avatar

邱翔飞

博士生
华东师范大学
xfqiu@stu.ecnu.edu.cn 邮箱
qxf780310 微信
Google Scholar Scholar DBLP DBLP GitHub GitHub LinkedIn LinkedIn Xiaohongshu XHS ORCID ORCID 简历 简历

👋 关于我

我目前是 华东师范大学 数据科学与工程学院 的博士研究生（2023 年秋季入学），隶属于 决策智能实验室，导师为 胡吉林教授 和 杨彬教授。同时，我也与 Christian S. Jensen 教授 保持密切合作。

🔍 研究方向

我的研究兴趣主要集中在时间序列分析与深度学习。目前重点关注时间序列基础模型与时间序列评测基准，同时也持续推进面向真实应用场景的研究工作。我的目标是构建能够处理大规模、复杂时序数据的智能系统，并推动其在金融、工业、环境等领域中的落地应用。更多信息可参考我的 Google Scholar Google Scholar Citations 和 GitHub GitHub Stars。

🔥 最新动态

  • [2026 年 4 月] 时间序列应用平台 EasyTime, ICDE 2025 被 Paper Digest 评为 最具影响力论文（397 篇接收论文中排名第 1）。
  • [2026 年 1 月] 我们的论文 “GCGNet” 和 “ASTGI” 被 ICLR 2026 接收。
  • [2025 年 12 月] 我入选 中国科协青年人才培育工程博士生专项计划。
  • [2025 年 12 月] 时间序列模型 DUET, KDD 2025 被 Paper Digest 评为 最具影响力论文。
  • [2025 年 11 月] 我们的论文 “Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline” 被 AAAI 2026 接收，并获 oral presentation。
  • [2025 年 10 月] 我们的论文 “EDAD: An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data” 被 ICDE 2026 接收。
  • [2025 年 10 月] 我获得 国家奖学金。
  • [2025 年 9 月] 我们的论文 “SRSNet” 和 “DBLoss” 被 NeurIPS 2025 接收，其中一篇为 Spotlight，一篇为 Poster。
  • [2025 年 6 月] 我获得 SIGKDD 2025 Research Track Outstanding Reviewer 和 Applied Data Science Track Excellent Reviewer。
  • [2025 年 5 月] 我获得 CCF优秀大学生学术秀硕士组冠军。
  • [2025 年 5 月] 我的论文 “TAB: Unified Benchmarking of Time Series Anomaly Detection Methods” 被 PVLDB 2025 接收。
  • [2025 年 5 月] 我们的论文 “TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting” 被 SIGKDD 2025 接收。
  • [2025 年 5 月] 我们的论文 “SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation” 被 SIGKDD 2025 接收。
  • [2025 年 5 月] 我的论文 “K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting” 被接收为 ICML 2025 Spotlight。
  • [2025 年 1 月] 我们的论文 “CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching” 被 ICLR 2025 接收。
  • [2024 年 12 月] 我的论文 “EasyTime: Time Series Forecasting Made Easy” 被 ICDE 2025 接收。
  • [2024 年 11 月] 我的论文 “DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting” 被 SIGKDD 2025 接收。
  • [2024 年 10 月] 我获得 国家奖学金。
  • [2024 年 8 月] 我的论文 “TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods” 获得 VLDB 2024 最佳论文奖提名。
  • [2024 年 8 月] 我们发布了时间序列分析排行榜项目 OpenTS。


