🏷 About Me

Educational Experience

2016 - 2019 | High School Affiliated to Fudan University
2019 - 2023 | School of Computer Engineering and Science, Shanghai University
2023 - Present | School of Data Science and Engineering of East China Normal University and a member of the Decision Intelligence Lab, advised by Prof. Bin Yang

Research Interests

My research interests cover Time Series Analysis and Spatio-Temporal data management. I am currently working on foundation time series models, and generative probabilistic modeling. For more information, you may take a look at my Google Scholar and GitHub.

🔥 News

  • 2025.05: ⭐️⭐️ Our paper "TAB: Unified Benchmarking of Time Series Anomaly Detection Methods" has been accepted by PVLDB 2025!
  • 2025.05: 🎉🎉 Our paper "K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting" has been accepted as a Spotlight Poster by ICML 2025!
  • 2025.01: 🎈🎈 Our paper "CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching" has been accepted by ICLR 2025!
  • 2024.12: 🏖️🏖️ Our paper "EasyTime: Time Series Forecasting Made Easy" has been accepted by ICDE 2025!
  • 2024.11: 🤖🤖 Our paper "DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting" has been accepted by SIGKDD 2025
  • 2024.10: ⭐️⭐️ I have been awarded the National Scholarship!
  • 2024.08: 🎉🎉 Our paper "TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods" receives VLDB 2024 Best Research Paper Award Nomination!
  • 2024.08: 🥂🥂 The AutoCTS series is integrated into the leaderboard for time series analytics, called OpenTS
  • 2024.07: 📑📑 Our paper "FACTS: Fully Automated Correlated Time Series Forecasting in Minutes" has been accepted by PVLDB 2025
  • 2024.07: 🎓🎓 Our paper "AutoCTS++: Zero-shot Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting" has been accepted by VLDBJ 2024.

📝 Publications

ICML 2025 Spotlight
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K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting

Xingjian Wu*, Xiangfei Qiu*, Hongfan Gao, Jilin Hu, Chenjuan Guo, Bin Yang#

International Conference on Machine Learning (ICML), 2025.

[Paper] | [Project]

Preprint
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Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline

Xvyuan Liu*, Xiangfei Qiu*, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu#, Bin Yang

arXiv preprint, 2025.

PVLDB 2025
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TAB: Unified Benchmarking of Time Series Anomaly Detection Methods

Xiangfei Qiu, Zhe Li, Wanghui Qiu, Shiyan Hu, Lekui Zhou, Xingjian Wu, Zhengyu Li Chenjuan Guo, Aoying Zhou, Zhenli Sheng, Jilin Hu#, Christian S. Jensen, Bin Yang

International Conference on Very Large Databases (PVLDB), 2025.

ICLR 2025
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CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching

Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang#

International Conference on Learning Representations (ICLR), 2025.

[Paper] | [Slides] | [Project]

Preprint
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A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective

Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Jilin Hu, Chenjuan Guo

arXiv preprint, 2025.

[Paper] | [Project]

ICDE 2025
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EasyTime: Time Series Forecasting Made Easy

Xiangfei Qiu*, Xiuwen Li*, Ruiyang Pang*, Zhicheng Pan*, Xingjian Wu*, Liu Yang*, Jilin Hu, Yang Shu, Xuesong Lu, Chengcheng Yang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen and Bin Yang#.

IEEE International Conference on Data Engineering (ICDE), 2025.

[Paper] | [Project]

SIGKDD 2025
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DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

Xiangfei Qiu, Xingjian Wu, Yan Lin, Chenjuan Guo, Jilin Hu#, Bin Yang

ACM Knowledge Discovery and Data Mining (SIGKDD), 2025.

[Paper] | [Project]

PVLDB 2025
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FACTS: Fully Automated Correlated Time Series Forecasting in Minutes

Xinle Wu, Xingjian Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang#, Christian S Jensen

International Conference on Very Large Databases (PVLDB), 2025.

[Paper] | [Project]

VLDBJ 2024
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AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting

Xinle Wu*, Xingjian Wu*, Bin Yang#, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen

VLDB Journal (VLDBJ), 2024.

[Paper] | [Project]

PVLDB 2024
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TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

Xiangfei Qiu, Jilin Hu#, Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, Bin Yang

International Conference on Very Large Databases (PVLDB), 2024.

[Paper] | [Project]

*Equal Contribution, # Corresponding Author. More working drafts / preprints under review will be released later ⌛️

🎖 Honors and Awards

  • 2024.10 National Scholarship

  • 2024.11 Outstanding Student of East China Normal University

  • 2024.08 VLDB Best Research Paper Award Nomination

  • 2023.08 Outstanding Graduate of Shanghai University

  • 2023.06 Ministry of Education-Huawei, Future Star Scholarship

  • 2022.12 ASC STUDENT SUPERCOMPUTER CHALLENGE, (International Second Prize)

  • 2021.10 Outstanding Student of Shanghai University

💬 Invited Talks

  • 2025.04 Conduct a popular science lecture on large language models for Shanghai No.1 Welfare Institute (a department - level unit).
  • 2025.03 Conduct a popular science lecture on large language models for Shanghai Art & Design Academy (a department - level unit).

💻 Applications

  • AutoCTS series: AutoML for Time Series analytics.
  • EasyTime: Time Series Forecasting Made Easy.

📖 Services

  • 2025.02 International Joint Conference on Artificial Intelligence (IJCAI), (Main & Survey Track).
  • 2024.12 International Conference on Learning Representations (ICLR).