郭晨娟
联系电话：62235112
电子邮箱：cjguo@dase.ecnu.edu.cn
办公地点：数学馆东112室
通讯地址：上海市普陀区中山北路3663号华东师范大学数据科学与工程学院

  • 详细信息

  • 学术研究

个人简介    

郭晨娟，华东师范大学，数据科学与工程学院，教授、博士生导师。2021年入选国家级青年人才计划。英国曼彻斯特大学博士，曾任职丹麦奥尔堡大学，工程技术学院, 计算机系终身副教授。主要研究领域是数据管理和数据分析，涉及在智能交通，数字能源，和智能水资源管理等上的应用。已在主流知名国际会议和国际期刊上发表了多篇论文，包括Nature Communications， SIGMOD, VLDB，ICDE，IJCAI，AAAI，KDD，WWW，ICML，NeurIPS, ICLR，VLDB Journal, TKDE等。并担任IEEE TKDE、IEEE TMC等多个顶级期刊的专家审稿人，以及ICML，NeurIPS, ICLR，IJCAI、AAAI，ICDE，KDD，PVLDB等若干国际顶级会议的程序委员。  
   

     

职称    

教授，博士生导师。
         

决策智能实验室主页    

 https://decisionintelligence.github.io/    

 欢迎本科生、研究生、博士生、博士后加入实验室！    


   

专著：时序智能——面向时间序列分析的人工智能方法 正式上线！    


   

研究方向    

  • 数据管理与分析（Data Management and Analytics），机器学习（Machine Learning）

  • 时间序列分析（Time Series Analytics），时空序列分析（Spatio-Temporal Data Analytics），AI for Science

  • 时间序列基础模型（Time Series Foundation Models），自动机器学习（AutoML），多智能体（Multi-Agents）

   


科研项目    

  • 可解释的自动时间序列异常点预测，国家自然科学基金，2024-2027

  • 时间序列分析基础模型，华为校企合作项目，2023-2025

  • 多源异构数据的异常检测和根因分析，阿里巴巴校企合作项目，2023-2024

  • Time Series Analytics, 华为校企合作项目，2023-2024

  • 基于负载预测的云计算资源调度优化算法，阿里巴巴校企合作项目，2022-2023

  • 时空数据管理与分析，国家自然科学基金，2022-2025

  • Explainable AI for Complex Microbial Community Interactions and Predictions, funded by Villum Fonden, Denmark, in collaboration with Prof. Per Halkjær Nielsen, 2021 - 2024.

  • Light-AI for Cognitive Power Electronics, funded by Villum Fonden, Denmark, 2020-2023.

  • Time Series Analytics and Spatio-temporal Data Management, funded by Huawei, 2020 - 2022.

  • Advance: A Data-Intensive Paradigm for Dynamic, Uncertain Networks, funded by Independent Research Fund Denmark, 2019 - 2023.

  • Astra: AnalyticS of Time seRies in spAtial networks, funded by Independent Research Fund Denmark, 2018 - 2021.

  • Collaboration with BlipTrack, funded by Forskerpuljen, 2018.


               

Selected Papers:    

Full Lists: DBLP  Google Scholar     


   

  • Xvyuan Liu, Xiangfei Qiu, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu, Bin Yang: Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline. AAAI Oral (2026)  CCF-A

  • Junkai Lu, Peng Chen, Chenjuan Guo, Yang Shu, Meng Wang, Bin Yang: Towards Non-Stationary Time Series Forecasting with Temporal Stabilization and Frequency Differencing. AAAI (2026)  CCF-A

  • Ronghui Xu, Jihao chen, Jindong Tian, Chenjuan Guo, Bin Yang: MoST: A Foundation Model for Multi-modality Spatio-temporal Traffic Prediction. KDD (2026)   CCF-A

  • Kasper Skytte Andersen, Kai Zhao, Alexander de Linde Agerskov, Christian Bro Sørensen, Trine Juhl Holmager, Marta Nierychlo, Miriam Peces, Chenjuan Guo, Per Halkjær Nielsen: Predicting microbial community structure and temporal dynamics by using graph neural network models. Nature Communications, volume 16, Article number: 9124 (2025)

  • Beibu Li, Qichao Shentu, Yang Shu, Hui Zhang, Ming Li, Ning Jin, Bin Yang, Chenjuan Guo: CrossAD: Time Series Anomaly Detection with Cross-scale Associations and Cross-window Modeling. NeurIPS (2025)   CCF-A

  • Xingjian Wu, Xiangfei Qiu, Hanyin Cheng, Zhengyu Li, Jilin Hu, Chenjuan Guo, Bin Yang: Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective. NeurIPS spotlight (2025)   CCF-A

  • Siru Zhong, Junjie Qiu, Yangyu Wu, Xingchen Zou, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang: Learning to Factorize Spatio-Temporal Foundation Models. NeurIPS spotlight (2025)   CCF-A

  • Xiangfei Qiu, Xingjian Wu, Hanyin Cheng, Xvyuan Liu, Chenjuan Guo, Jilin Hu, Bin Yang: DBLoss: Decomposition-based Loss Function for Time Series Forecasting. NeurIPS (2025)   CCF-A

