About Me
My name is Natchapon Jongwiriyanurak (pronounced Nat-cha-pon Jong-wi-ri-ya-nu-rak), though I also go by “Pong”. I am a PhD Candidate at SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, UCL, supervised by Dr James Haworth and Dr Nicola Christie. My research explores how advanced methods can be applied to real-world challenges in the built environment, with a particular focus on GeoAI, computer vision, and multimodal data for applications in transportation and smart cities. I am currently completing my PhD and am a visiting PhD student at the Applied Geotechnologies Research Group Research, CINTECX, UVigo.
I am particularly interested in applying and adapting methods across domains, and in developing scalable solutions for data-scarce and rapidly evolving urban contexts, especially in the Global South. If you’re working on something similar or have ideas to explore, feel free to reach out.
News
- [Mar. 2026] Our paper accepted in Infrastructure
- [Jan. 2026] I am a visiting PhD student at Applied Geotechnologies Research Group Research, CINTECX, UVigo
- [Dec. 2025] CLIP the landscape is accpeted in Remote Sensing Applications: Society and Environment
- [Sept. 2025] A paper is accpeted in Accident Analysis and Prevention
- [Aug. 2025] Into the Unknow is accpeted at SigSpatial
Recent Publications
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RSASE
Remote Sensing Applications: Society and Environment -
SIGSPATIAL
33rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2025) -
AAAP
Accident Analysis & Prevention -
ICCVW
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops
Teaching Experience
I have contributed to teaching at UCL across several undergraduate and postgraduate modules as a Postgraduate Teaching Assistant (PGTA) and Guest Lecturer:
- CEGE0012: Scenarios in Civil Engineering
- CEGE0014: Surveying and Field Studies
- BENV0093: Spatial Analysis of Energy Data
- BENV0145: Data Analytics in the Smart Built Environment
- BENV0159: Machine Learning and Predictive Data Analytics
- CEGE0097: Spatial Analysis and Geocomputation
- CEGE0042: Spatial-Temporal Data Analysis and Data Mining (STDM)
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