Fan Lyu, PhD, Postdoc AI researcher
New Laboratory of Pattern Recognition (NLPR)
Institute of Automation, Chinese Academy of Sciences (CASIA)
Contact
: fan.lyu@cripac.ia.ac.cn, fanlyu@ieee.org
I am currently a Postdoctoral Research Fellow at the New Laboratory of Pattern Recognition (NLPR) , Institute of Automation, Chinese Academy of Sciences (CASIA) , supervised by Prof. Liang Wang . I received my Ph.D. from the College of Intelligence and Computing, Tianjin University, under the supervision of Prof. Wei Feng . Earlier, I earned my master’s degree from Suzhou University of Science and Technology in 2018, where I was advised by Prof. Fuyuan Hu . My research focuses on Open-World Learning, with an emphasis on Continual Learning and Test-Time Learning. I am particularly interested in building machine learning models that can adapt to dynamic and evolving environments. I also have a solid background in computer vision and multi-modal learning, with several publications in these domains. I have led and participated in multiple research projects and am experienced in managing teams to deliver complex tasks in both academic and applied settings.
🔔 News
- ‼️ 2025.06 | 1 paper was accepted by IEEE TMM 2025: Constructing Enhanced Mutual Information for Online Class-Incremental Learning. [pdf] [code]
- ‼️ 2025.04 | 1 paper was accepted by IEEE TCSVT 2025: Few-Shot Class-Incremental Learning via Asymmetric Supervised Contrastive Learning. [paper]
- ‼️ 2025.03 | 1 paper was accepted by ICME 2025: Controllable Continual Test-Time Adaptation. [arxiv] [code]
- ‼️ 2025.02 | 3 paper was accepted by CVPR 2025:
- 2025.02 | 1 survey was accepted by JIG 2025: A Comprehensive Survey on Continual Learning. [paper]
- 2025.02 | Our book of continual learning is published: Continual Artificial Intelligence towards Changing Environment.
- 2025.01 | 1 paper was accepted by AAAI 2025: Rebalancing Multi-Label Class-Incremental Learning. [pdf]
- 2024.07 | 1 paper was accepted by ECCV 2024: Confidence Self-Calibration for Multi-Label Class-Incremental Learning. [pdf]
- 2024.06 | 1 paper was accepted by IEEE TCSVT 2024: Overcoming Modality Bias in Question-Driven Sign Language Video Translation. [paper] [code]
📡 Research Interest
- Open-World AI: Developing AI that maintains effectiveness in dynamic and ever-changing environments
- Sustaintable AI: Ensuring AI systems remain effective and adaptive over the long term
🏹 Research Projects
- National Science Foundation of China (NSFC), 2024~2027.
- China Postdoctoral Science Foundation (CPSF), 2024~2026.
- Postdoctoral Fellowship Program of CPSF, 2023~2025.
