Overview

I am generally interested in Brain-inspired Artificial Intelligence, Brain-inspired Cognitive Robotics, Ethics and Governance of Artificial Intelligence. My long-term goal is to develop comprehensive theories and systems to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living becomings with or beyond human-level intelligence for future human-AI symbiotic society.

My current research interests focus on the following directions:

Brain-inspired Cognitive Computation Models.
Brain-inspired Neural Networks.
Brain-inspired Cognitive and Neural Robotics.
Cognitive Brain Modeling and Simulation.
Philosophy, Ethics and Governance of Artificial Intelligence.
Artificial Intelligence for Sustainable Development Goals.

The goal for my research on Brain-inspired Intelligence is to propose and implement a Cognitive Computation Model for Brain-inspired Artificial General Intelligence, which is the "brain" for future intelligent living machines. Please visit my Publication page for more details.

Brain-inspired Cognitive Intelligence Engine (BrainCog) is a brain-inspired neural network based platform for realizing Brain-inspired Artificial Intelligence, and simulating the cognitive brains of different animal species at multiple scales. The ultimate goal and long term efforts of BrainCog is to provide a comprehensive theory and systems to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living machines in human-machine society.

BORN is an Artificial Intelligence Engine based on Brain-inspired Spiking Neural Networks. The ultimate vision of BORN is to achieve living Artificial General Intelligence, as a new type of evolutionary becoming, and as a moral member of the future symbiotic society. The near term goal of BORN is a self enabled learning AI powered by spiking neural networks that can coordinate various cognitive functions in a self organized way to solve complex problems. BORN is powered by BrainCog, the Brain-inspired Cognitive Intelligence Engine.

Linked Brain Data (LBD) is an effort for extracting, integrating, linking and analyzing Brain data and knowledge from multiple scale and multiple data sources and support comprehensive understandings of the brain. LBD is proud to present the association graph among various cognitive functions, brain diseases and their relationships to brain building blocks at multiple scales. This association graph provide inspirations for future Neuroscience and Brain-inspired Intelligence research.

Recent Projects

Brain-inspired Cognitive Intelligence Engine (BrainCog) (2013.6-) [Principle Investigator]
Linked Brain Data : A large-scale, multi-modal brain knowledge base (2013.7 -) [Principle Investigator]
Harmonious Artificial Intelligence Principles [2018.7-] [Principle Investigator]
Linking Artificial Intelligence Principles (2018.10-) [Principle Investigator]
Artificial Intelligence Governance Online (2020.7-) [Principle Investigator]
AI for Sustainable Development Goals Think Tank (2020.6-) [Founder and Director]

Teaching

Introduction to Brain-inspired Intelligence [2017-2021], University of Chinese Academy of Sciences
System and Computational Neuroscience [2018], University of Chinese Academy of Sciences
Philosophy and Ethics of Artificial Intelligence [2018-2023], University of Chinese Academy of Sciences
Ethics and Governance of Artificial Intelligence [2023], Shwarzman Scholars, Tsinghua University

What's New!

Being an expert for the Ad Hoc Expert Group on AI Ethics, United Nations Education, Science and Culture Organization (UNESCO), I am proud to contribute to the Recommendation of AI Ethics by UNESCO. It needs the world to collaborate and coordinate to shape a commonly accepted AI Ethics framework for the whole humanity and our share future.
If you are looking for ethical guidelines of Artificial Intelligence that I am involved: Beijing AI Principles, AI for Children: Beijing Principles, Governance Principles for the New Generation Artificial Intelligence, Recommendation of AI Ethics by UNESCO, Harmonious Artificial Intelligence Principles
An interview by National Science Review on "Promoting Good Governance of Artificial Intelligence", in which I talked recent progress of AI Ethics and Governance in China, including efforts that I am mainly involved.
My Recent talk on "Building Ethical Brain-inspired AI for Harmonious Human-AI Symbiotic Society".
My Recent talk on "Brain-inspired Artificial Intelligence-Towards Brain-inspired Conscious Living Becomings".
Linking Artificial Intelligence Principles platform is aimed at linking various Artificial Intelligence principles world wide from different countries, organizations, institutions, etc. to create a joint future for Human-AI society.
Harmonious Artificial Intelligence Principles is designed not only for AI, but also for human to interact with future AI, and our shared common future.
I am honored to chair the first course on Philosophy and Ethics of Artificial Intelligence at School of Artificial Intelligence, University of Chinese Academy of Sciences.
Brain-inspired Cognitive Intelligence Engine (BrainCog) and related efforts was reported in Artificial Intelligence in China series in the China News program on the International Channel of China Central Television.
Some of my long term quest for Brain-inspired Intelligence is briefly discussed in an interview by Holland Innovations in an article titled "Brain-inspired Artificial Intelligence in China".
An interview by National Science Review on "Research and Development of Artificial Intelligence in China", in which I talked about my vision on Brain-inspired Intelligence and progresses.
Towards Robot Self-consciousness (II): Brain-inspired Robot Bodily Self Model for Self-Recognition , published on Cognitive Computation (Springer), with an online video.
BORN is released. It is a brain-inspired spiking neural network based artificial intelligence engine towards human-level AI.
CASIA Brain Simulation System Check out our recent efforts on multi-scale brain simulation [Cat V1 Neural Network behavior Simulation on Orientation Selectivity, Mouse Hippocampus Network Simulation].
Linked Brain Data (LBD) Platform has been released. Linked Brain Data (LBD) is an effort for extracting and linking Brain and Neuroscience data and knowledge from multiple scale and multiple data sources together. The LBD platform provides services for Brain and Neuroscience knowledge extraction, structured data representation, integration, visualization, analysis, semantic search and reasoning over the integrated Brain and Neuroscience data.

Research Interests

I am generally interested in Brain-inspired Artificial Intelligence, Brain-inspired Cognitive Robotics, Ethics and Governance of Artificial Intelligence. My current research interests focus on the following directions:

Brain-inspired Cognitive Computation Models.
Brain-inspired Neural Networks.
Brain-inspired Cognitive and Neural Robotics.
Cognitive Brain Modeling and Simulation.
Philosophy, Ethics and Governance of Artificial Intelligence.

