An asterisk (*) denotes the corresponding author. Underlined names indicate student (mentee) authors.

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50. Sharma Dulal, S.#, Jain, D.#, Sherman, Z., Zhang, M., Kim, R., Subramanian, S. V.*, Kim, J.* Expanding Public Access to Understanding Data: A Case Study of Leveraging Generative AI for India Policy Insights Dashboard. The Professional Geographer. Accepted. (# Equal contribution to the paper. * Co-corresponding authors.)

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49. Howell, B. A., Kim, J., Thornhill, T. A., Lee, J., Biegacki, E. T., Grau, L. E., ... & Gonsalves, G. S. (2026). Travel time to methadone treatment via personal vehicle vs public transit. JAMA Network Open, 9(2), e2557361. https://doi.org/10.1001/jamanetworkopen.2025.57361

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48. Kim, J.*, Klopfer, M., Grohs, J., Eldardiry, H., Weichert, J., Cox II, L., & Pike, D. (2025). Examining Faculty and Student Perceptions of Generative AI in University Courses. Innovative Higher Education. https://doi.org/10.1007/s10755-024-09774-w

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47. Renshaw, A. Ismini, L., Lee, J., Crawford, T., & Kim, J.* (2025). Comparing the Spatial Querying Capacity of Large Language Models: OpenAI’s ChatGPT and Google’s Gemini Pro. The Professional Geographer, 1-13. https://doi.org/10.1080/00330124.2024.2434455

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46. Jang, K., & Kim, J.* (2025). Social inequalities in green exposure in small-and medium-sized US cities: A mobility-based approach. Social Science Research. https://doi.org/10.1016/j.ssresearch.2025.103142

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45. Rahman, F., Oliver, R., Buehler, R., Lee, J., Crawford, T., & Kim, J.* (2025). Impacts of point of interest (POI) data selection on 15-Minute City (15-MC) accessibility scores and inequality assessments. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2025.104429

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44. Sherman, Z., Sharma, Dulal, Cho, J., Zhang, M., & Kim, J.* (2025). Generative AI for Geospatial Analysis: Fine-Tuning ChatGPT to Convert Natural Language into Python-Based Geospatial Computations. ISPRS International Journal of Geo-Information, 14(8), 314. https://doi.org/10.3390/ijgi14080314

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43. Sherman, Z., Karki, S., Brickhouse, T., Vujicic, M., Nasseh, K., Wang, C., ... Kim, J. & Zhang, M. (2025). Geospatial access to oral health care in Virginia: Insights from driving and public transit analysis. The Journal of the American Dental Association. https://doi.org/10.1016/j.adaj.2025.09.003

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42. Shaver, H., Kim, J., Diab, E., & Lee, J. (2025). Bridging the gap: A social equity analysis of intra-city transit access to inter-city rail in Canada. Cities. 163. https://doi.org/10.1016/j.cities.2025.106041

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41. Day, T., Gonzalez, M., Kim, J., McDaniel, P., Redican, K., & Zhu, T. (2025). Generative AI in Undergraduate Education: An Early View of Developments, Prospects, and Challenges of the AI Revolution. The Professional Geographer, 1-18. https://doi.org/10.1080/00330124.2025.2478075

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40. Ahmed, N., Jui, J., Liu, D., Kim, K., Kim, J., & Lee, J. (2025). Understanding inequalities in geographic accessibility to emergency cyclone shelters in Bangladesh under climate change. Journal of Transport Geography. https://doi.org/10.1016/j.jtrangeo.2025.104134

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39. Weichert, J., Kim, D., Zhu, Q., Kim, J., & Eldardiry, H. (2025). Assessing computer science student attitudes towards AI ethics and policy. AI & Ethics, https://doi.org/10.1007/s43681-025-00817-2

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38. Huang, T., Ye, X., Yigitcanlar, T., Xu, B., Newman, G., Zhao, B., ... Kim, J., & Wang, D. (2026). Artificial Intelligence in urban design: A systematic review. Cities, 169, 106527. https://doi.org/10.1016/j.cities.2025.106527

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37. Kim, J.*, Lee, J., Jang, K. M., & Lourentzou, I. (2024). Exploring the limitations in how ChatGPT introduces environmental justice issues in the United States: A case study of 3,108 counties. Telematics and Informatics, 86, 102085. https://doi.org/10.1016/j.tele.2023.102085

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36. Kim, J.*, Kim, D., & David-John, B. (2024). The role of privacy concerns, perceived benefits, and trust in citizens' acceptance of street-view image collection by local planning agencies. Cities, 154, 105339.  https://doi.org/10.1016/j.cities.2024.105339

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35. Kim, J.*, Park, J., Lee, J., & Jang, K. M. (2024). Examining the socio-spatial patterns of bus shelters with deep learning analysis of street-view images: A case study of 20 cities in the US. Cities, 148, 104852. https://doi.org/10.1016/j.cities.2024.104852

