Machine Learning

(2025) GeoAggregator: An Efficient Transformer Model for Geo-Spatial Tabular Data. In: 39th Annual AAAI Conference on Artificial Intelligence (AAAI'25), Philadelphia, Pennsylvania, USA, 25 February – 4 March 2025, pp. 11572-11580. ISBN 9781577358978
Rui Deng, Ziqi Li, Dr. Mingshu Wang
DOI
New Paper Published: GeoAggregator - An Efficient Transformer Model for Geo-Spatial Tabular Data
Our latest research on transformer models for geospatial data has been published, introducing GeoAggregator - a novel approach for handling geo-spatial tabular data.
Dr. Mingshu Wang
Last updated on Jun 21, 2025 1 min read
(2024) Occupation prediction with multimodal learning from Tweet messages and Google Street View images. AGILE: GIScience Series, 5, 36
Xinyi Liu, Bo Peng, Meiliu Wu, Dr. Mingshu Wang, Heng Cai, Qunying Huang
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(2024) A Transformer-Based Model for Effective Representation of Geospatial Data and Context. EGU General Assembly 2024, Vienna, Austria, 14-19 April 2024
Rui Deng, Ziqi Li, Dr. Mingshu Wang
DOI
(2024) Machine learning-based characterisation of urban morphology with the street pattern. Computers, Environment and Urban Systems, 109, 102078
Cai Wu, Jiong Wang, Dr. Mingshu Wang, Menno-Jan Kraak
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(2024) Mapping street patterns with network science and supervised machine learning. ISPRS International Journal of Geo-Information, 13(4), 114
Cai Wu, Yanwen Wang, Jiong Wang, Menno-Jan Kraak, Dr. Mingshu Wang
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(2022) Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning. Computers, Environment and Urban Systems, 91, 101716
Jiayu Wu, Yutian Lu, Hei Gao, Dr. Mingshu Wang
DOI
(2019) Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning. Journal of Transport Geography, 79, 102479
Xiaolu Zhou, Dr. Mingshu Wang, Dongying Li
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