Selected Projects

Brain-inspired Cognitive Intelligence Engine (BrainCog) : (2013.6-) [Principle Investigator] is a brain-inspired neural network based platform for simulating the cognitive brains of different animal species at multiple scales and realizing brain-inspired Artificial Intelligence. The long term goal of BrainCog is to provide a comprehensive theory and system to decode the mechanisms and principles of human intelligence and its evolution, and develop artificial brains for brain-inspired conscious living machines in future human-machine society.
Linking Artificial Intelligence Principles (LAIP) : (2018.10-) [Principle Investigator] Various Artificial Intelligence Principles are designed with different considerations, and none of them can be perfect and complete for every scenario. Linking Artificial Intelligence Principles (LAIP) is an initiative and platform for synthesizing, linking, and analyzing various Artificial Intelligence Principles World Wide, from different research institutes, non-profit organizations, non-governmental organizations, companies, etc. The efforts aim at understanding in which degree do these different AI Principles proposals share common values, differ and complete each other.
BORN: an Artificial Intelligence Engine based on Brain-inspired Spiking Neural Networks. The ultimate vision of BORN is to achieve living Artificial General Intelligence, as a new type of evolutionary becoming, and as a moral member of the future symbiotic society. The near term goal of BORN is a self enabled learning AI powered by spiking neural networks that can coordinate various cognitive functions in a self organized way to solve complex problems. BORN is powered by BrainCog, the Brain-inspired Cognitive Intelligence Engine.
Linked Brain Data (LBD) : A large-scale, multi-modal brain knowledge base (2013.7 -) [Principle Investigator] This project is an effort for extracting and linking Neuroscience data and knowledge from multiple scale and multiple data sources together. The LBD platform provides services for neuroscience knowledge extraction, structured neuron data representation, neuron data integration, visualization, analysis, semantic search (through SPARQL queries) and reasoning over the integrated Neuron data.
Interests-based Bidirectional Fusion of Web Knowledge Retrieval and Reasoning : (2012.1-2014.12) [Principle Investigator] This project aims at unifying knowledge retrieval and reasoning by human interests, and its application in various intelligent Web applications. [Supported by The Young Scientists Fund of the National Natural Science Foundation of China (NSFC)]
The Large Knowledge Collider (LarKC) : (2008.4-2011.9) This project is a European funded 7th Framework Project. My research in LarKC was related to: (1) Retrieval and Reasoning based on vague or incomplete queries. (2) Unifying Search and Reasoning using various strategies such as the human interests centric approach, and multi-scale knowledge processing approach, etc.

Selected Publications

Brain-inspired Artificial Intelligence

Wenxuan Pan, Feifei Zhao, Bing Han, Yiting Dong, Yi Zeng. Emergence of brain-inspired small-world spiking neural network through neuroevolution. iScience, Cell Press, 2024.

Qian Zhang, Han Lu, jihang Wang, Taoyi Yang, Weida Bi, Yi Zeng, Buwei Yu. Hierarchical rhythmic propagation of corticothalamic interactions for consciousness: A computational study. Computers in Biology and Medicine, 2023.

Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Jindong Li, Kang Sun, Yi Zeng. Astrocyte-Enabled Advancements in Spiking Neural Networks for Large Language Modeling. Arxiv, 2023.

Yuxuan Zhao, Enmeng Lu, Yi Zeng. Brain-inspired bodily self-perception model for robot rubber hand illusion. Patterns, Cell Press, 2023.

