郭晨娟

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，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。

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）

自动机器学习（AutoML），模型压缩（Model Compression），AI4DB

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！

- 计算机科学拔尖班数据结构：2023、2024年春季学期

• - 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，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, funded by Villum Fonden, 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.

Full list: DBLP, Google Scholar.

Selected Papers:

• - 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

• - 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

• - 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

• - 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

• - Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories. CIKM 2018: 863-872. CCF-A

• - Razvan-Gabriel Cirstea, Darius-Valer Micu, Gabriel-Marcel Muresan, Chenjuan Guo, Bin Yang: Correlated Time Series Forecasting using Multi-Task Deep Neural Networks. CIKM 2018: 1527-1530. 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

国家级青年人才计划