Mr Hyesop Shin

  • Research Associate (MRC/CSO Social & Public Health Sciences Unit)

email: Hyesop.Shin@glasgow.ac.uk

99 Berkeley Street, Glasgow, Glasgow City, Scotland, 영국, G3 7HR

ORCID iDhttps://orcid.org/0000-0003-2637-7933

Biography

Hyesop is a quantitative geographer interested in themes including environmental hazards, urban air quality, individual mobility patterns, which are likely to be real-world problems. To tackle these issues, Hyesop applies methods including GIScience and agent-based modelling (ABM). Prior to joining Glasgow, Hyesop completed his PhD at the University of Cambridge where he looked at how individuals exposure to air pollution can differ by commuting routes and socioeconomic backgrounds using an agent-based simulation. At Glasgow, Hyesop’s current project unravels the benefits of using crowdsourcing to help improve our understanding of locational services for the under-represented groups.

Research interests

My research mainly stands on the quantitative side of geography. This includes miscellaneous GIS approaches, geo-statistics (i.e. clustering, spatial autocorrelation), and agent-based modelling. The topics I worked on through my academic path varied from the aquatic ecosystem, disease to urban transport.

Publications

List by: Type | Date

Jump to: 2022 | 2021 | 2019
Number of items: 6.

2022

Shin, H. and Bithell, M. (2022) Exposure to non-exhaust emission in Central Seoul using an agent-based framework. In: Czupryna, M. and Kamiński, B. (eds.) Advances in Social Simulation: Proceedings of the 16th Social Simulation Conference, 20–24 September 2021. Series: Springer Proceedings in Complexity. Springer International Publishing: Cham, pp. 343-354. ISBN 9783030928421 (doi: 10.1007/978-3-030-92843-8_26)

Shin, H. and Basiri, A. (2022) Geographic Biases in OSM Contributions: How do the Geographic Extent of Contributions Differ Among Demographic Groups? In: GISRUK 2022, Liverpool, UK, 05-08 Apr 2022, (doi: 10.5281/zenodo.6411601)

Shin, H. (2022) Quantifying the health effects of exposure to non-exhaust road emissions using agent-based modelling (ABM). MethodsX, 9, 101673. (doi: 10.1016/j.mex.2022.101673)

Shin, H. , Cagnina, C. and Basiri, A. (2022) The Impact of Built Environment on Bike Commuting: Utilising Strava Bike Data and Geographically Weighted Models. In: 25th AGILE Conference on Geographic Information Science “Artificial Intelligence in the service of Geospatial Technologies”, Vilnius, Lithuania, 14-17 June 2022, p. 15. (doi: 10.5194/agile-giss-3-15-2022)

2021

Shin, H. (2021) Benefits of open research in social simulation: an early-career researcher's perspective. Review of Artificial Societies and Social Simulation, 23 Nov.

2019

Shin, H. and Bithell, M. (2019) An agent-based assessment of health vulnerability to long-term particulate exposure in Seoul districts. Journal of Artificial Societies and Social Simulation, 22(1), 12. (doi: 10.18564/jasss.3940)

This list was generated on Sun Sep 25 07:42:51 2022 BST.
Number of items: 6.

Articles

Shin, H. (2022) Quantifying the health effects of exposure to non-exhaust road emissions using agent-based modelling (ABM). MethodsX, 9, 101673. (doi: 10.1016/j.mex.2022.101673)

Shin, H. (2021) Benefits of open research in social simulation: an early-career researcher's perspective. Review of Artificial Societies and Social Simulation, 23 Nov.

Shin, H. and Bithell, M. (2019) An agent-based assessment of health vulnerability to long-term particulate exposure in Seoul districts. Journal of Artificial Societies and Social Simulation, 22(1), 12. (doi: 10.18564/jasss.3940)

Book Sections

Shin, H. and Bithell, M. (2022) Exposure to non-exhaust emission in Central Seoul using an agent-based framework. In: Czupryna, M. and Kamiński, B. (eds.) Advances in Social Simulation: Proceedings of the 16th Social Simulation Conference, 20–24 September 2021. Series: Springer Proceedings in Complexity. Springer International Publishing: Cham, pp. 343-354. ISBN 9783030928421 (doi: 10.1007/978-3-030-92843-8_26)

Conference Proceedings

Shin, H. and Basiri, A. (2022) Geographic Biases in OSM Contributions: How do the Geographic Extent of Contributions Differ Among Demographic Groups? In: GISRUK 2022, Liverpool, UK, 05-08 Apr 2022, (doi: 10.5281/zenodo.6411601)

Shin, H. , Cagnina, C. and Basiri, A. (2022) The Impact of Built Environment on Bike Commuting: Utilising Strava Bike Data and Geographically Weighted Models. In: 25th AGILE Conference on Geographic Information Science “Artificial Intelligence in the service of Geospatial Technologies”, Vilnius, Lithuania, 14-17 June 2022, p. 15. (doi: 10.5194/agile-giss-3-15-2022)

This list was generated on Sun Sep 25 07:42:51 2022 BST.

Supervision

EcoSim: An Open Gamified Traffic Simulation Tool to Quantify the Impact of Air Pollution

This project aims to train and enable student(s) to explore and simulate the dynamics of TRAP and the consequent health effects using EcoSIM, namely a gamified simulation tool.

Urban Analytical Approaches to Combating Covid-19