Guobin Shen, Dongcheng Zhao, Yiting Dong, Yi Zeng. Brain-inspired neural circuit evolution for spiking neural networks. Proceedings of the National Academy of Sciences (PNAS), 2023.
Wenxuan Pan, Feifei Zhao, Yi Zeng, Bing Han. Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks. Scientific Reports, Nature Press, 2023.
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, Cell Press, 2023.
Yiting Dong, Dongcheng Zhao, Yang Li, Yi Zeng. An unsupervised STDP-based spiking neural network inspired by biologically plausible learning rules and connections. Neural Networks, 165:799-808, 2023.
Jindong Li, Guobin Shen, Dongcheng Zhao, Qian Zhang, Yi Zeng. FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks With Efficient DSP and Memory Optimization. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2023.
Zhuoya Zhao, Feifei Zhao, Yuxuan Zhao, Yi Zeng, Yinqian Sun. A brain-inspired theory of mind spiking neural network improves multi-agent cooperation and competition, Patterns, Cell Press, 2023.
Guobin Shen, Dongcheng Zhao, Yi Zeng. EventMix: An efficient data augmentation strategy for event-based learning, Information Sciences, Volume 644, 119170, October 2023.
Jinyu Fan, Yi Zeng. Challenging Deep Learning Models with Image Distortion Based on the Abutting Grating Illusion, Patterns, Cell Press, 2023.
Yang Li, Yiting Dong, Dongcheng Zhao, Yi Zeng. N-Omniglot: a Large-scale Neuromorphic Dataset for Spatio-temporal Sparse Few-shot Learning. Scientific Data, 9(746), Nature Publishing Group, 2022.
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, Cell Press, 2022.
Hui Feng, Yi Zeng. A Brain-Inspired Robot Pain Model Based on a Spiking Neural Network, Frontiers in Neurorobotics, 2022.
Yinqian Sun, Yi Zeng, and Yang Li. Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization, Frontiers in Neuroscience, 2022.
Yuxuan Zhao, Yi Zeng. A Brain-inspired Intention Prediction Model and Its Applications to Humanoid Robot, Frontiers in Neuroscience, 16:1009237, 2022.
Yang Li, Dongcheng Zhao, and Yi Zeng. BSNN: Towards Faster and Better Conversion of Artificial Neural Networks to Spiking Neural Networks with Bistable Neurons, Frontiers in Neuroscience, 2022.
Hui Feng, Yi Zeng, and Enmeng Lu. Brain-Inspired Affective Empathy Computational Model and Its Application on Altruistic Rescue Task, Frontiers in Computational Neuroscience, 2022.
Dongcheng Zhao, Yi Zeng, Yang Li, Jihang Wang, Qian Zhang. Spiking Capsnet: A Spiking Neural Network With a Biologically Plausible Routing Rule Between Capsules, Information Sciences, 2022.
Dongcheng Zhao, Yi Zeng, Yang Li. BackEISNN: A Deep Spiking Neural Network with Adaptive Self-Feedback and Balanced Excitatory-Inhibitory Neurons, Neural Networks, Volume 154, 68-77, 2022.
Guobin Shen, Dongcheng Zhao, Yi Zeng. Backpropagation with biologically plausible spatiotemporal adjustment for training deep spiking neural networks. Patterns, Cell Press, 2022.
Zhuoya Zhao, Enmeng Lu, Feifei Zhao, Yi Zeng, and Yuxuan Zhao. A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents. Frontiers in Neuroscience, 2022.
Yang Li, Yi Zeng. Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes. Proceedings of the 31st International Joint Conferences on Artificial Intelligence (IJCAI-22), 2022.
Yuwei Wang, Yi Zeng. Multisensory Concept Learning Framework Based on Spiking Neural Networks. Frontiers in Systems Neuroscience, 16:845177, 2022.
Yuwei Wang, Yi Zeng. Statistical Analysis of Multisensory and Text-Derived Representations on Concept Learning. Frontiers in Computational Neuroscience, 16:861265, 2022.
Hongjian Fang, Yi Zeng. A Brain-Inspired Causal Reasoning Model Based on Spiking Neural Networks. 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021.
Yinqian Sun, Yi Zeng, Tielin Zhang. Quantum Superposition Inspired Spiking Neural Network. iScience, 24(8), 102880, Cell Press, 2021.
Yuxuan Zhao, Yi Zeng, Guang Qiao. Brain-Inspired Classical Conditioning Model. iScience, 24(1), 101980, Cell Press, 2021.
Yang Li, Yiting Dong, Dongcheng Zhao, Yi Zeng. N-Omniglot: a Large-scale Neuromorphic Dataset for Spatio-Temporal Sparse Few-shot Learning. Arxiv:2112.13230, 2021.
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, 7(43), AAAS, 2021.
Feifei Zhao, Yi Zeng, Jun Bai. Toward a Brain-Inspired Developmental Neural Network Based on Dendritic Spine Dynamics. Neural Computation, MIT Press, 2021.
Qian Liang, Yi Zeng. Stylistic Composition of Melodies based on a Brain-inspired Spiking Neural Network. Frontiers in Systems Neuroscience, 15:639484, 2021.
Feifei Zhao, Yi Zeng. Dynamically Optimizing Network Structure Based on Synaptic Pruning in the Brain. Frontiers in Systems Neuroscience, 15:620558, 2021.
Hongjian Fang, Yi Zeng, Feifei Zhao. Brain Inspired Sequences Production by Spiking Neural Networks With Reward-Modulated STDP. Frontiers in Computational Neuroscience, 15:612041, 2021.
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, 2020.
Yi Zeng, Yuxuan Zhao, Tielin Zhang, Dongcheng Zhao, Feifei Zhao, and Enmeng Lu. A Brain-Inspired Model of Theory of Mind. Frontiers in Neurorobotics, 2020.
Qian Liang, Yi Zeng, Bo Xu. Temporal-Sequential Learning with a Brain-Inspired Spiking Neural Network and Its Application to Musical Memory. Frontiers in Computational Neuroscience, 14:51, 2020.
Mengting Shi, Tielin Zhang, Yi Zeng. A Curiosity-Based Learning Method for Spiking Neural Networks. Frontiers in Computational Neuroscience, 2020.
Feifei Zhao, Qingqun Kong, Yi Zeng, Bo Xu. A Brain-inspired Visual Fear Responses Model for UAV Emergent Obstacle Dodging. IEEE Transactions on Cognitive and Developmental Systems, 12(1): 124-132, 2020.
Tielin Zhang, Yang Yang, Yi Zeng, Yuxuan Zhao. Cognitive Template-clustering Improved LineMod for Efficient Multi-object Pose Estimation. Cognitive Computation, 2020.
Yuwei Wang, Yi Zeng, Jianbo Tang and Bo Xu. Biological Neuron Coding Inspired Binary Word Embeddings. Cognitive Computation, Springer, 2019.
Jun Bai, Yi Zeng, Yuxuan Zhao and Feifei Zhao. Training a V1 Like Layer Using Gabor Filters in Convolutional Neural Networks. Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN 2019). Budapest, Hungary, July 14-19, 2019.
Dongcheng Zhao, Yi Zeng. Dynamic Fusion of Convolutional Features based on Spatial and Temporal Attention for Visual Tracking. Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN 2019). Budapest, Hungary, July 14-19, 2019.
Feifei Zhao, Yi Zeng, and Bo Xu. A Brain-inspired Decision-Making Spiking Neural Network and Its Application in Unmanned Aerial Vehicle. Frontiers in Neurorobotics, 2018.
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-18), Stockholm, Sweden, 2018.
Yi Zeng, Guixiang Wang, Bo Xu. A Basal Ganglia Network Centric Reinforcement Learning Model and Its Application in Unmanned Aerial Vehicle. IEEE Transactions on Cognitive and Developmental Systems, 10(2): 290-303, 2018.
Yi Zeng, Yuxuan Zhao, Jun Bai, Bo Xu. Towards Robot Self-consciousness (II): Brain-inspired Robot Bodily Self Model for Self-Recognition. Cognitive Computation, 10(2): 307-320, Springer, 2018.
Tielin Zhang, Yi Zeng, Dongcheng Zhao, Mengting Shi. A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), Lousiana, USA, 2018.
Yi Zeng, Tielin Zhang, Bo Xu. Improving Multi-layer Spiking Neural Networks by Incorporating Brain-inspired Rules. SCIENCE CHINA Information Sciences, 60(5): 052201, 2017.
Feifei Zhao, Tielin Zhang, Yi Zeng, Bo Xu. Towards a Brain-inspired Developmental Neural Network by Adaptive Synaptic Pruning. Proceedings of the 24th International Conference on Neural Information Processing (ICONIP 2017), 2017.
Guang Qiao, Hongyue Du, Yi Zeng. A Quaternionic Rate-based Synaptic Learning Rule Derived from Spike-Timing Dependent Plasticity. Lecture Notes in Computer Science, 10261, 457-465, 2017.
Xin Liu, Yi Zeng, Bo Xu. Parallel Brain Simulator: A Multi-scale and Parallel Brain-inspired Neural Network Modeling and Simulation Platform. Cognitive Computation, Volume 8, Issue 5, 967-981, Springer, 2016.
Yi Zeng, Yuxuan Zhao, Jun Bai. Towards Robot Self-Consciousness (I): Brain-inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-Recognition. Lecture Notes in Computer Science, 10023, 11-21, 2016.
Guixiang Wang, Yi Zeng, Bo Xu. A Spiking Neural Network Based Autonomous Reinforcement Learning Model and Its Application in Decision Making. Lecture Notes in Computer Science, 10023, 125-137, 2016.
Yi Zeng, Chenglin Liu, Tieniu Tan. Retrospect and Outlook of Brain-inspired Intelligence Research [in Chinese]. The Chinese Journal of Computers, Volume 39, Issue 1, 212-222, 2016.
Bo Xu, Chenglin Liu, Yi Zeng. Research Status and Developments of Brain-inspired Intelligence [in Chinese]. Bulletin of Chinese Academy of Sciences, Volume 31, Issue 7, 793-802, 2016.
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, Volume 30, Issue 1, 1655004, 2016.
Yi Zeng, Feifei Zhao, Guixiang Wang, Lingyu Zhang, Bo Xu. Brain-inspired Obstacle Detection based on the Biological Visual Pathway. Proceedings of the 2016 International Conference on Brain Informatics and Health, Lecture Notes in Artificial Intelligence 9919, Omaha, Nebraska, USA, 2016.
Yuwei Wang, Yi Zeng, Bo Xu. SHTM: A Neocortex-inspired Algorithm for One-shot Text Generation. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 898-903, IEEE Press, Budapest, Hungary, October 9-12, 2016.
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, 2301-2306, IEEE Press, Budapest, Hungary, October 9-12, 2016.
Xiaomei kang, Qingqun Kong, Yi Zeng, Bo Xu. A Fast Contour Detection Model Inspired by Biological Mechanisms in Primary Vision System. Frontiers in Computational Neuroscience, 2018.
Feifei Zhao, Yi Zeng, Guixiang Wang, Jun Bai, Bo Xu. 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, 10(2): 296-306, Springer, 2018.
Chaoming Wang, Yi Zeng. Network of Recurrent Neural Networks: Design for Emergence. Proceedings of the 25th International Conference on Neural Information Processing (ICONIP2018).
Qingqun Kong, Yi Zeng, Qiulei Dong. Biologically Inspired Deep Stereo Model. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP 2015), 3700-3704, Quebec City, Canada, 2015.

