My research aims at creating strong learning machines that adapt to complex real world. I am working on transfer learning, out-of-distribution (OOD) generalization, domain adaptation and few-shot learning. I am also interested in related topics in machine learning and deep learning, such as foundation models, time series analysis and multi-modal learning.
I am currently an Assistant Professor, Chenhui Scholar, in School of Data Science and Engineering, East China Normal University. I received my Ph.D. degree from School of Software, Tsinghua University, advised by Mingsheng Long. I received my B.S. degree from Department of Automation, Tsinghua University.
Preprints
- Transferability in Deep Learning: A Survey
Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long*
[Paper]
[Website]
Publications
- Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao*, Lujia Pan, Bin Yang, Chenjuan Guo*
International Conference on Machine Learning (ICML), 2025 (accepted)
- LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo
International Conference on Machine Learning (ICML), 2025 (accepted)
- Enhancing Diversity for Data-free Quantization
Kai Zhao, Zhihao Zhuang, Miao Zhang, Chenjuan Guo*, Yang Shu, Bin Yang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (accepted, oral)
- AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification
Yuxuan Chen, Shanshan Huang, Yunyao Cheng, Peng Chen, Zhongwen Rao, Yang Shu*, Bin Yang,
Lujia Pan, Chenjuan Guo
IEEE International Conference on Data Engineering (ICDE), 2025
[Paper]
- AID-SQL: Adaptive In-Context Learning of Text-to-SQL with Difficulty-Aware Instruction and Retrieval-Augmented Generation
Xiuwen Li, Qifeng Cai, Yang Shu*, Chenjuan Guo, Bin Yang
IEEE International Conference on Data Engineering (ICDE), 2025 (accepted)
- Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
Qichao Shentu, Beibu Li, Kai Zhao, Yang Shu*, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo
International Conference on Learning Representations (ICLR), 2025
[Paper]
- Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
Sicong Liu, Yang Shu*, Chenjuan Guo, Bin Yang
International Conference on Learning Representations (ICLR), 2025
[Paper]
- RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems
Biao Ouyang, Yingying Zhang, Hanyin Cheng, Yang Shu*, Chenjuan Guo, Bin Yang, Qingsong Wen,
Lunting Fan, Christian S. Jensen
International Conference on Very Large Data Bases (VLDB), 2025
[Paper]
- Assessing Pre-trained Models for Transfer Learning through Distribution of Spectral Components
Tengxue Zhang, Yang Shu*, Xinyang Chen*, Yifei Long, Chenjuan Guo, Bin Yang
AAAI Conference on Artificial Intelligence (AAAI), 2025
[Paper]
- Boosting Transferability and Discriminability for Time Series Domain Adaptation
Mingyang Liu, Xinyang Chen*, Yang Shu*, Xiucheng Li*, Weili Guan, Liqiang Nie
Neural Information Processing Systems (NeurIPS), 2024
[Paper]
[Code]
- Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu*, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo
International Conference on Learning Representations (ICLR), 2024
[Paper]
[Code]
- Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning
Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long*
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
[Paper]
- CLIPood: Generalizing CLIP to Out-of-Distributions
Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long*
International Conference on Machine Learning (ICML), 2023
[Paper]
[Code]
- Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models
Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long*
Neural Information Processing Systems (NeurIPS), 2022
[Paper]
- Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long*
International Conference on Machine Learning (ICML), 2021
[Paper]
[Code]
- Open Domain Generalization with Domain-Augmented Meta-Learning
Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long*
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[Paper]
[Code]
- Transferable Curriculum for Weakly-Supervised Domain Adaptation
Yang Shu, Zhangjie Cao, Mingsheng Long*, Jianmin Wang
AAAI Conference on Artificial Intelligence (AAAI), 2019
[Paper]
[Code]
Academic Services
PC Member
- International Conference on Machine Learning (ICML), 2022, 2023, 2024, 2025
- Neural Information Processing Systems (NeurIPS), 2022, 2023, 2024, 2025
- International Conference on Learning Representations (ICLR), 2024, 2025
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, 2022, 2023
- IEEE International Conference on Computer Vision (ICCV), 2021, 2023, 2025
- European Conference on Computer Vision (ECCV), 2022, 2024
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
- AAAI Conference on Artificial Intelligence (AAAI), 2025
- ACM International Conference on Multimedia (ACMMM), 2025
- International Joint Conference on Artificial Intelligence (IJCAI), 2020
Reviewer
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- International Journal of Computer Vision (IJCV)
- Artificial Intelligence Journal (AIJ)
- Information Sciences
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
- IEEE Transactions on Industrial Informatics (TII)
- Transactions on Machine Learning Research (TMLR)
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