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Dr Tongxin Chen

Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • Data Science AI and Modelling Centre (DAIM)

Qualifications

  • PhD / DPhil (University College London)

Summary

Dr Tongxin Chen is a lecturer at the Centre of Excellence for Data Science, Artificial Intelligence and Modelling (DAIM), Faculty of Science and Engineering, University of Hull.

Big Data and Data Mining in MSc AI and Data science

Recent outputs

View more outputs

Book Chapter

Urban Crime and Security

Cheng, T., & Chen, T. (2021). Urban Crime and Security. In W. Shi, M. F. Goodchild, M. Batty, M.-P. Kwan, & A. Zhang (Eds.), Urban Informatics (213-228). Springer. https://doi.org/10.1007/978-981-15-8983-6_14

Journal Article

Applying Dynamic Human Activity to Disentangle Property Crime Patterns in London during the Pandemic: An Empirical Analysis Using Geo-Tagged Big Data

Chen, T., Bowers, K., & Cheng, T. (2023). Applying Dynamic Human Activity to Disentangle Property Crime Patterns in London during the Pandemic: An Empirical Analysis Using Geo-Tagged Big Data. ISPRS International Journal of Geo-Information, 12(12), Article 488. https://doi.org/10.3390/ijgi12120488

Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic

Chen, T., Zhu, D., Cheng, T., Gao, X., & Chen, H. (2023). Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic. PLoS ONE, 18(1 January), Article e0277913. https://doi.org/10.1371/journal.pone.0277913

Human mobility variations in response to restriction policies during the COVID-19 pandemic: An analysis from the Virus Watch community cohort in England, UK

Cheng, T., Chen, T., Liu, Y., Aldridge, R. W., Nguyen, V., Hayward, A. C., & Michie, S. (2022). Human mobility variations in response to restriction policies during the COVID-19 pandemic: An analysis from the Virus Watch community cohort in England, UK. Frontiers in public health, 10, Article 999521. https://doi.org/10.3389/fpubh.2022.999521

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

Chen, T., Bowers, K., Zhu, D., Gao, X., & Cheng, T. (2022). 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. Computational Urban Science, 2(1), Article 13. https://doi.org/10.1007/s43762-022-00041-2

Research interests

Spatial temporal big data analytics, urban mobility, crime science, and applied machine learning.

Co-investigator

Project

Funder

Grant

Started

Status

Project

Understanding Community Insights into the Impact of GRIP hotspot policing

Funder

Home Office

Grant

£299,585.00

Started

1 January 2024

Status

Ongoing

Postgraduate supervision

I am accepting research students for both MSc and PhD in urban big data analytics and spatio-temporal crime analysis.

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