Overview
Background
2016 - 2020, Ph.D., Data Science, University of Queensland (UQ), Supervised by Prof. Xiaofang Zhou and Prof. Sibo Wang
Availability
- Dr Dan He is:
- Available for supervision
Qualifications
- Bachelor, University of Science and Technology Beijing
- Masters (Coursework), Peking University
- Doctor of Philosophy, The University of Queensland
Research interests
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Spatial-temporal data management and data mining
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High-Performance query processing on spatial-temporal database management
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Intelligent transportation systems
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Traffic prediction with spatial-temporal data
Works
Search Professor Dan He’s works on UQ eSpace
2025
Journal Article
Efficient algorithms for approximate k-radius coverage query on large-scale road networks
Li, Xiaocui, He, Dan and Zhang, Xinyu (2025). Efficient algorithms for approximate k-radius coverage query on large-scale road networks. Ieee Transactions On Intelligent Transportation Systems, 26 (2), 1631-1644. doi: 10.1109/TITS.2024.3510532
2025
Journal Article
Dynamic Route Optimization With Multi-Category Constraints for POIs Visit
Li, Jiajia, Liu, Chunhui, He, Dan, Li, Lei, Zhou, Xiaofang and Zhu, Rui (2025). Dynamic Route Optimization With Multi-Category Constraints for POIs Visit. IEEE Transactions on Intelligent Transportation Systems, 26 (3), 1-14. doi: 10.1109/tits.2024.3520580
2024
Conference Publication
EGNN-AD: An effective graph neural network-based approach for anomaly detection on edge-attributed graphs
Wang, Hewen, Hooi, Bryan, He, Dan, Liu, Juncheng and Xiao, Xiaokui (2024). EGNN-AD: An effective graph neural network-based approach for anomaly detection on edge-attributed graphs. 29th International Conference, DASFAA 2024, Gifu, Japan, 2-5 July 2024. Heidelberg, Germany: Springer. doi: 10.1007/978-981-97-5572-1_21
2023
Journal Article
MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networks
Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2023). MSGNN: A Multi-structured Graph Neural Network model for real-time incident prediction in large traffic networks. Transportation Research Part C: Emerging Technologies, 156 104354. doi: 10.1016/j.trc.2023.104354
2023
Conference Publication
Map-matching on wireless traffic sensor data with a sequence-to-sequence model
Zhu, Zichun, He, Dan, Hua, Wen, Kim, Jiwon and Shi, Hua (2023). Map-matching on wireless traffic sensor data with a sequence-to-sequence model. 24th IEEE International Conference on Mobile Data Management (MDM), Singapore, Singapore, 3-6 July 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/mdm58254.2023.00048
2023
Conference Publication
Heterogeneous region embedding with prompt learning
Zhou, Silin, He, Dan, Chen, Lisi, Shang, Shuo and Han, Peng (2023). Heterogeneous region embedding with prompt learning. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23), Washington, DC, United States, 7–14 February 2023. Washington, DC, United States: AAAI Press. doi: 10.1609/aaai.v37i4.25625
2023
Journal Article
Autonomous anomaly detection on traffic flow time series with reinforcement learning
He, Dan, Kim, Jiwon, Shi, Hua and Ruan, Boyu (2023). Autonomous anomaly detection on traffic flow time series with reinforcement learning. Transportation Research Part C: Emerging Technologies, 150 104089, 1-21. doi: 10.1016/j.trc.2023.104089
2022
Journal Article
An efficient algorithm for maximum trajectory coverage query with approximation guarantee
He, Dan, Zhou, Thomas, Zhou, Xiaofang and Kim, Jiwon (2022). An efficient algorithm for maximum trajectory coverage query with approximation guarantee. IEEE Transactions on Intelligent Transportation Systems, PP (99), 1-13. doi: 10.1109/tits.2022.3207499
2022
Journal Article
Efficient kNN query for moving objects on time-dependent road networks
Li, Jiajia, Ni, Cancan, He, Dan, Li, Lei, Xia, Xiufeng and Zhou, Xiaofang (2022). Efficient kNN query for moving objects on time-dependent road networks. The VLDB Journal, 32 (3), 1-20. doi: 10.1007/s00778-022-00758-w
2021
Journal Article
GLAD: a grid and labeling framework with scheduling for conflict-aware kNN queries
