Junghwan Kim

• Principles of GIS (GEOG 2084/5064)
• Generative AI Applications in Social Science (GEOG 4094/5094)
• Geospatial Analysis of Mobility (GEOG 4304/5304)
• Analysis In GIS (GEOG 4314)
• Analysis of Spatial Data (GEOG 5034)

• American Association of Geographers (AAG) Council Outstanding Graduate Student Paper Award (2019)
• Peter Gould Student Paper Award from the AAG Health and Medical Geography Specialty Group (2019)
• 2023 Most Downloaded Paper Awards (co-authored paper; Annals of GIS) (2023)
• Student Research Presentation Award from the Race/Ethnicity/Place Conference, First Prize (2020)
• American Planning Association (APA) Transportation Planning Division Student Paper Award, Third Prize (2018)
• APA National Smart Cities Student Design Competition Winner (in Team, 2017)
• Outstanding Teaching Assistant Award from the Department of Urban and Regional Planning at the UIUC (2018)
• Student Paper Award from the Korean-American Association for Geospatial and Environmental Sciences (2020)
• President Award from the Korean Planning Association (2016)
• Recipient of the Study Abroad Scholarship and National Science and Engineering Scholarship from the South Korean Government (2016)

Geospatial Analysis and Optimization for Veterans’ Healthcare Access in Pain Management
Sponsor: Whole Health Consortium Seed Grant (PI)
2025

Assessing Older Adults’ Perceptions and Human-Machine Interface Preferences in Autonomous Human-AI Transportation (HAT) Systems: An Experimental Mixed-Method Approach
Sponsor: ICTAS COE Engineering Faculty Organization-Opportunity (Co-PI)
2024-25

A new green space exposure index utilizing AI methods and an eye-tracking device
Sponsor: 4-VA Collaborative Research Grant (PI) 
2024-25

Examining the Impacts of Green Space Exposure on People's Health Outcomes by Integrating AI and GIScience Methods
Sponsor: 4-VA Pre-Tenure Faculty Research Grant (PI)
2023

Assessing urban walkability with an artificial intelligence (AI) method: A case study in small-sized U.S. cities
Sponsor: ISCE Social Science PREP Program (PI) 
2022-23

• Renshaw, A., Lourentzou, I., Lee, J., Crawford, T., & Kim, J. (2024). 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
• Lu, Y., Kim, J., Shu, X., Zhang, W., & Wu, J. (2025). 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
• 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
• 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
• 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
• 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. 
  https://doi.org/10.1016/j.cities.2024.105339
• Kim, J., Lee, J., Thornhill T. [...] Gonsalves, G. (2024). Accessibility of Opioid Treatment Programs Based on Conventional vs Perceived Travel Time Measures. JAMA Network Open.
   https://doi.org/10.1001/jamanetworkopen.2024.0209
• Kim, J.*, Park, J., Lee., J., & Jang. K. (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 U.S. Cities. 
  https://doi.org/10.1016/j.cities.2024.104852
• Kim, J.*, Lee, J., Jang, K., & 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. 102085. 
  https://doi.org/10.1016/j.tele.2023.102085
• Kim, J.*, Rapuri, S., Wang, K., 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. 
  https://doi.org/10.1080/19475683.2024.2304205 
  (Undergraduate Students: Rapuri; Wang)
• 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. 
  https://doi.org/10.1038/s43247-024-01392-w 
  (Graduate student: Atkins; Undergraduate Student: Girgente)
• Gyanwali, S., Karki, S., Jang, K., 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. 
  https://doi.org/10.1007/s10109-024-00448-x 
  (Graduate student: Gyanwali; Karki)
• Jang, K., Chen, J., Kang, Y., Kim, J., Lee, J., Duare, F., & Ratti, C. Place identity: a generative AI’s perspective. Humanities and Social Sciences Communications. 
  https://doi.org/10.1057/s41599-024-03645-7
• Ahmed, N., Lee, J., Liu, L., Kim, J., Jang, K., & 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. 
  https://doi.org/10.1016/j.compenvurbsys.2024.102145
• 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. 102. 
  https://doi.org/10.1016/j.compenvurbsys.2023.101956
• 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
• 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. 
  https://doi.org/10.1016/j.tbs.2022.10.002  
• 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
• 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  
• 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
• 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
• Xu, T., Wang, S., Liu, Q., Kim, J., Zhang, J., Ren, Y., ... & 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
• 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
• 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
• 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
• 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
• 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
• 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   
• 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
• 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
• 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
• 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. 
  https://doi.org/10.1080/15230406.2020.1794976
• 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
• 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  
• 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
• 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
• 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
• 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