Affiliate Faculty
Dr. Kang directs the GISense Lab at the University of Texas at Austin. The GISense Lab focuses on modeling and understanding human-environment relationships at place and tackling real-world challenges (e.g., spatial-socio inequity, public health, housing, crime, climate change) in urban systems with spatiotemporal big data analytics, geospatial artificial intelligence (GeoAI), and maps and geovisualizations. There are three key research themes of the GISense Lab:
(1) an emphasis on place to observe human subjective experiences such as emotion, perception, cognition, personality, and creativity;
(2) a recognition of the need to develop ethical cartography and GeoAI methods (e.g., machine learning, deep learning, Generative AI, Diffusion, reinforcement learning) for modeling geographic phenomena and urban environments;
(3) a focus on human-environment interactions in urban systems to solve practical problems and inform decision-making processes, including but not limited to public health, spatial-socio inequity, housing, and crime.
As the director of the GISense Lab, Dr. Kang was a postdoctoral researcher at the MIT SENSEable City Lab, received his Ph.D. from the University of Wisconsin-Madison, and obtained his bachelor's degree from Wuhan University. He had working experience at the University of South Carolina, Google X, and MoBike. Dr. Kang’s research mainly focuses on Human-centered Geospatial AI and Data Science to understand human experience at place and develop ethical and responsible geospatial artificial intelligence (GeoAI) approaches. He was the recipient of the Waldo-Tobler Young Researcher Award by the Austrian Academy of Sciences, CaGIS Rising Award, CPGIS Education Excellence Award, etc. He was the founder of the non-profit educational organization GISphere that summarizes global GIS programs and faculty. His work has been recognized as the best papers in the Annals of GIS and the AAG GISS/CyberGIS/EPBG groups. He has served as the associate editor of the Computational Urban Science, the editorial board member of Humanities and Social Sciences Communications, and has been a reviewer of over 50 academic journals, such as Nature Communications, Nature Human Behaviour. Dr. Kang has served on multiple academic committees, such as the AAG GISS/Cartography/CyberGIS and CPGIS.
Postdoc in Urban Planning, MIT Senseable City Lab
Ph.D. in Geography (GIScience), University of Wisconsin-Madison
M.S. in Computer Science, University of Wisconsin-Madison
M.S. in Cartography and GIS, University of Wisconsin-Madison
B.S. in Geographic Information Science, Wuhan University, China
Chen, Y., Nelson, J., Zhou, B., Zhou, R.Z., Ye, S., Liu, H., Gu, Z., Kar, A., Kwon, H.,
Chen, P., Sun, M. and Kang, Y.*, 2025. Where are GIScience faculty hired from? Analyzing faculty mobility and research themes through hiring networks. Cartography and Geographic Information Science.
Wang, J., Tan, H., Liao, B., Jiang, A., Fei, T., Huang, Q., Tu, Z., Ye, S. and Kang, Y.*, 2025. SounDiT: Geo-contextual soundscape-to-landscape generation. arXiv preprint arXiv:2505.12734. https://arxiv.org/pdf/2505.12734
Gu, Z., Li, W., Zhou, B., Wang, Y., Chen, Y., Ye, S., Wang, K., Gu, H. and Kang, Y.*, 2025. GISphere knowledge graph for geography education: recommending graduate Geographic Information System/Science programs. Transactions in GIS, 29(1), p.e13283. https://onlinelibrary.wiley.com/doi/pdf/10.1111/tgis.13283
Qiao, S., Fang, X., Wang, J., Zhang, R., Li, X. and Kang, Y.*, 2025. Generative AI for thematic analysis in a maternal health study: coding semistructured interviews using large language models. Applied Psychology: Health and Well‐Being, 17(3), p.e70038. https://iaap-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/aphw.70038
Jang, K.M., Chen, J., Kang, Y.*, Kim, J., Lee, J., Duarte, F. and Ratti, C., 2024. Place identity: a generative AI’s perspective. Humanities and Social Sciences Communications, 11(1), pp.1-16. https://www.nature.com/articles/s41599-024-03645-7
Zhuang, Y., Kang, Y.*, Fei, T., Bian, M. and Du, Y., 2024. From hearing to seeing: Linking auditory and visual place perceptions with soundscape-to-image generative artificial intelligence. Computers, Environment and Urban Systems, 110, p.102122. https://www.sciencedirect.com/science/article/pii/S0198971524000516