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34. Kim, J.*, Rapuri, S., Wang, K., Wendy Guan, W., & Laituri, M. (2024). A scoping review of COVID-19 research adopting quantitative geographical methods in geography, urban studies, and planning: a text mining approach. Annals of GIS, 30(1), 67-80. https://doi.org/10.1080/19475683.2024.2304205

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33. Kim, J., Lee, J., Thornhill, T. A., Dennett, J., Lu, H., Howell, B., ... & Gonsalves, G. (2024). Accessibility of opioid treatment programs based on conventional vs perceived travel time measures. JAMA Network Open, 7(2), e240209-e240209. https://doi.org/10.1001/jamanetworkopen.2024.0209

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32. Kim, J., Karki, S., Brickhouse, T., Vujicic, M., Nasseh, K., Wang, C., & Zhang, M. (2024). Navigating Disparities in Dental Health—A Transit‐Based Investigation of Access to Dental Care in Virginia. Community Dentistry and Oral Epidemiology. https://doi.org/10.1111/cdoe.13015

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31. Jang, K. M., & Kim, J.* (2024). Multimodal Large Language Models as Built Environment Auditing Tools. The Professional Geographer, 1-7. https://doi.org/10.1080/00330124.2024.2404894

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30. Jones, W., & Kim, J.* (2024). The Uneven Geography of Access to Live Performances of Western Classical Music in the United States. Findings. https://doi.org/10.32866/001c.125761 (Jones conducted this research while enrolled as an undergraduate student at Virginia Tech.)

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29. Gyanwali, S., Karki, S., Jang, K. M., Crawford, T., Zhang, M., & Kim, J.* (2024). Implications for spatial non-stationarity and the neighborhood effect averaging problem (NEAP) in green inequality research: evidence from three states in the USA. Journal of Geographical Systems, 1-24. https://doi.org/10.1007/s10109-024-00448-x (Editors’ Choice Article: “… editors recognize as providing an especially significant contribution to the field…”)

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28. Atkins, C., Girgente, G., Shirzaei, M., & Kim, J.* (2024). Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies. Communications Earth & Environment, 5(1), 226. https://doi.org/10.1038/s43247-024-01392-w (Girgente conducted this research while enrolled as an undergraduate student at Virginia Tech.)

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27. Lu, Y., Kim, J., Shu, X., Zhang, W., & Wu, J. (2024). Confronting the controversy over neighborhood effect bias in green exposure: Using large-scale multi-temporal mobile signal data. Landscape and Urban Planning, 253, 105222. https://doi.org/10.1016/j.landurbplan.2024.105222

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26. Jang, K. M., Chen, J., Kang, Y., Kim, J., Lee, J., Duarte, F., & Ratti, C. (2024). Place identity: a generative AI’s perspective. Humanities and Social Sciences Communications, 11(1), 1-16. https://doi.org/10.1057/s41599-024-03645-7

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25. Ahmed, N., Lee, J., Liu, L., Kim, J., Jang, K. M., & Wang, J. (2024). The cost of climate change: A generalized cost function approach for incorporating extreme weather exposure into public transit accessibility. Computers, Environment and Urban Systems, 112, 102145. https://doi.org/10.1016/j.compenvurbsys.2024.102145

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24. Kim, J., & Jang, K. (2023). An examination of the spatial coverage and temporal variability of Google Street View (GSV) images in small- and medium-sized cities: A people-based approach. Computers, Environment and Urban Systems, 101, 101956. https://doi.org/10.1016/j.compenvurbsys.2023.101956

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23. Kim, J.*, & Lee, J. (2023). How does ChatGPT introduce transport problems and solutions in North America?. Findings, March. https://doi.org/10.32866/001c.72634
 

22. Kim, J. & Lee, B. (2023). Campus commute mode choice in a college town: An application of the integrated choice and latent variable (ICLV) model. Travel Behaviour and Society, 30, 249-261. https://doi.org/10.1016/j.tbs.2022.10.002

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21. Kim, J.*, Rapuri, S., Chuluunbaatar, E., Sumiyasuren, E., Lkhagvasuren, B., Budhathoki, N., & Laituri, M. (2023). Developing and examining the transit-based accessibility to hospitals of Ulaanbaatar, Mongolia, Habitat International, 131. https://doi.org/10.1016/j.habitatint.2022.102729

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20. Lee, J., & Kim, J. (2023). Social equity analysis of public transit accessibility to healthcare might be erroneous when travel time uncertainty impacts are overlooked. Travel Behaviour and Society, 32.   https://doi.org/10.1016/j.tbs.2023.100588

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19. Javanmard, R., Lee, J., Kim, J., Lu, L., & Diab, E. (2023). The impacts of the modifiable spatial unit problem (MSUP) on social equity analysis of public transit reliability. Journal of Transport Geography, 106, 103500.  https://doi.org/10.1016/j.jtrangeo.2022.103500

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18. Xu, T., Wang, S., Liu, Q., Kim, J., Zhang, J., Ren, Y., Ta, N., Wang, X., & Wu. J. (2023). Vegetation color exposure differences at the community and individual levels: An explanatory framework based on the neighborhood effect averaging problem. Urban Forestry & Urban Greening, 86, 128001. https://doi.org/10.1016/j.ufug.2023.128001

