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Xiaowei GAO
Xiaowei GAO
PhD in Spacetime Lab, UCL
Verified email at ucl.ac.uk
Title
Cited by
Cited by
Year
Experimental study on individual walking speed during emergency evacuation with the influence of ship motion
X Wang, Z Liu, J Wang, S Loughney, Z Yang, X Gao
Physica A: Statistical Mechanics and its Applications 562, 125369, 2021
302021
Multi-scale object detection model for autonomous ship navigation in maritime environment
Z Shao, H Lyu, Y Yin, T Cheng, X Gao, W Zhang, Q Jing, Y Zhao, L Zhang
Journal of Marine Science and Engineering 10 (11), 1783, 2022
112022
Sea-surface object detection based on electro-optical sensors: A review
H Lyu, Z Shao, T Cheng, Y Yin, X Gao
IEEE Intelligent Transportation Systems Magazine 15 (2), 190-216, 2022
112022
Spatio-temporal stratified associations between urban human activities and crime patterns: a case study in San Francisco around the COVID-19 stay-at-home mandate
T Chen, K Bowers, D Zhu, X Gao, T Cheng
Computational urban science 2 (1), 13, 2022
112022
Revealing spatiotemporal transmission patterns and stages of COVID-19 in China using individual patients’ trajectory data
T Cheng, T Lu, Y Liu, X Gao, X Zhang
Computational urban science 1 (1), 9, 2021
92021
Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction
X Jiang, D Zhuang, X Zhang, H Chen, J Luo, X Gao
Proceedings of the 32nd ACM International Conference on Information and …, 2023
62023
A spatiotemporal analysis of the impact of lockdown and coronavirus on London’s bicycle hire scheme: from response to recovery to a new normal
X Gao, H Chen, J Haworth
Geo-spatial Information Science 26 (4), 664-684, 2023
52023
Spatiotemporal graph neural networks with uncertainty quantification for traffic incident risk prediction
X Gao, X Jiang, D Zhuang, H Chen, S Wang, J Haworth
arXiv preprint arXiv:2309.05072, 2023
52023
Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic
T Chen, D Zhu, T Cheng, X Gao, H Chen
PloS one 18 (1), e0277913, 2023
42023
Measures to prevent nosocomial transmissions of COVID-19 based on interpersonal contact data
T Cheng, J Liu, Y Liu, X Zhang, X Gao
Primary Health Care Research & Development 23, e4, 2022
32022
A framework for the optimal deployment of police drones based on street-level crime risk
H Chen, X Gao, H Li, Z Yang
Applied Geography 162, 103178, 2024
22024
Fatigue Detection for Ship OOWs Based on Input Data Features, From the Perspective of Comparison With Vehicle Drivers: A Review
H Lyu, J Yue, W Zhang, T Cheng, Y Yin, X Yang, X Gao, Z Hao, J Li
IEEE Sensors Journal, 2023
22023
Nonlinear control of decarbonization path following underactuated ships
H Zhao, X Gao, Y Zhang, X Zhang
Ocean Engineering 272, 113784, 2023
22023
Timeseries Suppliers Allocation Risk Optimization via Deep Black Litterman Model
J Luo, W Zhang, Y Fang, X Gao, D Zhuang, H Chen, X Jiang
arXiv preprint arXiv:2401.17350, 2024
12024
Uncertainty Quantification in the Road-level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network (STZINB-GNN)
X Gao, J Haworth, D Zhuang, H Chen, X Jiang
12th International Conference on Geographic Information Science (GIScience …, 2023
12023
Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?
I Ilyankou, A Lipani, S Cavazzi, X Gao, J Haworth
arXiv preprint arXiv:2404.04169, 2024
2024
Joint prediction of travel mode choice and purpose from travel surveys: A multitask deep learning approach
H Bei, H Chen, L Li, X Gao, Y Xia, Y Sun
Travel Behaviour and Society 33, 100625, 2023
2023
Revealing the relationship between human mobility and urban deprivation using geo-big data: a case study from London in the post-pandemic era
T Chen, X Gao, T Cheng
Geographical Information Science Research UK (GISRUK), 2023
2023
Fatigue Detection for Ship OOWs Based on Input Data Features, from The Perspective of Comparison with Vehicle Drivers: A
H Lyu, J Yue, W Zhang, T Cheng, Y Yin, X Yang, X Gao, Z Hao, J Li
2023
Spatiotemporal analysis of human cycling patterns' changes during weekdays under the COVID-19 lockdown: A case study of London docked shared bicycles
X GAO, J Haworth, H CHEN, P Fernandes
2021
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