I joined the School of Artificial Intelligence at Beijing Normal University (BNU) as an Associate Professor and Ph.D. Supervisor in September 2024. I am a member of the Visual Media Computing Lab, Prof. Hua Huang’s team. Prior to this, I was a young senior researcher at the Institute of Information Engineering, Chinese Academy of Sciences, from September 2020 to September 2024. I received my Ph.D. from the University of Chinese Academy of Sciences in June 2020, under the supervision of Professor Yong Liu and Professor Weiping Wang.

北京师范大学人工智能学院副教授、博士生导师，智能媒体计算实验室（黄华教授团队）成员；研究方向聚焦大模型信息压缩、高效智能体与教育智能体系统。已发表高水平学术论文40余篇，Google Scholar 被引用1000余次；其中以第一作者在 IEEE Transactions on Information Theory (IEEE TIT)、Journal of Machine Learning Research (JMLR) 与 Artificial Intelligence (AIJ)、ICML、NeurIPS、AAAI等人工智能领域顶级期刊及会议论文发表十余篇。近五年主持国家自然科学基金面上项目/青年项目、国家重点研发计划子课题、中国博士后科学基金、中央高校基本科研业务费等科研项目，累计项目经费318万元。曾入选微软亚洲研究院“铸星计划”、中国科学院特别研究助理、中科院信工所优才计划 A 类与 B 类等人才计划，曾获 PRICAI 2021 最佳学生论文奖。

My research focuses on information compression for large language models and efficient intelligent agents, aiming to build resource-aware LLM systems that preserve reasoning, memory, and tool-use capabilities under constrained computation, context, and deployment budgets. I am particularly interested in the fundamental mechanisms of compression, adaptation, and capability preservation, as well as their deployment in reliable and scalable educational AI systems. Specific research interests include, but are not limited to:

• Information compression for LLMs: Investigating model compression, context compression, memory compression, knowledge compression, and skill compression to understand how large-scale models and agents can retain essential information and capabilities with lower computational and contextual cost.

• Efficient and resource-aware agents: Studying cost-aware reasoning, budgeted memory, dynamic retrieval, tool-use scheduling, small-agent capability enhancement, and multi-agent coordination to improve the efficiency, robustness, and scalability of agentic LLM systems.

• Educational intelligent agents: Developing efficient, trustworthy, and deployable educational agents for interactive teaching-resource generation, question-generation agents, lesson-plan generation, intelligent tutoring, educational evaluation, and personalized learning support.

Career

Education

Selected Papers [Full List] [Google Scholar]

• Textual Stochastic Gradient Descent: Discrete Optimization of External Memory for Reasoning Language Agents.
  Jian Li, Hua Huang.
  International Conference on Machine Learning (ICML), 2026. CCF-A Conference.

• A Survey on Model Compression for Large Language Models. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Can Ma, Weiping Wang.
  Transactions of the Association for Computational Linguistics (TACL), 2024. CCF-B Journal / SCI Q1.
  

• Distilling mathematical reasoning capabilities into Small Language Models. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Can Ma, Weiping Wang.
  Neural Networks, 2024. CCF-B Journal / SCI Q1.

• Optimal Rates for Agnostic Distributed Learning. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  IEEE Transactions on Information Theory (TIT), 2023. CCF-A Journal / SCI Q1.
  

• Optimal Convergence Rates for Distributed Nyström Approximation. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  Journal of Machine Learning Research (JMLR), 2023. CCF-A Journal / SCI Q1.

• Convolutional Spectral Kernel Learning with Generalization Guarantees. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  Artificial Intelligence (AIJ), 2022. CCF-A Journal / SCI Q2.

• Optimal Convergence Rates for Agnostic Nyström Kernel Learning. [pdf]
  Jian Li, Yong Liu, Weiping Wang.
  International Conference on Machine Learning (ICML), 2023. CCF-A Conference.

• Federated learning for non-iid data: From theory to algorithm. [pdf] [presentation] [🏆Best Student Paper Award] (1/92)
  Bojian Wei, Jian Li*, Yong Liu, Weiping Wang.
  Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2021. CCF-C Conference, Best Student Paper Award.

Projects

• National Natural Science Foundation of China (No. 62576041), 2026.01 - 2029.12, ¥500,000.
  Information Compression of Large Language Models: Mathematical Mechanism Analysis and Algorithm Design.