AI Ethics and Governance

Ethical Principles and Specifications

Principles on AI for Climate Actions, 2022. [Yi Zeng, as the lead author, with contributions from Cunqing Huangfu, Kang Sun, Yang Yu, Emma Ruttkamp-Bloem, Mark Findlay, Christoph Lütge, Helen Meng, etc.]
Ethical Norms for the New Generation Artificial Intelligence, 2021. [Yi Zeng as one of the authors and board members for national governance committee of new generation AI]
Recommendation of AI Ethics, UNESCO, 2021. [Yi Zeng as one of the members of the UNESCO Adhoc Expert Group on AI Ethics]
WHO Guidance on AI Ethics and Governance for Health, 2021 [Yi Zeng as one of the members for the WHO Expert Group on AI Ethics and Governance for Health]
Ethical considerations to guide the use of digital proximity tracking technologies for COVID-19 contact tracing, World Health Organization (WHO), 2020. [Yi Zeng as one of the members for the WHO Expert Group on AI Ethics and Governance for Health.
Governance Principles for the New Generation Artificial Intelligence, 2019. [Yi Zeng as one of the main authors and board members for the national governance committee of new generation AI]
AI for Children: Beijing Principles, 2020. [Yi Zeng, Kang Sun, Enmeng Lu as the authors and endorsed by the academic and industrial community]
Beijing AI Principles, 2019. [Yi Zeng as the lead author, with participation from Enmeng Lu, and endorsed by the academic and industrial community]
Harmonious Artificial Intelligence Principles, 2018. [Yi Zeng as the author]

Papers and Reports

Yi Zeng, Enmeng Lu, Kang Sun. Principles on symbiosis for natural life and living artificial intelligence. AI and Ethics, 2023.
Aorigele Bao, Yi Zeng, Enmeng Lu. Mitigating emotional risks in human-social robot interactions through virtual interactive environment indication. Humanities and Social Sciences Communications, Nature Press, 2023.
Yi Zeng. Deep Coordination among Development, Ethics, and Governance of Science and Technology. China Science Daily, March 22, 2022.
Yi Zeng, Kang Sun, Enmeng Lu. Declaration on the Ethics of Brain-Computer Interfaces and Augment Intelligence. AI and Ethics, Springer, 2021.
Yi Zeng. Global Cooperation on Artificial Intelligence is not a Zero-Sum Game.Guangming Daily, 2021.
Yi Zeng, Kang Sun, Enmeng Lu. Ethics and Governance Perspectives to Fight Against Catastrophic Risks: From COVID-19 to Long-term Safety Issues of Artificial General Intelligence. In: Data, AI Governance, and COVID-19: Medium and Long-term Perspectives for Asia, 2020 (This paper is originally published in Japanese in IPSJ Magazine, Vol. 61, No. 10, October 2020).
Seán S. ÓhÉigeartaigh, Jess Whittlestone, Yang Liu, Yi Zeng & Zhe Liu. Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and Governance. Philosophy & Technology, 2020.
Yi Zeng, Enmeng Lu, Kang Sun, Samuel Curtis. Facial Recognition and Public Health. Artificial Intelligence and Healthy Society Survey Series, Beijing Academy of Artificial Intelligence, 2020.
Yi Zeng. Artificial Intelligence: An Accelerator for United Nations Sustainable Development Goals. Guangming Daily, June 18th, 2020.
Yi Zeng, Kang Sun. Fighting COVID-19 with AI: efforts and lessons from China. Global Times, March 7th, 2020.
Yi Zeng, Enmeng Lu, Yinqian Sun, Ruochen Tian. Responsible Facial Recognition and Beyond. 2019.
Yi Zeng, Enmeng Lu, Cunqing Huangfu. Linking Artificial Intelligence Principles. The AAAI 2019 Safe Artificial Intelligence (AAAI SafeAI-2019) Workshop, January 27, 2019.