  • Kai Zhao, Zhihao Zhuang, Chenjuan Guo, Hao Miao, Yunyao Cheng, Bin Yang: Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning. KDD (2025)   CCF-A

  • Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo: LightGTS: A Lightweight General Time Series Forecasting Model. ICML (2025)   CCF-A

  • Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo: Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer. ICML (2025)   CCF-A

  • Xingjian Wu, Xiangfei Qiu, Hongfan Gao, Jilin Hu, Bin Yang, Chenjuan Guo: K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting. ICML (2025)   CCF-A

  • Zhe Li, Xiangfei Qiu, Peng Chen, Yihang Wang, Hanyin Cheng, Yang Shu, Jilin Hu, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Bin Yang: TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting. KDD (2025)   CCF-A

  • 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: TAB: Unified Benchmarking of Time Series Anomaly Detection Methods. Proc. VLDB Endow. 18(9): 2775-2789 (2025)   CCF-A

  • Hao Miao, Yan Zhao, Chenjuan Guo, Bin Yang, Kai Zheng, Christian S. Jensen: Spatio-Temporal Prediction on Streaming Data: A Unified Federated Continuous Learning Framework. IEEE Trans. Knowl. Data Eng. 37(4): 2126-2140 (2025)   CCF-A

  • Yunyao Cheng, Chenjuan Guo, Kaixuan Chen, Kai Zhao, Bin Yang, Jiandong Xie, Christian S. Jensen, Feiteng Huang, Kai Zheng: Gaussian Process Latent Variable Modeling for Few-Shot Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 37(8): 4604-4619 (2025)   CCF-A

  • Tengxue Zhang, Yang Shu, Xinyang Chen, Yifei Long, Chenjuan Guo, Bin Yang: Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components. AAAI (2025): 22560-22568  CCF-A

  • Kai Zhao, Zhihao Zhuang, Miao Zhang, Chenjuan Guo, Yang Shu, Bin Yang: Enhancing Diversity for Data-free Quantization. CVPR Oral (2025): 20969-20978   CCF-A

  • Yuxuan Chen, Shanshan Huang, Yunyao Cheng, Peng Chen, Zhongwen Rao, Yang Shu, Bin Yang, Lujia Pan, Chenjuan Guo: AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification. ICDE (2025): 1952-1965   CCF-A

  • Xiuwen Li, Qifeng Cai, Yang Shu, Chenjuan Guo, Bin Yang: AID-SQL: Adaptive In-Context Learning of Text-to-SQL with Difficulty-Aware Instruction and Retrieval-Augmented Generation. ICDE (2025): 3945-3957   CCF-A

  • Bin Yang, Yuxuan Liang, Chenjuan Guo, Christian S. Jensen: Data Driven Decision Making with Time Series and Spatio-Temporal Data. ICDE (2025): 4517-4522   CCF-A

  • 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, Bin Yang: EasyTime: Time Series Forecasting Made Easy. ICDE (2025): 4564-4567   CCF-A

  • Sicong Liu, Yang Shu, Chenjuan Guo, Bin Yang: Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation. ICLR (2025)

  • Qichao Shentu, Beibu Li, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo: Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders. ICLR (2025)

  • Jindong Tian, Yuxuan Liang, Ronghui Xu, Peng Chen, Chenjuan Guo, Aoying Zhou, Lujia Pan, Zhongwen Rao, Bin Yang: Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems. ICLR (2025)

  • Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang: CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching. ICLR (2025)

  • Xiangfei Qiu, Xingjian Wu, Yan Lin, Chenjuan Guo, Jilin Hu, Bin Yang: DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting. KDD (1) 2025: 1185-1196   CCF-A

  • Ronghui Xu, Hanyin Cheng, Chenjuan Guo, Hongfan Gao, Jilin Hu, Sean Bin Yang, Bin Yang: MM-Path: Multi-modal, Multi-granularity Path Representation Learning. KDD (1) 2025: 1703-1714   CCF-A

  • Xinle Wu, Xingjian Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen: Fully Automated Correlated Time Series Forecasting in Minutes. Proc. VLDB Endow. 18(2): 144-157 (2024)   CCF-A

  • Yunyao Cheng, Chenjuan Guo, Bin Yang, Haomin Yu, Kai Zhao, Christian S. Jensen: A Memory Guided Transformer for Time Series Forecasting. Proc. VLDB Endow. 18(2): 239-252 (2024)   CCF-A

  • Zhihao Zhuang, Yingying Zhang, Kai Zhao, Chenjuan Guo, Bin Yang, Qingsong Wen, Lunting Fan: Noise Matters: Cross Contrastive Learning for Flink Anomaly Detection. Proc. VLDB Endow. 18(4): 1159-1168 (2024)   CCF-A

  • Biao Ouyang, Yingying Zhang, Hanyin Cheng, Yang Shu, Chenjuan Guo, Bin Yang, Qingsong Wen, Lunting Fan, Christian S. Jensen: RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems. Proc. VLDB Endow. 18(4): 1169-1182 (2024)   CCF-A

