Oshan. T,, Irekponor, V.E, (2025).An Interpretable Machine Learning Approach to Modeling Metrorail Ridership: A case study of Washington, DC. Case Studies on Transport Policy (in prep,) 2025
Irekponor, V.E,, Oshan. T, (2025).Reproducible Visualization Strategies for Spatially Varying Coefficient (SVC) models: Incorporating Uncertainty and Assessing Replicability. Journal of Catography and Geographic Information Science (CaGIS) (in prep,) 2025
Oshan. T, Irekponor, V.E, (2024).Conducting local comparisons using Adjusted Geographically Weighted Correlation Coefficients. (in prep,) 2025
J Chapman, H Iseki, Irekponor, V.E, S Alam, C Harvey, M Liao, Z Liu (2023).Changes in the Determinant of Travel Demand for the Washington DC Metrorail System after COVID-19: Evidence from a Replication Study. Case Studies on Transport Policy, https://doi.org/10.1016/j.cstp.2025.101394
Abdul-Rahman, M., Chan, E. H., Wong, M. S., Irekponor, V. E., & Abdul-Rahman, M. O. (2021).A framework to simplify pre-processing location-based social media big data for sustainable urban planning and management. Cities, 109. https://doi.org/10.1016/j.cities.2020.102986
Irekponor, V.E, Oshan. T, (2025).Generalized Local Additive Spatial Smoothing (GLASS): A New Approach to Mitigating the Modifiable Areal Unit Problem. 33rd Annual Geographical Information Science Research UK (GISRUK) Conference, Bristol, United Kingdom
Irekponor, V.E, Oshan. T, (2025).Generalized Local Additive Spatial Smoothing (GLASS): A New Approach to Mitigating the Modifiable Areal Unit Problem. 2025 American Association of Geographers (AAG) Annual Meeting, Detroit, Michigan
Irekponor, V.E, Oshan. T, (2024).Visualization Strategies for Big Models. Cartography and Geographic Information Science (CaGIS) and the University Consortium for Geographic Information Science (UCGIS) Symposium, Columbus, Ohio.