He, Dan, Wang, Sibo, Zhou, Xiaofang and Cheng, Reynold (2021). GLAD: a grid and labeling framework with scheduling for conflict-aware kNN queries. IEEE Transactions on Knowledge and Data Engineering, 33 (4) 8845640, 1-1. doi: 10.1109/tkde.2019.2942585
2021
Conference Publication
Efficient Trajectory Contact Query Processing
Chao, Pingfu, He, Dan, Li, Lei, Zhang, Mengxuan and Zhou, Xiaofang (2021). Efficient Trajectory Contact Query Processing. 26th International Conference, DASFAA 2021, Taipei, Taiwan, 11–14 April 2021. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-73194-6_44
2020
Conference Publication
Route reconstruction using low-quality bluetooth readings
Xu, Yehong, He, Dan, Chao, Pingfu, Kim, Jiwon, Hua, Wen and Zhou, Xiaofang (2020). Route reconstruction using low-quality bluetooth readings. 28th International Conference on Advances in Geographic Information Systems, Online, 3 - 6 November 2020. New York NY, United States: Association for Computing Machinery. doi: 10.1145/3397536.3422224
2020
Other Outputs
Efficient quality-aware spatiotemporal data analytics
He, Dan (2020). Efficient quality-aware spatiotemporal data analytics. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/uql.2020.659
2020
Conference Publication
Efficient kNN Search with occupation in large-scale on-demand ride-hailing
Li, Mengqi, He, Dan and Zhou, Xiaofang (2020). Efficient kNN Search with occupation in large-scale on-demand ride-hailing. 31st Australasian Database Conference, ADC 2020, Melbourne, VIC, Australia, 3–7 February, 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-39469-1_3
2019
Journal Article
Efficient and robust data augmentation for trajectory analytics: a similarity-based approach
He, Dan, Wang, Sibo, Ruan, Boyu, Zheng, Bolong and Zhou, Xiaofang (2019). Efficient and robust data augmentation for trajectory analytics: a similarity-based approach. World Wide Web, 23 (1), 361-387. doi: 10.1007/s11280-019-00695-9
2019
Conference Publication
An efficient framework for correctness-aware kNN queries on road networks
He, Dan, Wang, Sibo, Zhou, Xiaofang and Cheng, Reynold (2019). An efficient framework for correctness-aware kNN queries on road networks. 35th International Conference on Data Engineering (ICDE 2019), Macao, Macao, 8-11 April 2019. New York, NY, United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00118
2018
Conference Publication
A system for spatial-temporal trajectory data integration and representation
Peixoto, Douglas Alves, Zhou, Xiaofang, Hung, Nguyen Quoc Viet, He, Dan and Stantic, Bela (2018). A system for spatial-temporal trajectory data integration and representation. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD, Australia, 21-24 May 2018. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-91458-9_53
2018
Conference Publication
Trajectory set similarity measure: An EMD-based approach
He, Dan, Ruan, Boyu, Zheng, Bolong and Zhou, Xiaofang (2018). Trajectory set similarity measure: An EMD-based approach. 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, 24-27 May 2018. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-92013-9_3
2018
Conference Publication
Origin-destination trajectory diversity analysis: efficient top-k diversified search
He, Dan, Ruan, Boyu, Zheng, Bolong and Zhou, Xiaofang (2018). Origin-destination trajectory diversity analysis: efficient top-k diversified search. 19th IEEE International Conference on Mobile Data Management, MDM 2018, Aalborg University, Aalborg, Denmark, 26-28 June 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/MDM.2018.00030
2017
Conference Publication
A performance study on large-scale data analytics using disk-based and in-memory database systems
Chao, Pingfu, He, Dan, Sadiq, Shazia, Zheng, Kai and Zhou, Xiaofang (2017). A performance study on large-scale data analytics using disk-based and in-memory database systems. 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017, Jeju, South Korea, 13 - 16 February 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/BIGCOMP.2017.7881706
Supervision
Availability
- Dr Dan He is:
- Available for supervision
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Media
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