About Me
I am currently a PhD student (from fall, 2021) at the School of Software of Tsinghua University and a member of the THUML, advised by Prof. MingSheng Long.
My research interests cover Time Series Analysis and Deep Learning. I am currently working on foundation time series models, large time series models, and multi-modal time series models. In addition to pure research, I also dedicate myself to promoting research on valuable real-world applications. My research aims to contribute to the advancement of intelligent systems capable of handling massive and complicated temporal data across domains, including finance, healthcare, industry, and environment.
For more information, you may take a look at my Google Scholar and GitHub.
News
- [Sept. 2024] Two papers (AutoTimes and TimeXer) were accepted in NeurIPS 2024.
- [Jun. 2024] Large model for time series (Timer) was accepted in ICML 2024. Code is available!
- [Jan. 2024] Multivariate deep forecaster (iTransformer) was accepted as ICLR 2024 Splotlight.
- [Dec 2023] Native AI analytical engine (AINode) in time-series database (Apache IoTDB) is released!
Publications & Preprints
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arXiv
Yong Liu*, Guo Qin*, Xiangdong Huang, Jianmin Wang, Mingsheng Long#
arXiv preprint, 2024.
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ICML
Yong Liu*, Haoran Zhang*, Chenyu Li*, Xiangdong Huang, Jianmin Wang, Mingsheng Long#
International Conference on Machine Learning, 2024.
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NeurIPS
Yong Liu*, Guo Qin*, Xiangdong Huang, Jianmin Wang, Mingsheng Long#
Conference on Neural Information Processing Systems, 2024.
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ICLR
Yong Liu*, Tengge Hu*, Haoran Zhang*, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long#
International Conference on Learning Representations, 2024.
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NeurIPS
Yuxuan Wang*, Haixu Wu*, Jiaxiang Dong, Guo Qin, Haoran Zhang, Yong Liu, Yunzhong Qiu, Jianmin Wang, Mingsheng Long#
Conference on Neural Information Processing Systems, 2024.
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ICLR
Haiwu Wu*, Tengge Hu*, Yong Liu*, Hang Zhou, Jianmin Wang, Mingsheng Long#
International Conference on Learning Representations, 2023.
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arXiv
Yuxuan Wang*, Haixu Wu*, Jiaxiang Dong, Yong Liu, Mingsheng Long, Jianmin Wang#
arXiv preprint, 2024.
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NeurIPS
Yong Liu*, Chenyu Li*, Jianmin Wang, Mingsheng Long#
Conference on Neural Information Processing Systems, 2023.
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NeurIPS
Yong Liu*, Haiwu Wu*, Jianmin Wang, Mingsheng Long#
Conference on Neural Information Processing Systems, 2022.
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JMLR
Kaichao You*, Yong Liu*, Ziyang Zhang, Jianmin Wang, Michael I. Jordan, Mingsheng Long#
Journal of Machine Learning Research, 2022.
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ICML
Kaichao You*, Yong Liu*, Jianmin Wang, Mingsheng Long#
International Conference on Machine Learning, 2021.
Selected Projects
Deep Models for Time Series
- iTransformer - Foundation Multivariate Time Series Model.
- Timer - Datasets, Checkpoints, Code for Developing Large Time Series Model.
- Non-stationary Transformers - Transformers for Non-stationary Forecasting.
- Koopa - Theory-inspired efficient non-stationary time series forecaster.
Algorithm Library
System and Applications
Invited Talks
- Exploring Large Models for Time Series at IoA, CAS. [Slides]
- Deep Learning for Time Series Applications at DoA, THU. [Slides]
- Large Models for Native Database Analysis at TPCTC 2024. [PDF]
Services
Academic Services
- Conference Reviewer, International Conference on Learning Representations (ICLR) 2024.
- Conference Reviewer, International Conference on Machine Learning (ICML) 2022-2024.
- Conference Reviewer, International Conference on Machine Learning (CVPR) 2023.
- Conference Reviewer, International Conference on Very Large Databases (VLDB) 2023.
- Conference Reviewer, Conference on Neural Information Processing Systems (NeurIPS) 2023-2024.
Teaching Experiences
- Teaching Assistant, Database System, Spring 2024, Prof. Jianmin Wang.
- Teaching Assistant, Machine Learning, Fall 2023, Prof. Mingsheng Long.
- Teaching Assistant, Introduction to Artificial Intelligence, Spring 2023, Prof. Mingsheng Long.
- Teaching Assistant, Deep Learning, Fall 2022, Prof. Mingsheng Long.
- Teaching Assistant, Introduction to Artificial Intelligence, Spring 2022, Prof. Mingsheng Long.
- Teaching Assistant, Machine Learning, Fall 2021, Prof. Mingsheng Long.
- Teaching Assistant, Introduction to Artificial Intelligence, Spring 2021, Prof. Mingsheng Long.
Education
Honors & Awards
- Outstanding Papers of Beijing (北京市优秀毕业论文, Top 1%). 2021.
- Outstanding Graduates of Beijing (北京市优秀毕业生, Top 1%). 2021.
- Excellent Graduates of Tsinghua (清华大学优秀毕业生, Top 1%). 2021.
- Future Scholar Scholarship (未来学者奖学金, Top 1%), Tsinghua University, 2021.
- Shenzhen Stock Exchange Scholarship (深交所奖学金, Top 1%). 2023.
- Boeing Scholarship (波音奖学金, Top 1%), Tsinghua University, 2020.
- Tang Lixin Scholarship (唐立新优秀奖学金, Top 1%), Tsinghua University, 2020.
- Jiang Nanxiang Scholarship (蒋南翔奖学金, Top 1%), Tsinghua University, 2019.
- Huawei Scholarship (华为奖学金, Top 1%), Tsinghua University, 2018.
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