Kang, Y., Gao, S. and Roth, R.E., 2024. Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics. Cartography and Geographic Information Science, pp.1-32. https://www.tandfonline.com/doi/full/10.1080/15230406.2023.2295943
Kang, Y., Zhang, Q. and Roth, R., 2023. The ethics of AI-Generated maps: A study of DALLE 2 and implications for cartography. arXiv preprint arXiv:2304.10743. https://arxiv.org/pdf/2304.10743
Kang, Y., Abraham, J., Ceccato, V., Duarte, F., Gao, S., Ljungqvist, L., Zhang, F., Näsman, P. and Ratti, C., 2023. Assessing differences in safety perceptions using GeoAI and survey across neighbourhoods in Stockholm, Sweden. Landscape and Urban Planning, 236, p.104768. https://www.sciencedirect.com/science/article/pii/S0169204623000877
Wang, Y., Kang, Y.*, Liu, H., Hou, C., Zhou, B., Ye, S., Liu, Y., Rao, J., Pei, Z., Ye, X. and Gao, S., 2023. Choosing GIS graduate programs from afar: Chinese students' perspectives. Transactions in GIS, 27(2), pp.450-475. https://onlinelibrary.wiley.com/doi/full/10.1111/tgis.13037
Kang, Y., Wu, K., Gao, S., Ng, I., Rao, J., Ye, S., Zhang, F. and Fei, T., 2022. STICC: a multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity. International Journal of Geographical Information Science, 36(8), pp.1518-1549. https://www.tandfonline.com/doi/full/10.1080/13658816.2022.2053980
Kang, Y., Zhang, F., Gao, S., Peng, W. and Ratti, C., 2021. Human settlement value assessment from a place perspective: Considering human dynamics and perceptions in house price modeling. Cities, 118, p.103333. https://www.sciencedirect.com/science/article/pii/S026427512100233X
Kang, Y., Zhang, F., Peng, W., Gao, S., Rao, J., Duarte, F. and Ratti, C., 2021. Understanding house price appreciation using multi-source big geo-data and machine learning. Land Use Policy, 111, p.104919. https://www.sciencedirect.com/science/article/pii/S0264837719316746
Kang, Y., Zhang, F., Gao, S., Lin, H. and Liu, Y., 2020. A review of urban physical environment sensing using street view imagery in public health studies. Annals of GIS, 26(3), pp.261-275. https://www.tandfonline.com/doi/full/10.1080/19475683.2020.1791954
Kang, Y., Jia, Q., Gao, S., Zeng, X., Wang, Y., Angsuesser, S., Liu, Y., Ye, X. and Fei, T., 2019. Extracting human emotions at different places based on facial expressions and spatial clustering analysis. Transactions in GIS, 23(3), pp.450-480. https://onlinelibrary.wiley.com/doi/full/10.1111/tgis.12552
Kang, Y., Gao, S. and Roth, R.E., 2019. Transferring multiscale map styles using generative adversarial networks. International Journal of Cartography, 5(2-3), pp.115-141. https://www.tandfonline.com/doi/full/10.1080/23729333.2019.1615729
Ceccato, V., Kang, Y., Abraham, J., Näsman, P., Duarte, F., Gao, S., Ljungqvist, L., Zhang, F. and Ratti, C., 2025. What makes a place safe? Assessing AI-generated safety perception scores using Stockholm’s street view images. The British Journal of Criminology, p.azaf017. https://academic.oup.com/bjc/advance-article/doi/10.1093/bjc/azaf017/81…
Abraham, J., Kang, Y., Ceccato, V., Näsman, P., Duarte, F., Gao, S., Ljungqvist, L., Zhang, F. and Ratti, C., 2025. Crime and visually perceived safety of the built environment: A deep learning approach. Annals of the American Association of Geographers, pp.1-21. https://www.tandfonline.com/doi/full/10.1080/24694452.2025.2501998
Hou, C., Zhang, F., Kang, Y., Gao, S., Li, Y., Duarte, F. and Li, S., 2025. Transferred bias uncovers the balance between the development of physical and socioeconomic environments of cities. Annals of the American Association of Geographers, 115(1), pp.148-166. https://www.tandfonline.com/doi/full/10.1080/24694452.2024.2412173
Wang, C., Kang, Y., Gong, Z., Zhao, P., Feng, Y., Zhang, W. and Li, G., 2025. CartoAgent: a multimodal large language model-powered multi-agent cartographic framework for map style transfer and evaluation. International Journal of Geographical Information Science, pp.1-34. https://www.tandfonline.com/doi/full/10.1080/13658816.2025.2507844
Ito, K., Kang, Y., Zhang, Y., Zhang, F. and Biljecki, F., 2024. Understanding urban perception with visual data: A systematic review. Cities, 152, p.105169. https://www.sciencedirect.com/science/article/pii/S0264275124003834
Huang, J., Fei, T., Kang, Y., Li, J., Liu, Z. and Wu, G., 2024. Estimating urban noise along road network from street view imagery. International Journal of Geographical Information Science, 38(1), pp.128-155.