📝 论文与预印本

  1. TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods 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 博客 🏆 PVLDB, CCF A, Accepted (Best Paper Award Nomination)
  2. TAB: Unified Benchmarking of Time Series Anomaly Detection Methods 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. TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting 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 博客 SIGKDD, CCF A, Accepted
  1. GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables ICLR
    GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
    Zhengyu Li, Xiangfei Qiu, Yuhan Zhu, Xingjian Wu, Jilin Hu, Chenjuan Guo, Bin Yang
    International Conference on Learning Representations, 2026.
    PDF ICLR, CCF A, Accepted
  2. ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting ICLR
    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
    International Conference on Learning Representations, 2026.
    PDF ICLR, CCF A, Accepted
  3. Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline 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 博客 ✨ AAAI, CCF A, Accepted (Oral, Top 4%)
  4. Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective 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 博客 ✨ NeurIPS, CCF A, Accepted (Spotlight, Top 3.2%)
  5. DBLoss: Decomposition-based Loss Function for Time Series Forecasting 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 博客 NeurIPS, CCF A, Accepted
  6. K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting 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 博客 ✨ ICML, CCF A, Accepted (Spotlight, Top 2.6%)
  7. EasyTime: Time Series Forecasting Made Easy 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)
  8. DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting 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 博客 🏆 SIGKDD, CCF A, Accepted (PaperDigest Most Influential Paper)
  9. AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting 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 博客 VLDBJ, CCF A, Accepted
  10. DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables arXiv
    DAG: A Dual Correlation 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
  11. Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting arXiv
    Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
    Xiangfei Qiu, Kangjia Yan, Xvyuan Liu, Xingjian Wu, Jilin Hu#
    arXiv preprint, 2026.
    PDF
  12. SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement arXiv
    SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
    Xiangfei Qiu, Xvyuan Liu, Tianen Shen, Xingjian Wu, Hanyin Cheng, Bin Yang, Jilin Hu#
    arXiv preprint, 2026.
    PDF
  13. Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting arXiv
    Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
    Xiangfei Qiu, Liu Yang, Xiangyu Xu, Hanyin Cheng, Xingjian Wu, Rongjia Wu, Zhigang Zhang, Ding Tu, Chenjuan Guo, Bin Yang, Christian S. Jensen, Jilin Hu#
    arXiv preprint, 2025.
    PDF
  14. MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models arXiv
    MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models
    Xiaoyun Yu*, Li Fan*, Xiangfei Qiu, Nanqing Dong, Yonggui Huang, Honggang Qi, Geguang Pu, Wanli Ouyang, Xi Chen#, Jilin Hu#
    arXiv preprint, 2026.
    PDF
  15. LightGTS-Cov: Covariate-Enhanced Time Series Forecasting arXiv
    LightGTS-Cov: Covariate-Enhanced Time Series Forecasting
    Yong Shang, Zhipeng Yao, Ning Jin, Xiangfei Qiu, Hui Zhang, Bin Yang
    arXiv preprint, 2026.
    PDF
  1. An Encode-then-Decompose Approach to Unsupervised Time Series Anomaly Detection on Contaminated Training Data 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. CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching 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 博客 ICLR, CCF A, Accepted
  3. MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast 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 博客
  1. SSD-TS: Exploring the potential of linear state space models for diffusion models in time series imputation 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. A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective arXiv
    A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective
    Xiangfei Qiu, Hanyin Cheng, Xingjian Wu, Junkai Lu, Jilin Hu, Chenjuan Guo, Christian S. Jensen, Bin Yang
    arXiv preprint, 2025.
    PDF Code 博客
  3. TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation arXiv
    TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation
    Xingjian Wu, Junkai Lu, Zhengyu Li, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Christian S. Jensen, Bin Yang, Bin Yang#
    arXiv preprint, 2025.
    PDF
  4. Task-Aware Mixture-of-Experts for Time Series Analysis arXiv
    Task-Aware Mixture-of-Experts for Time Series Analysis
    Xingjian Wu, Zhengyu Li, Hanyin Cheng, Xiangfei Qiu, Jilin Hu, Chenjuan Guo, Bin Yang#
    arXiv preprint, 2025.
    PDF
  5. FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting 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
  6. ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies arXiv
    ST-EVO: Towards Generative Spatio-Temporal Evolution of Multi-Agent Communication Topologies
    Xingjian Wu, Xvyuan Liu, Junkai Lu, Siyuan Wang, Xiangfei Qiu, Yang Shu, Jilin Hu, Chenjuan Guo, Bin Yang
    arXiv preprint, 2026.
    PDF

* 表示共同一作，# 表示通讯作者

💻 应用项目

📖 学术服务

会议程序委员会 / 审稿服务

期刊审稿

教学经历

🎖 荣誉奖项

👀 访客统计


由 Jekyll 和 Minimal Light 主题驱动。