• Fundamental Research Funds for the Central Universities, Young Faculty Research Start-up Project, 2024.10 - 2026.09, ¥200,000.
  Fundamental Research on Large Language Models for Efficient Reasoning.

• China Postdoctoral Science Foundation (Special Support, No. 2023T160680), 2023.07 - 2024.03, ¥180,000.
  Research on Deep Differentiable Gaussian Processes for Structured Prediction.

• National Key R&D Program of China (2022YFB3105302.2), 2022.12 - 2025.11, ¥1,200,000.
  Aggregation and Collaborative Techniques for Cross-platform Heterogeneous Data.

• National Natural Science Foundation of China (No. 62106257), 2022.01 - 2024.12, ¥300,000.
  Large Scale Structured Prediction with Automated Spectral Kernel Learning.

• Special Research Assistant Project of CAS, 2020.09 - 2022.09, ¥800,000.
  Large-scale Few-shot Automated Machine Learning.

Patents

• Jian Li, Yong Liu, Liubin Wang, Yiguo Yang, Juhong Wang. Neural Network Architecture Search Method, Device, Computer Equipment, and Storage Medium: China. Granted invention patent, Granted Publication No. CN113408721B; Granted Date: May 16, 2025.
• Hailun Lin, Yong Liu, Jian Li, Weiping Wang. A Large-Scale Ontology Merging Method that Integrates Representation Learning and Divide-and-Conquer Strategy: China. Granted invention patent, Granted Publication No. CN110059194B; Granted Date: April 8, 2022.
• Jian Li, Jiaoyang Li, Zheng Lin, Yong Liu, Weiping Wang. A Vertical Domain Large Model Method and System Based on Knowledge Distillation and Prompt Engineering: China. Patent application, Publication No. CN117933360A; Publication Date: April 26, 2024.
• Jian Li, Jiaoyang Li, Bojian Wei, Yong Liu, Weiping Wang. A Federated Learning Method and System Based on Attention Mechanism: China. Patent application, Application No. CN202311073645.3; Application Date: August 24, 2023.

Students

• Ph.D. students: Yilin Kang (2020.09 - 2023.06, Differential Privacy; post-graduation: Purple Mountain Laboratories / Yuxi Normal University); Xunyu Zhu (2020.09 - 2025.06, Efficient LLM Inference and LLM Compression; publications in TACL, Neural Networks, etc.; post-graduation: State Power Investment Corporation Central Research Institute).
• Master students: Bojian Wei (2020.09 - 2022.06, Federated Learning; PRICAI 2021 Best Student Paper Award; post-graduation: Management Trainee in Bank of China Head Office); Xuning Zhang (2023.09 - 2026.06, Federated Learning; publication in TNNLS; post-graduation: ByteDance); Zhenyu Wu (2024.09 - present, Interactive Teaching Resource Generation and Question-Generation Agents); Mucun Xie (2025.09 - present, Efficient Agent Memory); Zongyou Tan (2025.09 - present, Educational Intelligent Agents).

Honors and Awards

• Microsoft Research Asia StarTrack Scholars Program, 2024
• Talent Plan Class A of IIE, CAS, 2023.
• PRICAI 2021 best student paper award, 2021.
• Special Research Assistant of Chinese Academy of Sciences, 2020.
• Talent Plan Class B of IIE, CAS, 2020.
• AIDU Talents of Baidu Research, 2020.
• Outstanding Graduates of Beijing, 2020.
• Outstanding Graduates of University of Chinese Academy of Sciences (UCAS), 2020.
• National Scholarship for Doctoral Students (twice), 2018 and 2019.
• ZhuLiYueHua Scholarship for Excellent Doctoral Student, 2019.
• CAS Presidential Scholarship, 2019.

Academic Service

• Committee member: CCF Technical Committee on Artificial Intelligence and Pattern Recognition.
• Academic forum organization: VALSE 2025 (Foundation of Large Models: Understanding Large Model Development from a Theoretical Perspective); 2026 CSIG Young Scientist Forum (Foundation of Large Models).
• Program committee member: ICML, NeurIPS, ICLR, AAAI, MM, KDD, etc.
• Journal service: Guest editor for a special issue of MDPI Mathematics (SCI Q1); reviewer for TPAMI, JMLR, Pattern Recognition, Acta Automatica Sinica, Chinese Journal of Computers, Journal of Software, etc.