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SIGMOD, VLDB,ICDE,IJCAI,KDD,WWW,ICLR,NeurIPS, VLDB Journal, TKDE等。并担任担任IEEE TKDE、IEEE TMC等多个顶级期刊的专家审稿人,以及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!


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

  • 自动机器学习(AutoML),模型可解释性(Interpretability),健壮性(Robustness),持续学习(Continual Learning),模型压缩(Model Compression),DB4ML


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


  • 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 PM$_{2.5}$ 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

  • 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

  • Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen, and Lu Chen: Context-Aware, Preference-Based Vehicle Routing. VLDB J. 29(5): 1149-1170 (2020).   CCF-A

  • Jilin Hu, Bin Yang, Chenjuan Guo, Christian S. Jensen, and Hui Xiong: Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks, ICDE 2020:1417-1428.   CCF-A

  • Lu Chen, Yunjun Gao, Ziquan Fang, Xiaoye Miao, Christian S. Jensen, Chenjuan Guo: Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories, PVLDB 12(10): 1208-1220 (2019).   CCF-A

  • Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Outlier Detection for Time Series with Recurrent Autoencoder Ensembles. IJCAI 2019: 2725-2732.   CCF-A

  • Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks. ICDE 2019: 1274-1285.   CCF-A

  • Jilin Hu, Bin Yang, Chenjuan Guo, and Christian S. Jensen. Risk-aware path selection with time-varying, uncertain travel costs—a time series approach. VLDB J. 27(2): 179-200 (2018).   CCF-A

  • Jian Dai, Bin Yang, Chenjuan Guo, Christian S. Jensen, and Jilin Hu. Pace: A path-centric paradigm for stochastic path finding. VLDB J. 27(2): 153-178 (2018).   CCF-A

  • Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen: Learning to Route with Sparse Trajectory Sets. ICDE 2018: 1073-1084.   CCF-A

  • Jian Dai, Bin Yang, Chenjuan Guo, Christian S. Jensen, and Jilin Hu. Path cost distribution estimation using trajectory data. PVLDB, 10(3):85–96, 2016.   CCF-A