Chaeyeon Han Ph.D. Student

Research Projects

• Exploring the Geography of Social Ties add_circle in the U.S. based onThanksgiving Destination (on-going)
• Website Urban Sensing of Pedestrians through Integrated, Cost-effective, and Scalable Audio Sensor Networks (on-going)
• Mental Health Facility Visits Before and After the Outbreak of Covid-19: The Role of Walkable Built Environment add_circle (on-going)
• A Bibliometric Literature Review on Artificial Intelligence in Urban Studies add_circle (on-going)

• A CyberGIS-enabled Pandemic Warning System Using Social Media Data
• CyberGIS-VIZ, 2021
• Development and Validation of Regional Models of HIV Vulnerabilities and Solutions, 2021

• Analysis of the Subway Ridership Change in Seoul after the Outbreak of COVID-19
• A Comparative Analysis of Trends of Disaster Risk Research using Topic Modeling & Network Analysis Published in Korean Society of Hazard Mitigation (KOSHAM)

Exploring the Geography of Social Ties in the U.S. based onThanksgiving Destination

Chaeyeon Han, Uijeong Hwang, Subhrajit Guhathakurta

#human_geography, #social_ties, #human_mobility, #social_network, #family_ties

This project aimed to visually identify the geography of the familial and social ties in the United States. To accomplish this, we have conducted an in-depth analysis of travel patterns during four years of Thanksgiving holidays, a time when the majority of individuals visit their families. The study assumes that trips made around Thanksgiving Day are predominantly made to visit people with kin relationships (e.g., family, close friends). This study employs SafeGraph data, which includes the weekly foot traffic of individuals with their anonymized smartphone data. The data also provides 1) visitors’ residential location at the Census Block Group level and 2) information on destination POIs, including locations. Based on the O-D patterns in the four years of Thanksgiving weeks that we collected (2018-2021), we used repetitive visits as a proxy of kin networks among family or close friends. Then, we visualized and examined the geographic distribution of social/family ties in the U.S.

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Mental Health Facility Visits Before and After the Outbreak of Covid-19: The Role of Walkable Built Environment

Chaeyeon Han, Uijeong Hwang, Bon Woo Koo, Subhrajit Guhathakurta

#Built-Environment, #Mental-Health, #COVID-19, #Walkability, #Walk-Score, #SafeGraph

This study examined the evolving impact of neighborhood walkability on mental health outcomes across three different stages of the COVID-19 pandemic. Utilizing Walk Score data to quantify neighborhood walkability and analyzing mental health facility visit frequencies using SafeGraph data alongside COVID-19 case rates, this study provides a thorough analysis of the mediating role of the pandemic in the dynamic between walkability and mental health. We found a consistent negative association between Walk Score and frequency of mental health facility visits, suggesting that neighborhoods characterized by better accessibility to Point-Of-Interests (POIs) tend to have better mental health outcomes. Furthermore, mediation analysis shows that walkability not only directly enhances mental health but also indirectly contributes to improved outcomes by correlating with lower COVID-19 cases. The study underscores the enduring value of walkable urban designs in enhancing mental well-being and reducing the spread of COVID-19, advocating for urban planning and policies that prioritize walkability.

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Teaching

• Spring 22 Graduate Teaching Assistant: NRES100 Fundamentals of Environmental Science (Virtual)
• Fall 21 Graduate Teaching Assistant: UP510-DA Plan Making

• Spring 21 Graduate Teaching Assistant: UP460 Urban Transportation Modeling
• Fall 20 Graduate Teaching Assistant: UP494 Advanced Data Science for Planners
• Fall 20 Graduate Teaching Assistant: UP199 Data Science for Planners

• Winter & Spring 20 Teaching Assistant: YCS1001 Computational Thinking and SW Programming

Publication

1. A Comparative Analysis of Trends of Disaster Risk Research using Topic Modeling & Network Analysis Published in Korean Society of Hazard Mitigation (KOSHAM)

1. Seshadri, P., Han, C., Koo, B., Posner, N., Guhathakurta, S., & Lerch, A. (2024). ASPED: An Audio Dataset for Detecting Pedestrians. Access through arXiv
2. Han, C., Hwang, U., Koo, B., Guhathakurta, S. (2024). A Bibliometric Literature Review on Artificial Intelligence, Machine Learning, and Deep Learning in Urban Studies

Position

• Aug. 2022 - present Doctoral Research Assistant, Center for Spatial Planning Analysis and Visualization, Georgia Tech
• Oct. 2021 - May. 2022 Graduate Research Assistant, CyberGIS Center, University of Illinois at Urbana-Champaign