Research Interests

We envision that the future of artificial intelligence will be an ecosystem of massive intelligent capabilities, where diverse models and agents continuously collaborate, evolve, and collectively address complex problems beyond the scope of any individual intelligence.

Built upon the Learnware paradigm (Learnware = Model + Specification), which enables models to become reusable intelligent units through specifications that characterize their implicit high-dimensional capabilities. My research aims to build the foundations for such an open intelligence ecosystem by studying how intelligent capabilities can be represented, organized, and composed.

• Intelligent capability characterization (specification design): developing capability representations and characterization methods to understand, characterize, organize, and reuse the diverse capabilities embedded in machine learning models.
• Self-evolving intelligent systems (learnware system): exploring how large-scale collections of reusable intelligent units can be autonomously coordinated, composed into self-evolving intelligent systems.

Talks

• 2026/7/31. 面向开放世界模型复用的模型能力刻画方法探索
  第十一届 CCF 中国数据挖掘会议 (CCDM 2026) · 开放环境下模型和智能体的复用与演进论坛.
• 2025/6/15. 学件规约分析与系统架构设计
  第十四届江苏省计算机大会 (JSCC 2025) · 人工智能前沿论坛

Academic Service

IJCAI 2021 Workflow Chair (May. 2020 - Aug. 2021) [Certificate of Appreciation]

Conference Reviewers:

• ICML (2026, 2025, 2024, 2023, 2022), NeurIPS (2025, 2024, 2023, 2022), ICLR (2026, 2025, 2024), AAAI (2027, 2025, 2024, 2022, 2020), KDD (2025), IJCAI (2020, 2019), AISTATS (2023, 2022), ECAI (2020), PAKDD (2022), PRICAI (2025, 2019)

Reviewer for Journals:

• Machine Learning (MLJ)
• Frontiers of Computer Science (FCS)
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• Transactions on Machine Learning Research (TMLR)
• International Journal of Data Science and Analytics (JDSA)
• IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
• ACM Transactions on Knowledge Discovery from Data (TKDD)

Awards & Honors

• 江苏省人工智能学会 (JSAI) 优秀博士学位论文，2025
• 南京大学“紫金学者”，2024
• 南京大学“毓秀青年学者”计划，2024
• 中国计算机学会人工智能会议 (CCFAI 2023) 最佳论文奖, 2023
• 南京大学-华为联合实验室突出贡献奖, 2023