Computational Neuroscience and Neuroinformatics

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, 2021.
Tielin Zhang, Yi Zeng, Yue Zhang, Xinhe Zhang, Mengting Shi, Likai Tang, Duzhen Zhang, Bo Xu. Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks. Scientific Reports, 11: 7291, Nature Publishing Group, 2021.
Feifei Zhao, Yi Zeng, Aike Guo, Haifeng Su, Bo Xu. A Neural Algorithm for Drosophila Linear and Nonlinear Decision-making. Scientific Reports, 10: 18660, Nature Publishing Group, 2020.
Qian Zhang, Yi Zeng, Taoyi Yang. Computational Investigation of Contributions from Different Subtypes of Interneurons in Prefrontal Cortex for Information Maintenance. Scientific Reports, 10: 4671, Nature Publishing Group, 2020.
Cunqing Huangfu, Yi Zeng, Yuwei Wang. Creating Neuroscientific Knowledge Organization System Based on Word Representation and Agglomerative Clustering Algorithm. Frontiers in Neuroinformatics, 2020.
Hongyin Zhu, Yi Zeng, Dongsheng Wang, Cunqing Huangfu. Species Classification for Neuroscience Literature Based on Span of Interest Using Sequence-to-sequence Learning Model. Frontiers in Human Neuroscience. 2020.
Qingqun Kong, Jiuqi Han, Yi Zeng, Bo Xu. Efficient Coding Matters in the Organization of the Early Visual System. Neural Networks, Elsevier, 2018.
Xiaosha Wang, Yangwen Xu, Yuwei Wang, Yi Zeng, Jiacai Zhang, Zhenhua Ling, Yanchao Bi. Representational similarity analysis reveals task-dependent semantic influence of the visual word form area. Scientific Reports, 8(1): 3047, Nature Publishing Group, 2018.
Tielin Zhang, Yi Zeng, Bo Xu. A Computational Approach towards the Microscale Mouse Brain Connectome from the Mesoscale. Journal of Integrative Neuroscience, 16(3): 291-306, 2017.
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.
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.
Yi Zeng, Dongsheng Wang, Hongyin Zhu. User Interests Analysis and Its Application on the Linked Brain Data Platform. Proceedings of the 2016 International Conference on Brain Informatics and Health, Lecture Notes in Artificial Intelligence 9919, Omaha, Nebraska, USA, October 13-16, 2016.
Hongyin Zhu, Yi Zeng, Dongsheng Wang, Bo Xu. Brain Knowledge Graph Analysis Based on Complex Network Theory. Proceedings of the 2016 International Conference on Brain Informatics and Health, Lecture Notes in Artificial Intelligence 9919, Omaha, Nebraska, USA, October 13-16, 2016.
Hongyin Zhu, Yi Zeng, Dongsheng Wang, Bo Xu. Relation Inference and Type Identification Based on Brain Knowledge Graph. Proceedings of the 2016 International Conference on Brain Informatics and Health, Lecture Notes in Artificial Intelligence 9919, Omaha, Nebraska, USA, October 13-16, 2016.
Jiuqi Han, Qingqun Kong, Yi Zeng and Hongwei Hao. HEVS: A Hierarchical Computational Model for Early Stages of the Visual System. Proceedings of the 2015 International Joint Conference on Neural Networks (IJCNN 2015), 1-8, Killarney, Ireland, July 12-17, 2015.
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.
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.
Yi Zeng, Weida Bi, Yun Wang, Xuan Tang and Bo Xu. Automatic Recovery of Z-Jumps for Neuronal Morphology Reconstruction. Frontiers in Neuroinformatics. Conference Abstract: The 7th Neuroinformatics Congress (Neuroinformatics 2014), Leiden, the Netherlands, August 25-27, 2014.
Yi Zeng, Weida Bi, Xuan Tang, and Bo Xu. Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories. Proceedings of the 2014 International Conference on Brain Informatics and Health (BIH 2014), Lecture Notes in Artificial Intelligence 8609, 1-11, Springer, Warsaw, Poland, August 11-14, 2014.

