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Xiangfei Qiu

Phd Student
East China Normal University
Email: xfqiu@stu.ecnu.edu.cn
WeChat: qxf780310


👋 About Me

I am currently a Phd student (from fall, 2023) at the School of Data Science and Engineering of East China Normal University and a member of the Decision Intelligence Lab, advised by Prof. Jilin Hu and Prof. Bin Yang.

🔍 Research Topics

My research interests cover Time Series Analysis and Deep Learning. I am currently working on foundation time series models, and time series benchmarking. I have published several relevant papers in top conferences with total google scholar citations 670. 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, industry, and environment.

For more information, you may take a look at my Google Scholar and GitHub.

🔥 News

▶️ Click to Expand/Collapse
  • [May. 2025] My paper "TAB: Unified Benchmarking of Time Series Anomaly Detection Methods" has been accepted by PVLDB 2025.
  • [May. 2025] Our paper "TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting" has been accepted by SIGKDD 2025.
  • [May. 2025] Our paper "SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation" has been accepted by SIGKDD 2025.
  • [May. 2025] My paper "K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting" has been accepted as ICML 2025 Spotlight.
  • [Jan. 2025] Our paper "CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching" has been accepted by ICLR 2025.
  • [Dec. 2024] My paper "EasyTime: Time Series Forecasting Made Easy" has been accepted by ICDE 2025.
  • [Nov. 2024] My paper "DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting" has been accepted by SIGKDD 2025.
  • [Oct. 2024] I have been awarded the National Scholarship!
  • [Aug. 2024] My paper "TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods" receives VLDB 2024 Best Research Paper Award Nomination!
  • [Aug. 2024] We have created a leaderboard for time series analytics, called OpenTS.


📝 Publications & Preprints

📊 Time Series Benchmark

  1. PVLDB
    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, 2024.
    PDF Code BibTex Blog 🏆 PVLDB, CCF A, Accepted (Best Paper Award Nomination)

  2. PVLDB
    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, 2025.
    PDF Code PVLDB, CCF A, Accepted

  3. SIGKDD
    TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
    Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Qingsong Wen, Christian S. Jensen, Bin Yang
    ACM Knowledge Discovery and Data Mining, 2025.
    PDF Code Blog SIGKDD, CCF A, Accepted

📈 Time Series Forecasting

  1. AAAI
    Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline
    Xvyuan Liu*, Xiangfei Qiu*, Xingjian Wu*, Zhengyu Li, Chenjuan Guo, Jilin Hu, Bin Yang
    AAAI Conference on Artificial Intelligence, 2026.
    PDF Code ✨ AAAI, CCF A, Accepted (Oral, Top 4%)

  2. NeurIPS
    Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
    Xingjian Wu, Xiangfei Qiu, Hanyin Cheng, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang#
    PDF Code ✨ NeurIPS, CCF A, Accepted (Spotlight, Top 3.2%)

  3. NeurIPS
    DBLoss: Decomposition-based Loss Function for Time Series Forecasting
    Xiangfei Qiu, Xingjian Wu, Hanyin Cheng, Xvyuan Liu, Chenjuan Guo, Jilin Hu#, Bin Yang
    Neural Information Processing Systems Conference, 2025.
    PDF Code NeurIPS, CCF A, Accepted

  4. ICML
    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, 2025.
    PDF Code ✨ ICML, CCF A, Accepted (Spotlight, Top 2.6%)

  5. ICDE
    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, 2025.
    PDF 🏆 ICDE, CCF A, Accepted (PaperDigest Most Influential Paper)

  6. SIGKDD
    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, 2025.
    PDF Code BibTex Blog 🏆 SIGKDD, CCF A, Accepted (PaperDigest Most Influential Paper)

  7. VLDBJ
    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, 2024.
    PDF Code BibTex Blog VLDBJ, CCF A, Accepted

  8. arXiv
    DAG: A Dual Causal Network for Time Series Forecasting with Exogenous Variables
    Xiangfei Qiu, Yuhan Zhu, Zhengyu Li, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu#
    arXiv preprint, 2026.
    PDF Code

  9. arXiv
    Multi-Scale Spatial-Temporal Hypergraph Network with Lead-Lag Structures for Stock Time Series Forecasting
    Xiangfei Qiu, Liu Yang, Hanyin Cheng, Xingjian Wu, Rongjia Wu, Zhigang Zhang, Ding Tu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Jilin Hu#
    arXiv preprint, 2025.
    PDF

  10. arXiv
    ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting
    Xvyuan Liu, Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Chenjuan Guo, Bin Yang, Jilin Hu#
    arXiv preprint, 2025.
    PDF

🔍 Time Series Anomaly Detection

  1. ICDE
    An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data
    Buang Zhang, Tung Kieu, Xiangfei Qiu, Chenjuan Guo, Jilin Hu, Aoying Zhou, Christian S. Jensen, Bin Yang
    IEEE International Conference on Data Engineering, 2026.
    PDF ICDE, CCF A, Accepted

  2. ICLR
    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, 2025.
    PDF Code Blog ICLR, Core A*, Accepted

  3. arXiv
    MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast
    Shiyan Hu, Kai Zhao, Xiangfei Qiu, Yang Shu, Jilin Hu, Bin Yang, Chenjuan Guo#
    arXiv preprint, 2024.
    PDF Blog

💡 Others

  1. SIGKDD
    SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation
    Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Jilin Hu#, Bin Yang
    ACM Knowledge Discovery and Data Mining, 2025.
    PDF Code SIGKDD, CCF A, Accepted

  2. arXiv
    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, Bin Yang
    arXiv preprint, 2025.
    PDF Code Blog

  3. arXiv
    Unlocking the Power of Mixture-of-Experts for Task-Aware Time Series Analytics
    Xingjian Wu, Zhengyu Li, Hanyin Cheng, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Bin Yang#
    arXiv preprint, 2025.
    PDF

  4. arXiv
    FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
    Xingjian Wu, Hanyin Cheng, Xiangfei Qiu, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang#
    arXiv preprint, 2025.
    PDF

*Equal Contribution, # Corresponding Author

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