Song WU (吴松)
Song WU is currently a PhD student in Université libre de Bruxelles, Belgium and Aalborg University, Denmark, under the supervision of Prof. Esteban Zimányi, Prof. Mahmoud Sakr, and Prof. Kristian Torp. His PhD research is funded by the European Union's Horizon 2020 research and innovation programme Data Engineering for Data Science. Song WU received his Bachelor degree in Software Engineering from Tianjin University (one 985-project University), China in 2018 and his Master degree in Computer Science from Shenzhen University, China in 2021. During his Master studies, Song WU also did a one-year visit to Kazan Federal University, Russia from Oct 2018 to June 2019.
Song WU's research interests are various tasks on large-scale ship trajectory data (e.g. Danish AIS Data), such as trajectory segmentation, sensor fusion, CO2 emissions analysis, and trajectory similarity measures.
Song WU's hobbies are travelling, badminton, hiking, and photography
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Selected Publications
[MDM'2025] Song Wu, Kristian Torp, Alexandros Troupiotis-Kapeliaris, Dimitris Zissis, Esteban Zimányi, Mahmoud Sakr: Effective Ship Trajectory Imputation with Multiple Coastal Cameras. (Best paper candidate) 26th IEEE International Conference on Mobile Data Management, 2025. [pdf] [code]
[MDM'2024] Song Wu, Alexandros Troupiotis-Kapeliaris, Dimitris Zissis, Kristian Torp, Esteban Zimányi, Mahmoud Sakr: Uncertainty-Aware Ship Location Estimation using Multiple Cameras in Coastal Areas. 25th IEEE International Conference on Mobile Data Management, 2024. [pdf] [code]
[SSTD'2023] Song Wu, Kristian Torp, Mahmoud Sakr, Esteban Zimányi: Evaluation of Vessel CO2 Emissions Methods using AIS Trajectories. 18th International Symposium on Spatial and Temporal Data, 2023. [pdf] [video]
[MDM'2022] Song Wu, Esteban Zimányi, Mahmoud Sakr, Kristian Torp: Semantic segmentation of AIS trajectories for detecting complete fishing activities. 23rd IEEE International Conference on Mobile Data Management, 2022. [pdf] [dataset] [experimental results] [video]
[Dagstuhl reports'2022] Mohamed Mokbel, Mahmoud Sakr, Li Xiong, Andreas Züfle, Jussara Almeida, Taylor Anderson, Walid Aref, Gennady Andrienko, Natalia Andrienko, Yang Cao, Sanjay Chawla, Reynold Cheng, Panos Chrysanthis, Xiqi Fei, Gabriel Ghinita, Anita Graser, Dimitrios Gunopulos, Christian Jensen, Joon-Sook Kim, Kyoung-Sook Kim, Peer Kröger, John Krumm, Johannes Lauer, Amr Magdy, Mario Nascimento, Siva Ravada, Matthias Renz, Dimitris Sacharidis, Cyrus Shahabi, Flora Salim, Mohamed Sarwat, Maxime Schoemans, Bettina Speckmann, Egemen Tanin, Yannis Theodoridis, Kristian Torp, Goce Trajcevski, Marc van Kreveld, Carola Wenk, Martin Werner, Raymond Wong, Song Wu, Jianqiu Xu, Moustafa Youssef, Demetris Zeinalipour, Mengxuan Zhang, Esteban Zimányi: Mobility data science (dagstuhl seminar 22021). Dagstuhl reports, 2022. [pdf]
[TKDE'2021] Dingming Wu, Ilkcan Keles, Song Wu, Hao Zhou, Simonas Šaltenis, Christian S. Jensen, Kezhong Lu: Density-Based Top-K Spatial Textual Clusters Retrieval. IEEE Transactions on Knowledge and Data Engineering, 2021. [paper]
Services
External Reviewer: VLDB'2023, SigSpatial'2025, DAWAK'2023
Student Volunteer: Dagstuhl Seminar 22021 - Mobility Data Science
Expertise
Tableau-based trajectory data visualization, exploration, and dashboard design
Resources
Fishing trajectory dataset: this dataset contains 128 fishing trajectories, and each trajectory point has a label of fishing or not-fishing. This dataset can be used for the task of trajectory segmentation to understand fishing activities.