🏷 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
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. CCF A.
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.
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. CCF A.
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. CORE A*.
Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Jilin Hu, Chenjuan Guo
arXiv preprint, 2025.
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. CCF A.
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. CCF A.
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. CCF A.
Xinle Wu*, Xingjian Wu*, Bin Yang#, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen
VLDB Journal (VLDBJ), 2024. CCF A.
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. CCF A.
*Equal Contribution, # Corresponding Author. More working drafts / preprints under review will be released later ⌛️
🎖 Honors and Awards
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2024.10 National Scholarship
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2024.11 Outstanding Student of East China Normal University
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2024.08 VLDB Best Research Paper Award Nomination
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2023.08 Outstanding Graduate of Shanghai University
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2023.06 Ministry of Education-Huawei, Future Star Scholarship
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2022.12 ASC STUDENT SUPERCOMPUTER CHALLENGE, (International Second Prize)
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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.