Research Interests

His research mainly focuses on AI Ethics, Safety and Governance, Brain-Inspired AI, and AI for Sustainable Development.

1. AI Ethics, Safety and Governance: Moral and Ethial AI model, AI value alignment, ethical assessment, short-term and long-term ethics, safety and governance of AI and agents, as well as the development of low-risk, highly safe, moral AI that live in symbiosis with humans.

2. Brain-Inspired AI: brain-inspired cognitive intelligence for artificial general intelligence (AGI) and superintelligence, including brain-inspired spiking neural networks, brain-inspired artificial neural networks, brain-inspired autonomous learning, developmental and evolutionary theories, algorithms, models and applications.

3. AI for Sustainable Development: AI and youth development, AI powered cultural heritage and exchanges, AI for sustainable development.

Honors & Awards

· TIME 100 Most Influential People in AI (TIME 100/AI), 2023

Professional Affiliations

· Founding Dean, Beijing Institute of AI Safety and Governance (Beijing-AISI)

· Director, Beijing Key Laboratory of Safe AI and Superalignment

· Expert, United Nations Advisory Body on AI (UN HLAB)

· Expert, UNESCO Ad Hoc Expert Group on AI Ethics

· Chair, Mind Computing Technical Committee, Chinese Association for Artificial Intelligence (CAAI)

· Co-Chair, AI Committee, World Internet Conference (WIC)

· Member, National New Generation AI Governance Special Committee

· Member, AI Subcommittee of the National Science and Technology Ethics Committee

· Co-Lead, AI Governance Thematic Group, National AI Standardization Overall Group

· Member, Beijing AI Strategic Advisory Committee

Selected Publications

AI Ethics, Safety and Governance:

· Feifei Zhao, Hui Feng, Haibo Tong, Zhengqiang Han, Erliang Lin, Enmeng Lu, Yinqian Sun, Yi Zeng: Building Altruistic and Moral AI Agent With Brain-Inspired Emotional Empathy Mechanisms. IEEE Transactions on Affective Computing. 17(1): 559-574, 2026.

· Guobin Shen, Dongcheng Zhao, Haibo Tong, Jindong Li, Feifei Zhao, Yi Zeng. Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense. Proceedings of the 14th International Conference on Learning Representations (ICLR), 2026.

· Guobin Shen, Dongcheng Zhao, Yiting Dong, Xiang He, Yi Zeng. Jailbreak Antidote: Runtime Safety-Utility Balance via Sparse Representation Adjustment in Large Language Models. International Conference on Learning Representations (ICLR), 2025.

· Guobin Shen, Dongcheng Zhao, Aorigele Bao, Xiang He, Yiting Dong, Yi Zeng. StressPrompt: Does Stress Impact Large Language Models and Human Performance Similarly?. AAAI Conference on Artificial Intelligence (AAAI), 2025.

· Haibo Tong, Zeyang Yue, Feifei Zhao, Erliang Lin, Lu Jia, Ruolin Chen, Yinqian Sun, Qian Zhang, Yi Zeng. CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models, ACL, 2026.

· Yuwei Wang, Enmeng Lu, Zizhe Ruan, Yao Liang, Yi Zeng. Stream: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models. AI & SOCIETY, 2024: 1-9.

· Aorigele Bao, Yi Zeng. Understanding the dilemma of explainable artificial intelligence: a proposal for a ritual dialog framework. Humanities and Social Sciences Communications, Nature Press, 11.1 (2024): 1-9.

· Aorigele Bao, Yi Zeng. Embracing grief in the age of deathbots: a temporary tool, not a permanent solution. Ethics and Information Technology, 2024, 26(1): 7.

· 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, Kang Sun, Enmeng Lu. Declaration on the Ethics of Brain-Computer Interfaces and Augment Intelligence. AI and Ethics, Springer, 2021.

Brain-inspired AI：

· Xiang He, Dongcheng Zhao, Yang Li, Qingqun Kong, Xin Yang, Yi Zeng. Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligence, Science Advances, accepted, 2026.

· Yinqian Sun, Feifei Zhao, Mingyang Lv, Yi Zeng. Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning, . Proceedings of the National Academy of Sciences (PNAS), 122 (50) e2513319122, 2025.

· 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), 120 (39) e2218173120, 2023.

· Bing Han, Feifei Zhao, Yi Zeng, Guobin Shen. Developmental Plasticity-inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2024.

· Tenglong Li, Jindong Li, Guobin Shen, Dongcheng Zhao, Qian Zhang, Yi Zeng. FireFly-T: High-Throughput Sparsity Exploitation for Spiking Transformer Acceleration with Dual-Engine Overlay Architecture, IEEE Transactions on Computers, 2026.

· Shen Guobin, Li Jindong, Li Tenglong, Zhao Dongcheng, Zeng Yi. SpikePack: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025.

· Jihang Wang, Dongcheng Zhao, Chengcheng Du, Xiang He, Qian Zhang, Yi Zeng. Random heterogeneous spiking neural network for adversarial defense. iScience, Cell Press, 2025.

· Yonghao Yu, Dongcheng Zhao, Guobin Shen, Yiting Dong, Yi Zeng. Brain-Inspired Stepwise Patch Merging for Vision Transformers. IJCAI, 2025.

· Wenxuan Pan, Feifei Zhao, Guobin Shen, Bing Han, Yi Zeng. Brain-Inspired Multi-Scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks. IEEE Transactions on Evolutionary Computation, 2024.

· Ilana Witten, Daniel L.K. Yamins, Claudia Clopath, Matthias Bethge, Yi Zeng, Ann Kennedy, Abeba Birhane, Doris Tsao, Been Kim, Ila Fiete. Future views on neuroscience and AI. Cell, 2024.

· Li Tenglong, Li Jindong, Shen Guobin, Zhao Dongcheng, Zhang Qian, Zeng Yi. FireFly-S: Exploiting Dual-Side Sparsity for Spiking Neural Networks Acceleration with Reconfigurable Spatial Architecture. IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), 2024.

· Xiang He, Dongcheng Zhao, Yang Li, Guobin Shen, Qingqun Kong, Yi Zeng. An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain. AAAI, 2024.

· Guobin Shen, Dongcheng Zhao, Tenglong Li, Jindong Li, Yi Zeng. Are Conventional SNNs Really Efficient? A Perspective from Network Quantization. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

· Jindong Li, Tenglong Li, Guobin Shen, Dongcheng Zhao, Qian Zhang, Yi Zeng. Revealing Untapped DSP Optimization Potentials for FPGA-Based Systolic Matrix Engines. 34th International Conference on Field-Programmable Logic and Applications, 2024.

· Sicheng Shen, Dongcheng Zhao, Guobin Shen, Yi Zeng. TIM: An Efficient Temporal Interaction Module for Spiking Transformer. IJCAI, 2024.

· Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng. Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. Advances in Neural Information Processing Systems (NeuRIPS), 2024, 36.

· 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.

· 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.

· 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.

Contacts

Email：yi.zeng (@)ruc.edu.cn