  • Xiangfei Qiu, Jilin Hu, Lekui Zhou, Xingjian Wu, Junyang Du, Buang Zhang, Chenjuan Guo, Aoying Zhou, Christian S. Jensen, Zhenli Sheng, Bin Yang: TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods. Proc. VLDB Endow. 17(9): 2363-2377 (2024) CCF-A

  • David Campos, Bin Yang, Tung Kieu, Miao Zhang, Chenjuan Guo, Christian S. Jensen: QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models. Proc. VLDB Endow. 17(11): 2708-2721 (2024) CCF-A

  • Chenjuan Guo, Ronghui Xu, Bin Yang, Yuan Ye, Tung Kieu, Yan Zhao, Christian S. Jensen: Efficient Stochastic Routing in Path-Centric Uncertain Road Networks. Proc. VLDB Endow. 17(11): 2893-2905 (2024) CCF-A

  • Xinle Wu, Xingjian Wu, Bin Yang, Lekui Zhou, Chenjuan Guo, Xiangfei Qiu, Jilin Hu, Zhenli Sheng, Christian S. Jensen: AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting. VLDB J. 33(5): 1743-1770 (2024)  CCF-A

  • Hao Miao, Yan Zhao, Chenjuan Guo, Bin Yang, Kai Zheng, Feiteng Huang, Jiandong Xie, Christian S. Jensen: A Unified Replay-Based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data. ICDE (2024): 1050-1062  CCF-A

  • Christian S. Jensen, Bin Yang, Chenjuan Guo, Jilin Hu, Kristian Torp: Routing with Massive Trajectory Data. ICDE (2024): 5542-5547 CCF-A

  • Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo: Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting. ICLR (2024)

  • Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen: AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting. Proc. ACM Manag. Data 1(1): 97:1-97:26 (2023)   CCF-A

  • David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, Christian S. Jensen: LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation. Proc. ACM Manag. Data 1(2): 171:1-171:27 (2023)   CCF-A

  • Zhicheng Pan, Yihang Wang, Yingying Zhang, Sean Bin Yang, Yunyao Cheng, Peng Chen, Chenjuan Guo, Qingsong Wen, Xiduo Tian, Yunliang Dou, Zhiqiang Zhou, Chengcheng Yang, Aoying Zhou, Bin Yang: MagicScaler: Uncertainty-aware, Predictive Autoscaling. Proc. VLDB Endow. 16(12): 3808-3821 (2023)   CCF-A

  • Sean Bin Yang, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: LightPath: Lightweight and Scalable Path Representation Learning. KDD (2023): 2999-3010   CCF-A

  • Haomin Yu, Jilin Hu, Xinyuan Zhou, Chenjuan Guo, Bin Yang, Qingyong Li: CGF: A Category Guidance Based PM2.5 Sequence Forecasting Training Framework. IEEE Trans. Knowl. Data Eng. 35(10): 10125-10139 (2023)   CCF-A

  • Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin: RetroGraph: Retrosynthetic Planning with Graph Search. KDD (2022): 2120-2129   CCF-A

  • Sean Bin Yang, Chenjuan Guo, Bin Yang: Context-Aware Path Ranking in Road Networks. IEEE Trans. Knowl. Data Eng. 34(7): 3153-3168 (2022)   CCF-A

  • Tung Kieu, Bin Yang, Chenjuan Guo, Razvan-Gabriel Cirstea, Yan Zhao, Yale Song, Christian S. Jensen: Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders. ICDE (2022): 1342-1354   CCF-A

  • Sean Bin Yang, Chenjuan Guo, Jilin Hu, Bin Yang, Jian Tang, Christian S. Jensen: Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning. ICDE (2022): 2873-2885   CCF-A

  • Razvan-Gabriel Cirstea, Bin Yang, Chenjuan Guo, Tung Kieu, Shirui Pan: Towards Spatio- Temporal Aware Traffic Time Series Forecasting. ICDE (2022): 2900-2913   CCF-A

  • Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, Kai Zheng: Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection. ICDE (2022): 3038-3050   CCF-A

  • Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang, Tung Kieu, Xuanyi Dong, Shirui Pan: Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting. IJCAI (2022): 1994-2001   CCF-A

  • Yan Zhao, Xuanhao Chen, Liwei Deng, Tung Kieu, Chenjuan Guo, Bin Yang, Kai Zheng, Christian S. Jensen: Outlier Detection for Streaming Task Assignment in Crowdsourcing. WWW (2022): 1933-1943   CCF-A

  • David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, and Christian S. Jensen. Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles. Proc. VLDB Endow. 15(3): 611-623 (2021)   CCF-A

  • Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen: AutoCTS: Automated Correlated Time Series Forecasting. Proc. VLDB Endow. 15(4): 971-983 (2021)   CCF-A

  • Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Bin Yang, Sinno Jialin Pan: EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting. ICDE (2021): 1739-1750.   CCF-A

  • Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang: Unsupervised Path Representation Learning with Curriculum Negative Sampling. IJCAI (2021): 3286-3292.   CCF-A