Zhang, F., Fan, Z., Kang, Y., Hu, Y. and Ratti, C., 2021. “Perception bias”: Deciphering a mismatch between urban crime and perception of safety. Landscape and Urban Planning, 207, p.104003. https://www.sciencedirect.com/science/article/pii/S0169204620314870
Kruse, J., Kang, Y., Liu, Y.N., Zhang, F. and Gao, S., 2021. Places for play: Understanding human perception of playability in cities using street view images and deep learning. Computers, Environment and Urban Systems, 90, p.101693. https://www.sciencedirect.com/science/article/pii/S0198971521001009
Hou, X., Gao, S., Li, Q., Kang, Y., Chen, N., Chen, K., Rao, J., Ellenberg, J.S. and Patz, J.A., 2021. Intracounty modeling of COVID-19 infection with human mobility: Assessing spatial heterogeneity with business traffic, age, and race. Proceedings of the National Academy of Sciences, 118(24), p.e2020524118. https://www.pnas.org/doi/full/10.1073/pnas.2020524118
Yang, J., Rong, H., Kang, Y., Zhang, F. and Chegut, A., 2021. The financial impact of street-level greenery on New York commercial buildings. Landscape and Urban Planning, 214, p.104162. https://www.sciencedirect.com/science/article/pii/S0169204621001250
Gao, S., Rao, J., Kang, Y., Liang, Y. and Kruse, J., 2020. Mapping county-level mobility pattern changes in the United States in response to COVID-19. SIGSpatial Special, 12(1), pp.16-26. https://dl.acm.org/doi/abs/10.1145/3404820.3404824
Gao, S., Rao, J., Kang, Y., Liang, Y., Kruse, J., Dopfer, D., Sethi, A.K., Reyes, J.F.M., Yandell, B.S. and Patz, J.A., 2020. Association of mobile phone location data indications of travel and stay-at-home mandates with COVID-19 infection rates in the US. JAMA network open, 3(9), pp.e2020485-e2020485. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2770249
Zhang, F., Zu, J., Hu, M., Zhu, D., Kang, Y., Gao, S., Zhang, Y. and Huang, Z., 2020. Uncovering inconspicuous places using social media check-ins and street view images. Computers, Environment and Urban Systems, 81, p.101478. https://www.sciencedirect.com/science/article/pii/S0198971519306003
Liu, Z., Yang, A., Gao, M., Jiang, H., Kang, Y., Zhang, F. and Fei, T., 2019. Towards feasibility of photovoltaic road for urban traffic-solar energy estimation using street view image. Journal of Cleaner Production, 228, pp.303-318. https://www.sciencedirect.com/science/article/pii/S0959652619313538
Rao, J., Gao, S., Kang, Y. and Huang, Q., 2020. LSTM-TrajGAN: A deep learning approach to trajectory privacy protection. In 11th International Conference on Geographic Information Science (GIScience 2021)-Part I (2020). Schloss-Dagstuhl-Leibniz Zentrum für Informatik. https://arxiv.org/abs/2006.10521
Li, B., Gao, S., Liang, Y., Kang, Y., Prestby, T., Gao, Y. and Xiao, R., 2020. Estimation of regional economic development indicator from transportation network analytics. Scientific reports, 10(1), p.2647. https://www.nature.com/articles/s41598-020-59505-2
Gao, S., Rao, J., Liu, X., Kang, Y., Huang, Q. and App, J., 2019. Exploring the effectiveness of geomasking techniques for protecting the geoprivacy of Twitter users. Journal of Spatial Information Science, (19), pp.105-129. https://josis.org/index.php/josis/article/view/107
Waldo-Tobler Young Researcher Award by the Austrian Academy of Sciences
CaGIS Rising Award
CPGIS Education Excellence Award
Human-centered (Geospatial) Data Science
Geospatial AI
GIS
Social Sensing
Urban Computing
Human Mobility
Crime
Environmental Psychology
Maternal Health