I am currently an Assistant Professor at the Department of Psychological and Cognitive Sciences, Tsinghua University. Before that, I received both the BS degree (Aug 2013 - Jul 2017, advised by Prof. Yi Zhong) and PhD degree (Aug 2019 - Jul 2023, co-advised by Prof. Yi Zhong and Prof. Jun Zhu) from Tsinghua University, where I also conducted my postdoc research (Jul 2023 - Jul 2025, working with Prof. Jun Zhu). I have an interdisciplinary background in neuroscience and machine learning. My primary research interest lies in the development of bio-inspired machine learning methodologies and generic computational models for neuroscience. The current focus includes continual / incremental / lifelong learning and transfer learning, by exploring “natural algorithms” in biological learning and memory. I’m also exploring AI algorithms that serve other scientific domains. Welcome discussion and collaboration if you are interested in my research.

My email address is changed to liyuanwang@tsinghua.edu.cn and wly19@tsinghua.org.cn.

Recent News

• 2026/05 Three papers are accepted to ICML.
• 2026/04 One paper is accepted (in principle) to Nature Communications.
• 2026/04 One paper is accepted to Patterns (as the cover).
• 2026/03 I will serve as an Action Editor for TMLR.
• 2026/02 Two papers are accepted to CVPR 2026.
• 2026/01 Two papers are accepted to ICLR 2026.
• 2025/11 I received the CFAA Award for our continual learning survey.
• 2025/11 I will serve as an Area Chair at ICML 2026.
• 2025/10 One paper is accepted to Nature Machine Intelligence.
• 2025/07 I received the WAIC Youth Outstanding Paper Award.
• 2025/06 I was awarded the CAAI Rising Scientist.
• 2025/05 We are organizing the 6th CLVision Workshop in ICCV 2025.
• 2025/04 One paper is accepted to IEEE TPAMI.
• 2025/04 I will serve as an Area Chair at NeurIPS 2025.
• 2024/09 I received the Excellent Conference Poster Award in CNS 2024.
• 2024/06 I was awarded the WAIC Rising Star.
• 2023/12 One paper is published in Nature Machine Intelligence (as the cover).

Selected Publications and Preprints

• Continual Action Quality Assessment via Adaptive Manifold-Aligned Graph Regularization.
  Kanglei Zhou, Qingyi Pan, Xingxing Zhang, Hubert PH Shum, Frederick WB Li, Xiaohui Liang, Liyuan Wang$^\dagger$.
  arXiv:2510.06842, Under Review, 2026.

• Domain Generalizable Continual Learning.
  Hongwei Yan, Guanglong Sun, Zhiqi Kang, Yi Zhong, Liyuan Wang$^\dagger$.
  arXiv:2510.16914, Under Review, 2026.

• From Reactive to Cognitive: Brain-Inspired Spatial Intelligence for Embodied Agents.
  Shouwei Ruan$^{\ast}$, Liyuan Wang$^{\ast}$, Caixin Kang, Qihui Zhu, Songming Liu, Xingxing Wei, Hang Su.
  Accepted in Principle to Nature Communications, 2026.

• Spacing Effect Improves Generalization in Biological and Artificial Systems.
  Guanglong Sun, Ning Huang, Hongwei Yan, Jun Zhou, Qian Li, Bo Lei, Yi Zhong, Liyuan Wang$^\dagger$.
  Patterns, Cover Paper, 2026.

• CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning.
  Hongwei Yan, Kanglei Zhou, Yuchen Liu, Qingyu Shi, Yi Zhong, Liyuan Wang$^{\dagger}$.
  International Conference on Machine Learning (ICML), 2026.

• MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning.
  Guanglong Sun, Hongwei Yan, Liyuan Wang$^{\dagger}$, Zhiqi Kang, Shuang Cui, Hang Su, Jun Zhu, Yi Zhong$^{\dagger}$.
  International Conference on Machine Learning (ICML), 2026.