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17. Jin, C., Park, S., Ha, H. J., Lee, J., Kim, J., Hutchenreuther, J., & Nara, A. (2023). Predicting households’ residential mobility trajectories with geographically localized interpretable model-agnostic explanation (GLIME). International Journal of Geographical Information Science, 1-23. https://doi.org/10.1080/13658816.2023.2264921

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16. Kim, J.*, Hagen, E., Muindi, Z., Mbonglou, G., & Laituri, M. (2022). An examination of water, sanitation, and hygiene (WASH) accessibility and opportunity in urban informal settlements during the COVID-19 pandemic: Evidence from Nairobi, Kenya. Science of the Total Environment, 823, 153398. https://doi.org/10.1016/j.scitotenv.2022.153398

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15. Wang, J., Kim, J., & Kwan, M-P. (2022). An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data. Cartography and Geographic Information Science, 49(5), 385-406. https://doi.org/10.1080/15230406.2022.2056510

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14. Kim, Y., Kim, J., Ha, H., Nakajima, N, & Lee, J. (2022). Job accessibility as a lens for understanding the urban structure of colonial cities: A digital humanities study of the colonial Seoul in the 1930s using GIS. ISPRS International Journal of Geo-Information, 11(12), 614, 1-16. https://doi.org/10.3390/ijgi11120614

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13. Singh, S., Javanmard, R., Lee, J., Kim, J., & Diab, E. (2022). Evaluating the accessibility benefits of the new BRT system during the COVID-19 pandemic in Winnipeg, Canada. Journal of Urban Mobility, 2, 100016. https://doi.org/10.1016/j.urbmob.2022.100016

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12. Ha, H. J., Lee, J., Kim, J., & Kim, Y. (2022). Uncovering Inequalities in Food Accessibility between Koreans and Japanese in 1930s Colonial Seoul Using GIS and Open-Source Transport Analytics Tools. Sustainability, 14(19), 11852. https://doi.org/10.3390/su141911852

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11. Laituri, M., Richardson, R., Kim, J., Cline, L., Viscuso, S., & Schwartz, L. Examining second-order impacts of COVID-19 in urban areas. (2022). Annals of GIS, 28(4), 479-490. https://doi.org/10.1080/19475683.2021.1954087

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10. Kim, J., & Kwan, M.-P. (2021). How neighborhood effect averaging might affect assessment of individual exposures to air pollution: A study of ozone exposures in Los Angeles. Annals of the American Association of Geographers, 111(1), 121-140. https://doi.org/10.1080/24694452.2020.1756208

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9. Kim, J., & Kwan, M-P. (2021). Assessment of sociodemographic disparities in environmental exposure might be erroneous due to neighborhood effect averaging: Implications for environmental inequality research. Environmental Research, 195, 110519. https://doi.org/10.1016/j.envres.2020.110519

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8. Kim, J., & Kwan, M-P. (2021). The impact of the COVID-19 pandemic on people’s mobility: A longitudinal study of the U.S. from March to September of 2020, Journal of Transport Geography, 93, 103039. https://doi.org/10.1016/j.jtrangeo.2021.103039

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7. Kim, J., Kwan, M.-P., Levenstein, M. C., & Richardson, D. B. (2021). How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection. Cartography and Geographic Information Science, 48(1), 2-20.

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6. Kim, J., & Kwan, M-P. (2021). An examination of people’s privacy concerns, perceptions of social benefits, and acceptance for COVID-19 mitigation measures that harness location information: A comparative study of the U.S. and South Korea. ISPRS International Journal of Geo-Information, 10(1), 25, 1-23. https://doi.org/10.3390/ijgi10010025

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5. Kim, J., & Kwan, M-P. (2021). Travel time errors caused by geomasking might be different between transportation modes and types of urban area. Transactions in GIS, 25(4), 1910-26. https://doi.org/10.1111/tgis.12751

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4. Kim, Y., Lee, J., Kim, J., & Nakajima, N. The disparity in transit travel time between Koreans and Japanese in 1930s Colonial Seoul. (2021). Findings, July. https://doi.org/10.32866/001c.25226

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3. Huang, J., Kwan, M.-P., & Kim, J. (2021). How culture and sociopolitical tensions might influence people’s acceptance of COVID-19 control measures that use individual-level georeferenced data. ISPRS International Journal of Geo-Information, 10(7), 490, 1-19. https://doi.org/10.3390/ijgi10070490

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2. Kim, J., & Lee, B. (2019). More than travel time: New job accessibility index capturing the connectivity of transit services. Journal of Transport Geography, 78, 8-18. https://doi.org/10.1016/j.jtrangeo.2019.05.008

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1. Kim, J., & Kwan, M.-P. (2019). Beyond commuting: Ignoring individuals’ activity-travel patterns may lead to inaccurate assessments of their exposure to traffic congestion. International Journal of Environmental Research and Public Health, 16(1), 1-20. https://doi.org/10.3390/ijerph16010089