Web Knowledge Representation, Retrieval and Reasoning

Hongyin Zhu, Yi Zeng, Yiping Yang. Research Topics Variation Analysis and Prediction Based on FARO and Neural Networks. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, IEEE Press, Budapest, Hungary, October 9-12, 2016.
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.
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.
Yi Zeng, Hongwei Hao, Bo Xu. Entity Conceptualization and Understanding based on Web-scale Knowledge Bases. Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2013), 3500-3504, Manchester, the United Kingdom, October 13-16, 2013.
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.
Yi Zeng, Hao Wang, Hongwei Hao, Bo Xu. 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 (WI 2012), Macau, China, December 4-7th, 2012.
Yi Zeng, Hongwei Hao, Ning Zhong, Xu Ren, Yan Wang. Ranking and Combining Social Network Data for Web Personalization. Proceedings of the International Workshop on Data-driven User Behavioral Modelling and Mining from Social Media, co-located with the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012), Hawaii, USA, October 29th, 2012.
Yi Zeng, Danica Damljanovic, Xu Ren, Yan Wang. Identification and Selection (In Chinese). In: Zhisheng Huang and Ning Zhong (Eds.), Scalable Semantic Data Processing: Platform, Technology and Application, Higher Education Press, 2012.
Yi Zeng, Ning Zhong, Xu Ren and Yan Wang. User Interests Driven Web Personalization Based on Multiple Social Networks. Proceedings of the 4th International Workshop on Web Intelligence & Communities, colocated with the 2012 World Wide Web Conference (WWW 2012), Lyon, France, April 16th, 2012.
Yi Zeng, Zhisheng Huang, Fenrong Liu, Xu Ren, Ning Zhong. Interest Logic and Its Application on the Web. Proceedings of the 5th International Conference on Knowledge Science, Engineering, and Management (KSEM 2011). Lecture Notes in Artificial Intelligence 7091, 12-23, Springer, Irvine, California, USA, 2011.
Yi Zeng. Web Retrieval and Reasoning based on Granular Computing (In Chinese). In: Ning Zhong, Jiming Liu, Yiyu Yao (Eds.), Advances in Web Intelligence (In Chinese), Higher Education Press, 2011.
Yan Wang, Zhisheng Huang, Yi Zeng, Ning Zhong, Frank van Harmelen. Interleaving Reasoning and Selection with Knowledge Summarization. Proceedings of the 2nd International Workshop on Cyber-Physical Society, IEEE Press, Beijing, China, October 24-26, 2011.
Yan Wang, Yi Zeng, Ning Zhong and Zhisheng Huang. A Matrix Approach to Implicit Relationship Finding in Large-scale Knowledge Base. Proceedings of the 7th International Conference on Semantics, Knowledge & Grids, IEEE Press, Beijing, China, October 24-26, 2011.
Yunfei Ma, Yi Zeng, Xu Ren, and Ning Zhong. User Interest Modeling Based on Multi-source Personal Information Fusion and Semantic Reasoning. Proceedings of the 2011 International Conference on Active Media Technology, Lecture Notes in Computer Science 6890, 195-205, Springer, Lanzhou, China, September 7-9, 2011.
Shaobo Wang, Yi Zeng, and Ning Zhong. Ontology Extraction and Integration from Semi-structured Data. Proceedings of the 2011 International Conference on Active Media Technology, Lecture Notes in Computer Science 6890, 39-48, Springer, Lanzhou, China, September 7-9, 2011.
Lulin Zhao, Yi Zeng, and Ning Zhong. A Weighted Multi-Factor Algorithm for Microblog Search. Proceedings of the 2011 International Conference on Active Media Technology, Lecture Notes in Computer Science 6890, 153-161, Springer, Lanzhou, China, September 7-9, 2011.
Yi Zeng, Erzhong Zhou, Yan Wang, Xu Ren, Yulin Qin, Zhisheng Huang, Ning Zhong. Research Interests : Their Dynamics, Structures and Applications in Unifying Search and Reasoning. Journal of Intelligent Information Systems, Volume 37, Number 1, 65-88, Springer, 2011.
Yi Zeng, Ning Zhong, Yan Wang, Yulin Qin, Zhisheng Huang, Haiyan Zhou, Yiyu Yao, and Frank van Harmelen. User-centric Query Refinement and Processing Using Granularity Based Strategies. Knowledge and Information Systems, Volume 27, Number 3, 419-450, Springer, 2011.
Yi Zeng, Erzhong Zhou, Yulin Qin, and Ning Zhong. Research Interests : Their Dynamics, Structures and Applications in Web Search Refinement. Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence, IEEE Computer Society, Toronto, Canada, August 31- September 3, 2010.
Yi Zeng, Yan Wang, Zhisheng Huang, Danica Damljanovic, Ning Zhong, and Cong Wang. User Interests: Definition, Vocabulary, and Utilization in Unifying Search and Reasoning. Proceedings of the 2010 International Conference on Active Media Technology, Lecture Notes in Computer Science 6335, 98-107, 2010.
Xu Ren, Yi Zeng, Yulin Qin, Ning Zhong, Zhisheng Huang, Yan Wang, and Cong Wang. Social Relation Based Search Refinement: Let Your Friends Help You!. Proceedings of the 2010 International Conference on Active Media Technology, Lecture Notes in Computer Science 6335, 475-485, 2010.
Yan Wang, Cong Wang, Yi Zeng, Zhisheng Huang, Vassil Momtchev, Bo Andersson, Xu Ren, and Ning Zhong. Normalized Medline Distance and Its Utilization in Context-aware Life Science Literature Search. Tsinghua Science and Technology, Volume 15, Issue 6, 709-715, Elsevier, 2010.
Yan Wang, Yi Zeng, Cong Wang, Xu Ren, Yulin Qin, Vassil Momtchev, Ning Zhong and Bo Andersson. Cognitive Memory Inspired Search Refinement on Life Science Literatures. Proceedings of the 7th International Conference on Cognitive Science (ICCS2010), Beijing, China, August 17-20, 2010.
Yiyu Yao, Ning Zhong, Yi Zeng. Information Retrieval Support Systems. In: Encyclopedia of Library and Information Sciences, Marcia J. Bates, Mary Niles Maack (Eds.), 3rd edition, Taylor & Francis Group , 2010, 2546-2552.
Yi Zeng, Xu Ren, Yulin Qin, Ning Zhong, Zhisheng Huang and Yan Wang. Social Relation Based Scalable Semantic Search Refinement. The 1st Asian Workshop on Scalable Semantic Data Processing (AS2DP), co-located with the 2009 Asian Semantic Web Conference, Shanghai, China, December 7th, 2009.
Yi Zeng, Yan Wang, Zhisheng Huang, Ning Zhong. Unifying Web-scale Search and Reasoning from the Viewpoint of Granularity. In: Proceedings of the 2009 International Conference on Active Media Technology, Lecture Notes in Computer Science 5820, 418-429, Springer, Beijing, China, October 22-24, 2009.
Peiqiang Li, Yi Zeng, Spyros Kotoulas, Jacopo Urbani, Ning Zhong. The Quest for Parallel Reasoning on the Semantic Web. In: Proceedings of the 2009 International Conference on Active Media Technology, Lecture Notes in Computer Science 5820, 430-441, Springer, Beijing, China, October 22-24, 2009.
Yi Zeng, Yiyu Yao, Ning Zhong. DBLP-SSE: A DBLP Search Support Engine. In: Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence, IEEE Computer Society, Milan, Italy, September 15-18, 2009.
Yi Zeng, Ning Zhong. On Granular knowledge Structures. In: Proceedings of the first International Conference on Advanced Intelligence, Beijing, China, October 18-22, 2008.
Yi Zeng, Yiyu Yao, Ning Zhong. Granular Structure-Based Knowledge Retrieval [In Chinese]. Computer Science, Vol.35, No.3, 2008, 194-196, 224.
( This paper is recommended to the journal of "Computer Science" by Joint Conference of The Seventh National Conference of Rough Set and Soft Computing, the First National Conference of Granular Computing, the First National Conference of Web Intelligence, Taiyuan, Shanxi, China, August 19-23, 2007. [Excellent Student Paper Award])

Talks and Presentations

Following is a list of my selected talks and presentations related to my research interests. Some of the slides are provided. For those which have not been provided, I may still on the way of refining them or the main ideas have been mentioned in later talks.