• Position: Modular Memory is the Key to Continual Learning Agents.
  Vaggelis Dorovatas, …, Liyuan Wang, Joost van de Weijer, Jonghyun Choi, Martin Mundt, Rahaf Aljundi.
  International Conference on Machine Learning (ICML), Spotlight, 2026.

• BriMA: Bridged Modality Adaptation for Multi-Modal Continual Action Quality Assessment.
  Kanglei Zhou, Chang Li, Liyuan Wang$^{\dagger}$.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

• Geometry-aware Cross-modal Graph Alignment for Referring Segmentation in 3D Gaussian Splatting.
  Yuwen Tao, Kanglei Zhou, Chang Li, Liyuan Wang.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

• PACE: Pretrained Audio Continual Learning.
  Chang Li, Kanglei Zhou, Liyuan Wang$^{\dagger}$.
  International Conference on Learning Representations (ICLR), 2026.

• FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning.
  Hongwei Yan, Guanglong Sun, Kanglei Zhou, Qian Li, Liyuan Wang$^{\dagger}$, Yi Zhong$^{\dagger}$.
  International Conference on Learning Representations (ICLR), 2026.

• Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer.
  Zehua Chen$^{\ast}$, Yuyang Miao$^{\ast}$, Liyuan Wang$^{\ast\dagger}$, Luyun Fan, Danilo P. Mandic, Jun Zhu$^{\dagger}$.
  Nature Machine Intelligence, 2025.

• HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning.
  Liyuan Wang, Jingyi Xie, Xingxing Zhang, Hang Su, Jun Zhu.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.

• LUNCH: Adaptive Task Balancing for Online Continual Learning via Hyperparameter Uncertainty.
  Qingyi Pan, Liyuan Wang$^\dagger$, Jingyi Zhang, Jun Zhu$^\dagger$.
  Science China Information Sciences (SCIS), 2025.

• Trend Virtual Adversarial Training for Semi-Supervised Time Series Classification.
  Qingyi Pan, Liyuan Wang$^\dagger$, Jingyi Zhang, Jun Zhu, Ning Chen$^\dagger$.
  Science China Information Sciences (SCIS), 2025.

• DualTeacher: Bridging Coexistence of Unlabelled Classes for Semi-supervised Incremental Object Detection.
  Ziqi Yuan$^{\ast}$, Liyuan Wang$^{\ast}$, Wenbo Ding, Xingxing Zhang, Jiachen Zhong, Jianyong Ai, Jianmin Li, Jun Zhu.
  Science China Information Sciences (SCIS), 2025.

• Convergent Multi-Modular Architecture for Adaptive Learning in Drosophila and Artificial Intelligence.
  Liyuan Wang$^\dagger$, Qian Li$^\dagger$.
  iScience, 2025.

• Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation.
  Guanglong Sun, Hongwei Yan, Liyuan Wang$^{\dagger}$, Qian Li, Bo Lei, Yi Zhong.
  International Conference on Machine Learning (ICML), 2025.

• Advancing Prompt-based Methods for Replay-Independent General Continual Learning.
  Zhiqi Kang, Liyuan Wang$^{\dagger}$, Xingxing Zhang, Karteek Alahari$^{\dagger}$.
  International Conference on Learning Representations (ICLR), 2025.

• A Comprehensive Survey of Continual Learning: Theory, Method and Application.
  Liyuan Wang, Xingxing Zhang, Hang Su, Jun Zhu.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Popular Documents (Top 0.1%), 2024.

• MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment.
  Kanglei Zhou, Liyuan Wang, Xingxing Zhang, Hubert Shum, Frederick Li, Jianguo Li, Xiaohui Liang.
  European Conference on Computer Vision (ECCV), Oral, 2024.

• Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation.
  Hongwei Yan, Liyuan Wang$^{\dagger}$, Kaisheng Ma$^{\dagger}$, Yi Zhong$^{\dagger}$.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

• Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence.
  Liyuan Wang$^{\ast}$, Xingxing Zhang$^{\ast}$, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, Yi Zhong.
  Nature Machine Intelligence, Cover Paper, 2023.

• Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality.
  Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, Jun Zhu.
  Neural Information Processing Systems (NeurIPS), Spotlight, 2023.

• Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation.
  Yilin Lyu$^{\ast}$, Liyuan Wang$^{\ast}$, Xingxing Zhang, Zicheng Sun, Hang Su, Jun Zhu, Liping Jing.
  Neural Information Processing Systems (NeurIPS), 2023.

• SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model.
  Gengwei Zhang$^{\ast}$, Liyuan Wang$^{\ast}$, Guoliang Kang, Ling Chen, Yunchao Wei.
  International Conference on Computer Vision (ICCV), 2023.

• Genetic Dissection of Mutual Interference between Two Consecutive Learning Tasks in Drosophila.
  Jianjian Zhao, Xuchen Zhang, Bohan Zhao, Wantong Hu, Tongxin Diao, Liyuan Wang, Yi Zhong, Qian Li.
  eLife, 2023.

• CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One.
  Liyuan Wang$^{\ast}$, Xingxing Zhang$^{\ast}$, Qian Li, Jun Zhu, Yi Zhong.
  European Conference on Computer Vision (ECCV), 2022.

• Memory Replay with Data Compression for Continual Learning.
  Liyuan Wang$^{\ast}$, Xingxing Zhang$^{\ast}$, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu.
  International Conference on Learning Representations (ICLR), 2022.

• AFEC: Active Forgetting of Negative Transfer in Continual Learning.
  Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong.
  Neural Information Processing Systems (NeurIPS), 2021.

• ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning.
  Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

• Triple-Memory Networks: A Brain-Inspired Method for Continual Learning.
  Liyuan Wang, Bo Lei, Qian Li, Hang Su, Jun Zhu, Yi Zhong.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

• Few-shot Continual Learning: a Brain-inspired Approach.
  Liyuan Wang, Qian Li, Yi Zhong, Jun Zhu.
  arXiv:2104.09034, 2021.

Academic Services

• Journal Editor: TMLR (2026)
• Organizer: CoLLAs (2026), ICCV 6th CLVision Workshop (2025), ISNN Continual Learning Forum (2024)
• Conference Area Chair: NeurIPS (2025), ICLR (2026), ICML (2026)
• Conference Reviewer: NeurIPS (2021, 2022, 2023, 2024), ICML (2024, 2025), ICLR (2022, 2023, 2024, 2025), CVPR (2022, 2023, 2024, 2025, 2026), ICCV (2023, 2025), ECCV (2022, 2024, 2026), AAAI (2025), IJCAI (2024), ACM MM (2022, 2023), CogSci (2024, 2025), CoLLAs (2023, 2024, 2025)
• Journal Reviewer: PNAS, TPAMI, IJCV, TAFFC, TIP, TNNLS, TCSVT, TETCI, TAI, SCIS, ACM Computing Surveys, Artificial Intelligence, Neural Networks, Neurocomputing

Honors and Awards

• Capital Frontier Academic Achievements (CFAA), 2025.
• World AI Conference (WAIC) Youth Outstanding Paper Award, 2025.
• Chinese Association for Artificial Intelligence (CAAI) Rising Scientist, 2025.
• CNS-RWD Award for Excellent Conference Poster, 2024.
• World AI Conference (WAIC) Rising Star, 2024.
• Shuimu Tsinghua Scholar for Postdoc Researcher, 2023.
• National Scholarship for Graduate Student, 2022.
• Beijing Outstanding Graduate Award, 2017.
• Tsinghua Outstanding Graduate Award, 2017.
• National Scholarship for Undergraduate Student, 2014, 2015, 2016.