Chenjuan Guo

I am an Associate Professor in Department of Computer Science at Aalborg University. I am also a faculty member in Center for Data-Intensive Systems.

I obtained my Ph.D. degree from the University of Manchester in 2011. From 2012 to 2014, I worked at Aarhus University, in Data-Intensive Systems group. I joined Aalborg University in August 2014.

Research Interests

Data management and data analytics, in particular on spatio-temporal data and time series data;
Explainable machine learning; Automated machine learning (AutoML); Learning with small data.

Publications

Full list: DBLP, Google Scholar.

Recent Publications:

  • Yan Zhao, Xuanhao Chen, Liwei Deng, Tung Kieu, Chenjuan Guo, Bin Yang, Kai Zheng and Christian S. Jensen. Outlier Detection for Streaming Task Assignment in Crowdsourcing. WWW 2022, To appear.
  • Tung Kieu, Bin Yang, Chenjuan Guo, Razvan-Gabriel Cirstea, Yan Zhao, Yale Song, and Christian S. Jensen. Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders. ICDE 2022, To appear.
  • Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, and Christian S. Jensen. AutoCTS: Automated Correlated Time Series Forecasting. PVLDB 2022, To appear.
  • 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).
  • 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.
  • Sean Bin Yang, Chenjuan Guo, Jilin Hu, Jian Tang, Bin Yang: Unsupervised Path Representation Learning with Curriculum Negative Sampling. IJCAI 2021: 3286-3292.
  • Sean Bin Yang, Chenjuan Guo, Bin Yang: Context-Aware Path Ranking in Road Networks. TKDE 2021.
  • 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).
  • 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.
  • 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).
  • Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen: Outlier Detection for Time Series with Recurrent Autoencoder Ensembles. IJCAI 2019: 2725-2732.
  • Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen: Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks. ICDE 2019: 1274-1285.
  • 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).
  • 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).
  • Chenjuan Guo, Bin Yang, Jilin Hu, Christian S. Jensen: Learning to Route with Sparse Trajectory Sets. ICDE 2018: 1073-1084.
  • 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.

Projects

  • Explainable AI for Complex Microbial Community Interactions and Predictions, funded by Villum Fonden, PI, in collaboration with Prof. Per Halkjær Nielsen, 2021 - 2024. News!
  • Time Series Analytics and Spatio-temporal Data Management, funded by Huawei, Co-PI, 2020 - 2022.
  • Advance: A Data-Intensive Paradigm for Dynamic, Uncertain Networks, funded by Independent Research Fund Denmark, Co-PI, 2019 - 2023.
  • Astra: AnalyticS of Time seRies in spAtial networks, funded by Independent Research Fund Denmark, Co-PI, 2018 - 2021.
  • Collaboration with BlipTrack, funded by Forskerpuljen, PI, 2018.

Conference Organizer

  • Proceedings Co-Chair, IEEE International Conference on Mobile Data Management

Program Committee Members

  • ACM SIGKDD (KDD)
  • International Joint Conference on Artificial Intelligence (IJCAI-ECAI)
  • IEEE International Conference on Data Engineering (ICDE)
  • AAAI Conference on Artificial Intelligence (AAAI)
  • International Conference on Information and Knowledge Management (CIKM)
  • International Symposium on Spatial and Temporal Databases (SSTD)
  • IEEE International Conference on Mobile Data Management (MDM)
  • International Conference on Database Systems for Advanced Applications (Dasfaa)
  • The Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data

Reviewers for Journals

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Transactions on Mobile Computing (TMC)
  • ACM Transactions on Spatial Algorithms and Systems
  • GeoInformatica
  • International Journal of Geographical Information Science (IJGIS)
  • IEEE Transactions on Intelligent Transportation Systems (T-ITS)
  • Transportation Research Part C: Emerging Technologies

PhD Students

  • Razvan-Gabriel Cirstea, 2018.10-, Topic: time series analytics, Co-supervise with Bin Yang
  • Yunyao Cheng, 2021.7-, Topic: explainable machine learning, Co-supervise with Christitan S. Jensen and Kaixuan Chen
  • Kai Zhao, 2021.12-, Topic: learning with small data, Co-supervise with Miao Zhang
  • Hao Miao, 2021.12-, Topic: spatio-temporal data analytics, Co-supervise with Christitan S. Jensen and Yan Zhao

Teaching

  • Algorithms and Data Structures (AD2), BAIT5, Lecturers, 2020, 2021.
  • Algorithms and Data Structures (AD1), DAT3/SW3, Lecturers, 2018, 2019.
  • Specialization Course in Database Technology (spDT), Lecturers, DAT9/SW9, 2019.
  • Specialization Course in Machine Intelligence (spMI), Lecturers, DAT9/SW9, 2020, 2021.
  • Master Thesis Projects, Supervisors, DAT9/SW9, DAT10/SW10, 2019, 2020, 2021.
  • Project Supervision, Supervisors, SW6/DAT7/CS-IT7, 2018, 2019, 2020.
  • Specialization Course in Database Technology (spDT), Coordinators, 2020, 2021.
  • PhD courses for Machine Learning, Organizers, 2021, 2022.

Contact

Address: Office 3.2.34, Selma Lagerlöfs Vej 300, DK-9220, Aalborg Øst, Denmark
Email: cguo [at] cs {dot} aau (dot) dk
Phone: +45 9940 3575