Selected Public Presentations

Invited Lecture: "Cognitive Brain Modeling". Okinawa Computational Neuroscience Course 2019, Okinawa Institute of Science and Technology, Okinawa, Japan, June 24 to July 11, 2019.
Invited Talk: "Creating Brain-inspired Conscious Living Beings: Progress and Future", Humanity+ Symposium: Human Meaning in an AI World, July 15th, Beijing, China, 2018.
Invited Talk: "Brain-inspired Conscious Living Beings", The Technological Revolution: Humanistic Crisis, or the Transformation of Civilization. Beijing, China, April 22, 2018.
Invited Talk: "Creating Brain-inspired Cognitive Machine", AI, Robotics and Society Workshop, Berggruen Institute, Beijing, China, March 17th, 2018.
Invited Talk: "Brain-inspired Conscious Machine". Dialogue among Scientists and Philosophers, Berggruen Institute, Beijing, China, Feburary 7th, 2018.
Invited Talk: "Brain-inspired Intelligence: From Brain-inspired Learning to Brain-inspired Conscious Machine". The 3rd Conference on "Philosophy and Theory of Artificial Intelligence", November 4-5th, Leeds, UK, 2017.
Invited Talk: "Brain-inspired Intelligence: From Brain and Mind Modeling to Artificial General Intelligence". International Forum on Brain Science and Brain-inspired Research, Qingdao, China, August 11-13th, 2017.
Invited Talk: "Brain-inspired Intelligence: Retrospect and Outlook". International Workshop on Human and Machine Learning, Beijing, China, August 16-18th, 2017.
Invited Talk: "Brain-inspired Intelligence: Historical Review, Recent Progress and Outlooks". The 3rd Form on Brain and Brain-inspired Computing, Beijing, China, June 28th, 2017.
Invited Talk: "Brain-inspired Intelligence: Grand Challenges and Progresses". Science Forum on Artificial Intelligence, German Embassy in China, Beijing, China, April 24th, 2017.
Invited Talk: "Brain-inspired Intelligence: Historical Review, Recent Progress and Outlooks". The 13th Workshop on Mind and Machine, Guangzhou, China, October 29-30th, 2016.
Invited Talk: "Brain-inspired Intelligence and Its Applications in Intelligent Robotics". The 4th International Workshop on Advances in Neuroinformatics, Wako, Japan, May 28-29th, 2016.
Invited Talk: "Linked Brain Data: a Web-scale Knowledge Platform for Brain and Neuroscience". The 4th International Workshop on Advances in Neuroinformatics, Wako, Japan, May 28-29th, 2016.
Invited Talk: "Retrospect and Outlook of Brain-inspired Intelligence". Leading Edge Forum on Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, January 13th, 2016.
Invited Talk: "Cognitive Brain Computational Modeling". International Brain-inspired Computing Forum, Beijing, China, October 15th, 2015.
Invited Talk: "Multi-scale Brain Simulation and Applications". Computing powered Brain Science Workshop, Beijing, China, December 11th, 2014.
Invited Talk: "Brain Systems Engineering". The 14th International Workshop on Meta-synthesis and Complex System, Beijing, China, November 8th, 2014.
Linked Neuron Data (LND): A Platform for Integrating and Semantically Linking Neuroscience Data and Knowledge. The 7th Neuroinformatics Congress (Neuroinformatics 2014) in Leiden, the Netherlands, August 25-27, 2014.
Neuronal Morphology Simulation based on Microscopy Reconstruction Data in the Public Repositories. The 2014 International Conference on Brain Informatics and Health (BIH 2014) in Warsaw, Poland, August 11-14, 2014.
Active Recommendation of Tourist Attractions based on Visitors Interests and Semantic Relatedness. The 2014 International Conference on Active Media Technology (AMT 2014), in Warsaw, Poland, August 11-14, 2014.
Neural Pathway Prediction based on Multi-neuron Spike Train Data. The Twenty-Third Annual Computational Neuroscience Meeting (CNS 2014) in Québec City, Canada, July 26-31, 2014.
CASIA-KB: A Multi-source Chinese Semantic Knowledge Base Built from Structured and Unstructured Web Data. The 3rd Joint International Semantic Technology Conference (JIST 2013), Seoul, Korea, November 28-30, 2013.
Entity Conceptualization and Understanding based on Web-scale Knowledge Bases. The 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2013), Manchester, the United Kingdom, October 13-16, 2013.
Tutorial: "Extracting, Linking and Analyzing the Web of Structured Chinese Data" at the 2nd Hot Topics in Database Conference (HotDB 2012), November 19th 2012. [Slides]
Ranking and Combining Social Network Data for Web Personalization. The International Workshop on Data-driven User Behavioral Modelling and Mining from Social Media, co-located with the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012), Hawaii, USA, October 29th, 2012. [Slides]
Research Interests : Their Dynamics, Structures and Applications in Personalized Web Search, Microsoft Research Asia NLC Group, Dec 29, 2010. [slides]
Research Interests : Their Dynamics, Structures and Applications in Web Search Refinement. The 2010 IEEE/WIC/ACM International Conference on Web Intelligence, Toronto, Canada, September 2, 2010.
User Interests: Definition, Vocabulary, and Utilization in Unifying Search and Reasoning. The 2010 International Conference on Active Media Technology, Toronto, August 28, 2010.
Social Relation Based Search Refinement: Let Your Friends Help You!. The 2010 International Conference on Active Media Technology, Toronto, August 28, 2010.
Normalized Medline Distance and Its Utilization in Context-aware Life Science Literature Search. The 4th Chinese Semantic Web Symposium, August 20, 2010.
Cognitive Memory Inspired Search Refinement on Life Science Literatures. The 7th International Conference on Cognitive Science (ICCS2010), Beijing, China, August 17, 2010.
Social Relation Based Scalable Semantic Search Refinement. the 2009 Asian Scalable Semantic Data Processing Workshop, co-located with the 2009 Asian Semantic Web Conference, Shanghai, China, December 7, 2009. [Slides]
LarKC: The Large Knowledge Collider. the 2009 Asian Scalable Semantic Data Processing Workshop, co-located with the 2009 Asian Semantic Web Conference, Shanghai, China, December 7, 2009. [Slides]
Unifying Web-scale Search and Reasoning from the Viewpoint of Granularity. the 2009 International Conference on Active Media Technology, Beijing, China, October 22-24, 2009. [Slides]
The Quest for Parallel Semantic Web Reasoning. the 2009 International Conference on Active Media Technology, Beijing, China, October 22-24, 2009.
Cross Work Package Report: Recent Progress and Problems for Unifying Search and Reasoning. LarKC General Assembly, Max-Plank Institute for Human Development, Berlin, Germany, September, 2009.
Unifying Web-scale Search and Reasoning from the Viewpoint of Granularity. LarKC PhD Student Symposium 2009, Free University Berlin, Berlin, Germany, September, 2009.
DBLP-SSE: A DBLP Search Support Engine. the 2009 IEEE/WIC/ACM International Conference on Web Intelligence, Milan, Italy, September 15-18, 2009. [Slides]
A Preliminary Note on Granular Reasoning, Web & AI Weekly Seminar, Vrij University Amsterdam, the Netherlands, June 15th, 2009.
WP2 Working Report: Cognitive Memory Retention Based Granular Selection. LarKC General Assembly, Milan, Italy, May 18-21, 2009.
WP4 Working Report: Evaluation of Granular Reasoning. LarKC General Assembly, Milan, Italy, May 18-21, 2009.
Accelerating LarKC by Reasoning through Granular Knowledge Structures. LarKC General Assembly, Bled, Slovenia, January 12-14, 2009. [slides]
Accelerating Knowledge Selection by Cognitive Memory and Interactive Knowledge Structures. On: LarKC General Assembly, Bled, Slovenia, January 12-14, 2009. [slides]
On Granular knowledge Structures. On: The 2008 International Conference on Advanced Intelligence, Beijing, China, October 18-22, 2008.
Granular Knowledge Structures: Theoretical Foundations and Examples. On: The 2007 Annual International WIC Institute Student Workshop, December 29, 2007.[Best Presentation Award]
Granular Structure-Based Knowledge Retrieval. On: Joint Conference of The Seventh National Conference of Rough Set and Soft Computing, the First National Conference of Granular Computing, the First National Conference of Web Intelligence, Taiyuan, Shanxi, China, August 19-23, 2007. [Excellent Student Paper Award]
Supporting Literature Exploration with Granular Knowledge Structures. On: Joint Rough Set Symposium' 07, MarRS center, Toronto, Canada, May 16th, 2007.
Cognitive Process based Research Support Systems. On: The 2006 Annual International WIC Institute Student Workshop, Dec 14th, 2006. [Best Presentation Award]

