Matters in the Organization of the Early Visual System,Neural Networks,2018,通讯作者
（5）A Basal Ganglia Network Centric Reinforcement Learning Model and Its Application in Unmanned Aerial Vehicle,IEEE Transactions on Cognitive and Developmental Systems,2018,第1作者
（6）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,2018,通讯作者
（7）Towards Robot Self-consciousness (II): Brain-inspired Robot Bodily Self Model for Self-Recognition,Cognitive Computation,2018,第1作者
（8）A Computational Approach towards the Microscale Mouse Brain Connectome from the Mesoscale,Journal of Integrative Neuroscience,2017,通讯作者
（9）Improving Multi-layer Spiking Neural Networks by Incorporating Brain-inspired Rules.,SCIENCE CHINA Information Sciences,2017,第1作者
（10）Towards a Brain-inspired Developmental Neural Network by Adaptive Synaptic Pruning,Proceedings of the 24th International Conference on Neural Information Processing (ICONIP 2017),2017,通讯作者
（11）A Quaternionic Rate-based Synaptic Learning Rule Derived from Spike-Timing Dependent Plasticity,Lecture Notes in Computer Science,2017,通讯作者
（12）HCNN: A Neural Network Model for Combining Local and Global Features towards Human-like Classification,International Journal of Pattern Recognition and Artificial Intelligence,2016,通讯作者
（13）类脑智能研究的回顾与展望,Retrospect and Outlook of Brain-inspired Intelligence Research,计算机学报,2016,第1作者
（14）类脑智能研究现状与发展思考,Research Status and Developments of Brain-inspired Intelligence,中国科学院院刊,2016,第3作者
（15）A Spiking Neural Network Based Autonomous Reinforcement Learning Model and Its Application in Decision Making,Lecture Notes in Computer Science,2016,第2作者
（16）Towards Robot Self-Consciousness (I): Brain-inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-Recognition,Lecture Notes in Computer Science,2016,第1作者
（17）Parallel Brain Simulator: A Multi-scale and Parallel Brain-inspired Neural Network Modeling and Simulation Platform,Cognitive Computation,2016,通讯作者
（18）Biological Neural Network Structure and Spike Activity Prediction based on Multi-neuron Spike Train Data,International Journal of Intelligence Science,2015,第2作者
（19）HEVS: A Hierarchical Computational Model for Early Stages of the Visual System,Proceedings of the 2015 International Joint Conference on Neural Networks (IJCNN 2015),2015,第3作者
（20）Biologically Inspired Deep Stereo Model,Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP 2015),2015,第2作者
（21）Neural Spike Prediction based on Spreading Activation,BMC Neuroscience, 15(Suppl 1): P7,2014,第2作者
（22）Neural Pathway Prediction based on Multi-neuron Spike Train Data,BMC Neuroscience, 15(Suppl 1): P6,2014,第1作者
（23）Active Recommendation of Tourist Attractions based on Visitors Interests and Semantic Relatedness,Lecture Notes in Computer Science,2014,第1作者
（24）Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories,Lecture Notes in Artificial Intelligence,2014,第1作者
（25）Automatic Recovery of Z-Jumps for Neuronal Morphology Reconstruction,Frontiers in Neuroinformatics. Conference Abstract,2014,第1作者
（26）Linked Neuron Data (LND): A Platform for Integrating and Semantically Linking Neuroscience Data and Knowledge,Frontiers in Neuroinformatics. Conference Abstract,2014,第1作者
（27）Linking Entities in Short Texts based on a Chinese Semantic Knowledge Base,Communications in Computer and Information Science,2013,第1作者
（28）Entity Conceptualization and Understanding based on Web-scale Knowledge Bases,Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2013),2013,第1作者
（29）CASIA-KB: A Multi-source Chinese Semantic Knowledge Base Built from Structured and Unstructured Web Data,Lecture Notes in Computer Science,2013,第1作者
（30）Statistical and Structural Analysis of Web-based Collaborative Knowledge Bases Generated from Wiki Encyclopedia,Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence,2012,第1作者