Research
Research Interests
My research interests include machine learning and data mining, with a particular focus on the learnware paradigm: reusing existing well-trained models to solve new tasks.
Academic Service
Conference Reviewers:
- NeurIPS (2022–2025), ICML (2023–2026), ICLR (2024–2025), AAAI (2023, 2025, 2026), IJCAI (2021), ECAI (2023), PAKDD (2021)
Reviewer for Journals:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- Frontiers of Computer Science (FCS)
Awards & Honors
- 国家资助博士后计划 B 档，2026 年
- 湖南省芙蓉计划科技创新类人才，2026 年
- 国防科技大学德雅青年学者博士后，2025 年
- 中国研究生数学建模竞赛“数模之星”提名（前10），2019 年
Project
Beimingwu: A Learnware Dock System
Beimingwu is an open-source platform for sharing, identifying, and reusing well-trained machine learning models to solve new tasks. I contributed to its development as part of the Learnware-LAMDA team.