Li Zhi

Zhi Li，PhD, Assistant Professor. Received his PhD in Computer Science and Technology from the University of Science and Technology of China in 2021, specializing in embodied AI, information fusion, large language models, knowledge representation and reasoning. In recent years, he has published over 40 CCF A/SCI Q1 papers in major international academic conferences in data mining, artificial intelligence, and robotics, including ICML, CVPR, NeurIPS, KDD, SIGIR, AAAI, IJCAI, and important academic journals such as IEEE TKDE, IEEE T-Mech, IEEE TNNLS, PR, and Science in China: Information Science. His research achievements have won numerous awards, including the Outstanding Paper Award at the 1st Aerospace Frontier Conference, the Best Paper Award at the 13th International Conference on Knowledge Science, Engineering and Management, the Best Student Paper Award at the 8th China Conference on Data Mining, and Top 10 Highly Cited Papers in the 2019 Journal of Computer Research and Development. He was also selected for the 10th China Association for Science and Technology's Young Talent Support Project. He has been granted over 10 national invention patents and 5 software copyrights, and some of his research results have been successfully commercialized.

Zhi Li currently serving as a reviewer for several academic journals including IEEE TKDE, ACM TOIS, ACM TKDD, IEEE TMC, and IEEE TNNLS, and a program committee member for international academic conferences such as ICLR, CVPR, ACL, KDD, SIGIR, AAAI, MM, and EMNLP. Also serving as a member and secretary of the Secretariat of the Intelligent Fusion Committee of the Chinese Association for Artificial Intelligence.

We welcome self-motivated, aspiring, and grounded undergraduate, graduate, postdoctoral, and engineer individuals to join our team to explore AI and robot learning theories and methods and their collaborative innovation in ocean engineering and multi-agent collaborative practices.

Sept. 2016 - Dec. 2021, Ph.D. in Data Science (Computer Science and Technology), University of Science and Technology of China, China

Sept. 2011 - Jun. 2015, B.Eng. in Software Engineering, Xi'an Jiaotong University, China

Nov. 2025 – Present, Tsinghua University Shenzhen Graduate School, Assistant Professor,

Mar. 2022 – Oct. 2025, Tsinghua University Shenzhen Graduate School, Postdoctoral Fellow/Assistant Researcher

Member/Secretariat Secretary of the Intelligent Fusion Committee of the Chinese Association for Artificial Intelligence

Member of IEEE/ACM/CIE/CAAI

Journal Reviewers: IEEE TKDE, ACM TOIS, IEEE TNNLS, IEEE TMC Neurocomputing, etc.

Conference Program Committee Members: ICLR 2024-2026, CVPR 2024-2026, NeurIPS 2024-2025, ACL 2024-2025, SIGIR 2022-2025, ACM MM 2023-2025, AAAI 2022-2026, etc.

My research focuses on robot learning, multi-modal information fusion, large language models, knowledge representation and reasoning, with a special interest in their application in ocean engineering.

1. Multimodal Information Fusion and Multimodal Large Language Model: This area focuses on multimodal information fusion technology, researching unified multimodal representation models, contextual learning, CoT reasoning, and multimodal knowledge learning, with a special focus on their applications in GUI agents and multi-agent systems.

2. Multi-agent Systems: This area focuses on collaborative perception and autonomous decision-making in multi-agent systems, with a focus on collaborative observation and environmental perception based on multi-source heterogeneous sensor data, and collaborative motion planning and decision control for multiple robots.

3. Embodied AI: This area focuses on robot learning technology based on large language models, conducting research on robot navigation, planning, and control related to visual-language multimodal collaboration.

[1]. Xiao B, Ruan S, Li Z, et al. Improving Radar–Camera Fusion for 3D Object Detection via Eliciting Knowledge From Foundation Model[J]. IEEE/ASME Transactions on Mechatronics, 2025.

[2]. Ke Y, Li S, Li Z, et al. ArenaSim: A High-Performance Simulation Platform for Multi-Robot Self-Play Learning[J]. IEEE Robotics and Automation Letters, 2025.

[3]. Mao Q, Li Z, Liu Q, et al. Promoting Machine Abilities of Discovering and Utilizing Knowledge in a Unified Zero-Shot Learning Paradigm[J]. ACM Transactions on Knowledge Discovery from Data, 2024, 19(1): 1-26.

[4]. Mao Q, Liu Q, Li Z, et al. Cross-reconstructed augmentation for dual-target cross-domain recommendation[C]//Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2024: 2352-2356.

[5]. He N, Li S, Li Z, et al. Rediffuser: Reliable decision-making using a diffuser with confidence estimation[C]//Forty-first International Conference on Machine Learning. 2024.

[6]. He W, Li Z, Wang H, et al. Multimodal Dialogue Systems via Capturing Context-aware Dependencies and Ordinal Information of Semantic Elements[J]. ACM Transactions on Intelligent Systems and Technology, 2024, 15(3): 1-25.

[7]. Wu L, Li Z, Zhao H, et al. Supporting your idea reasonably: A knowledge-aware topic reasoning strategy for citation recommendation[J]. IEEE Transactions on Knowledge and Data Engineering, 2024, 36(8): 4275-4289.

[8]. Hong S, Liu Y, Li Z, et al. Multi-agent collaborative perception via motion-aware robust communication network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024: 15301-15310.

[9]. Liu Z, Cheng M, Li Z, et al. Adaptive normalization for non-stationary time series forecasting: A temporal slice perspective[J]. Advances in Neural Information Processing Systems, 2023, 36: 14273-14292.

[10]. Wu L, Li Z, Zhao H, et al. Recognizing unseen objects via multimodal intensive knowledge graph propagation[C]//Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2023: 2618-2628.