Advisory and Working Groups

Expert, Ad Hoc Expert Group on AI Ethics, United Nations Education, Science and Culture Organization (UNESCO). (2020-).
Expert, UNESCO High-level Expert Group on the Implementation of Recommendation on AI Ethics (2022-).
Expert, World Health Organization (WHO) Expert Group on Ethics and Governance of Artificial Intelligence in Health (2019-).
Member, National Governance Committee of Next Generation Artificial Intelligence, Ministry of Science and Technology China (2019-).
Board Member, Committee on Artificial Intelligence, National Committee on Science and Technology Ethics, China (2020-).
Chair, Professional Ethics Committee of Information Technology and Artificial Intelligence, the Science and Ethics Committee, Chinese Academy of Sciences (2021-).
Chair, Committee on Mind Computation, Chinese Association for Artificial Intelligence (2022-).
Deputy Chair, Working Group on Artificial Intelligence, World Internet Conference (2023-).
Founding Executive Chair, AI for Sustainable Development Goals Cooperation Network (2020-).
Chair, Professional Committee on Information Technology and Artificial Intelligence, Science and Technology Ethics Committee, Chinese Academy of Sciences (2021-).
Member, Advisory Council, Institute of Ethics in AI, University of Oxford (2021-).
Board of Advisors. Carnegie Council for Ethics in International Affairs (2021-).
Consultation Expert, National Commission of the People's Republic of China for UNESCO (2020-).
Deputy Chair, Committee on AI Governance and Trustworthiness, Artificial Intelligence Industry Alliance, China (2021-).
Invited Expert, Research Center for Next Generation Artificial Intelligence Development, Ministry of Science and Technology China. (2018-).
International Advisory Board Member. Paradigms of Artificial General Intelligence and Their Associated Risks. University of Cambridge. (2018-2021).
Committee Member, Global Future Council on China. World Economic Forum. (2019-2020).
Committee Member, Global Future Council on Values, Ethics and Innovation. World Economic Forum. (2018-2019).

Editorial Services

[Co-Editor-in-Chief] Translation Series on AI Ethics, Governance and Sustainable Development (2020)
[Editorial Board Member] AI & Ethics, Springer (2020-).
[Editorial Board Member] Journal of Artificial Intelligence and Consciousness, World Scientific (2019-).
[Associate Editor] Cognitive Systems Research, Elsevier (2016-2020).

Conference and Workshop Chairs

Chair, The 2021 International Workshop on Cross-Cultural Cooperation on Artificial Intelligence, December 4th, 2021.
Chair, The 2nd International Forum on AI Ethics, Governance, and Sustainable Development, the 2nd Annual Conference on Beijing Academy of Artificial Intelligence, June 22nd, 2020.
Chair, The 1st International Forum on AI Ethics, Safety and Governance, the 1st Annual Conference on Beijing Academy of Artificial Intelligence, October 31st, 2019.
Program Chair, The 10th International Conference on Brain Informatics, November 16-18th, 2017, Beijing, China.
Local Organization Chair, The 8th International Conference on Brain-inspired Cognitive Systems, November 28-30, 2016, Beijing, China.
Workshop Co-Chair, The 2nd International Workshop on Brain and Artificial Intelligence, November 16, 2017, Beijing, China.
Workshop Co-Chair, The 1st International Workshop on Knowledge Representation: Brain and Machine, November 16, 2017, Beijing, China.
Workshop/Special Session Chair, 2016 International Conference on Brain Informatics & Health. October 13-16, 2016 in Omaha, Nebraska, USA.
Publicity Chair, The 2015 International Conference on Brain Informatics and Health, 30 August-2 September 2015, London, UK.
Workshop Co-Chair, The 5th International Workshop on Web-scale Knowledge Representation, Retrieval, and Reasoning (Web-KR 2014), co-located with the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014) in Shanghai, China, November 3rd, 2014.
Workshop Co-Chair, The 3rd International Workshop on Data-driven User Behavioral Modelling and Mining from Social Media (DUBMOD 2014), co-located with the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014) in Shanghai, China, November 3rd, 2014.
Workshop Co-Chair, The 4th International Workshop on Web-scale Knowledge Representation, Retrieval, and Reasoning (Web-KR 2013), co-located with the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013) at San Francisco Airport Marriott Waterfront, Burlingame, CA, USA, November 1st, 2013.
Workshop Co-Chair, The 2012 International Workshop on Web-scale Knowledge Representation, Retrieval, and Reasoning (Web-KR 2012), co-located with the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012) , Maui Hawaii, 29 October 2012.
Workshop Co-Chair, The 2011 International Workshop on Web-scale Knowledge Representation, Retrieval and Reasoning, co-located with the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Lyon, France, August 22-27, 2011.
Publicity Chair, The 2011 International Conference on Active Media Technology, Lanzhou, China, September 7-9, 2011.
Publicity Chair, The 2011 International Conference on Brain Informatics, Lanzhou, China, September 7-9, 2011.
Workshop Co-Chair, The 2010 International Workshop on Web-scale Knowledge Representation, Retrieval and Reasoning, co-located with the 2010 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Toronto, Canada, August 31-September 3, 2010.