Hi! I am a third-year PhD student at PAttern Recognition and NEural Computing (PARNEC) group, NUAA where I am fortunate enough to be advised by Prof. Songcan Chen who is also the leader of PARNEC group.

My research interests lie broadly in Machine Learning, especially Continual Learning Theory and Weakly Supervised Learning – check my Google Scholar for more information. I am open to other topics, so feel free to reach out if you’d like to chat!

Recent News

• June, 2025 You Never Walk Alone: A Generalizable and Non-Parametric Structure Learning Framework. accepted to TNNLS.

• May, 2025 Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning. accepted to ICML 2025.

• April, 2025 LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data. accepted to IJCAI 2025.

• April, 2025 Filter, Obstruct and Dilute: Defending Against Backdoor Attacks on Semi-Supervised Learning. is online.

• Feb, 2025 Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. accepted to AISTATS 2025.

• Sep, 2024 Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning. accepted to NeurIPS 2024.

• Jan, 2024 Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels. accepted to SCIENCE CHINA Information Sciences.

• Jan, 2024 Adaptive federated minimax optimization with lower complexities. accepted to AISTATS 2024.

• Dec, 2023 Unlocking the Power of Open Set: A New Perspective for Open-set Noisy Label Learning. accepted to AAAI 2024.

• Sep, 2023 Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends. accepted to NeurIPS 2023.

Academic Services

• Conference Reviewing: NeurIPS 2024/2025, ICLR 2025, AISTATS 2025, CVPR 2025, ICML 2025.