Journal papers, conference orals, and work in press. Talks and PDFs also live on the research one-pager.
Journal articles, conference papers (including orals at ICCBEI 2023 and ICRT 2024), and work in press or under review. Talks, slides, and awards are on the research one-pager.
Geographically weighted regression linking land use and MRT Blue Line ridership across space and time. Presented at CASPT 2025; this version is the Public Transport special issue.
This study investigates how digital infrastructure contributes to smart city performance in emerging economic contexts and whether its impact is shaped by governance models. We estimate the effect of a Digital Technology Index on a composite Smart City Index, employing a generalized least squares (GLS) random-effects model to address heteroskedasticity and serial correlation.
This study explores the development and application of a machine learning (ML) approach to predict buckling failure modes in ballasted railway tracks. With the growing demand for safer and more reliable railway systems, the ability to foresee and mitigate track failures is of paramount importance.
IWGMS
Spatiotemporal Dynamics of Land Use and Ridership: A Geographically Weighted Regression Analysis of Bangkok’s MRT Blue Line
Watcharapong Wongkaew, Kongtup Wanichjaroenporn, and Pongsun Bunditsakulchai
In 3rd International Workshop on Geographic Modelling and Simulation, Apr 2024
Workshop abstract on geographically weighted regression of land use and ridership for Bangkok’s MRT Blue Line. Later developed as the 2026 Public Transport paper.
Uses digital surface models, historical climate data, and machine learning to assess flood risk on Thailand’s railway networks and translate predictions into an operation-based Flood Risk Index.
