UIJEONG "UJ" HWANG

City and Regional Planning PhD | Spatial Data Scientist

ABOUT ME

I am a highly motivated data scientist specializing in spatial analytics, GIS, urban informatics, and machine/deep learning. With a strong background in research spanning 8 years, my work focuses on delivering actionable insights to inform effective planning practices to foster a more accommodating and safer transportation environment.

My interests center around travel behavior — I study (1) the ways in which people move around, (2) the factors that make people choose more walking, biking, and public transit, and (3) how the travel behavior is associated with public health and quality of life.

I also enjoy applying effective visualization techniques and state-of-the-art data analytical tools to urban studies. If you want to get a glimpse of what I do, see Research Highlights below.

Experience

  • Senior Planner

    Transportation Access & Mobility

    Atlanta Regional Commission

    Aug 2023 - present

  • Research Assistant

    Center for Spatial Planning Analytics and Visualization

    Georgia Institute of Technology

    Aug 2019 - Dec 2023

  • Junior Researcher

    Transportation System Research Center

    Seoul Institute

    Jul 2018 - Jul 2019

Education

  • PhD in City and Regional Planning

    Georgia Institute of Technology

    Aug 2019 - Dec 2023

  • MS in Urban Analytics

    Georgia Institute of Technology

    Aug 2021- Aug 2023

  • BS+MS in Urban Planning and Design

    cum laude, University of Seoul

    Mar 2010 - Aug 2017

Technical Skills

  • Languages: Python | R | SQL | JavaScript | HTML & CSS
  • Libraries & frameworks:
    • Web dev: React.js | Node.js | jQuery
    • Visualization: Mapbox.js | D3.js | kepler.gl | deck.gl
    • Machine learning: PyTorch | TensorFlow | OpenCV | MMCV
    • High performance computing: MVAPICH2
  • GIS: ArcGIS | QGIS
  • Other software: Tableau | Photoshop | Illustrator | AutoCAD

Interests

  • Travel behavior | Active mobility | Smart growth | Transit equity
  • Geospatial analytics | Visualization & mapping | GIS
  • Data science | Machine/Deep Learning | Computer vision
  • Network analysis | Urban modeling and simulation

Impact of Bike Lanes
on Mode Choice

Making people drive less is the utmost goal in the major U.S. cities. By simulating bike routes of 120,000 trips and running a mode choice model, this study demonstrates that bike lanes not only support cyclists but also induce people to shift from driving to walking and public transit.

street environments and the risk of bike near-miss

One of the challenges in biking safety research is the rarity of bike-involved accidents. A viable alternative is to study near-misses, which occur quite frequently. Using Simra, an app-based, crowdsourced dataset on bike routes and near-misses, this study examines the association between various street environments and the risk of near misses in Berlin, Germany.

Covid-19 and
Changes in Eating Habit

Eating behaviors are certainly one of the primary things that the pandemic has affected in negative ways. Using restaurant foot traffic data from SafeGraph, this study shows in what way our eating habits became unhealthier during the pandemic and how the changes differ by neighborhood characteristics.

"Streetscape" as
part of "servicescape"

Walkable streetscapes are conducive to the perceived safety and aesthetics of the street frontage. This study extends the concept of servicescapes to the surrounding street environment. The analysis shows that the quality of streetscapes (measured through a computer vision based method by Koo et al. (2022)) has positive effects on customer satisfaction (derived from Yelp reviews).

Algorithm for generating
complete street network

Complete streets aim to ensure safe travel for all street users regardless of their age, ability, or mode of transportation. Due to the inevitable piecemeal nature of those projects, however, complete streets are not very complete from a network standpoint. This study investigates the design of a complete street network by using bike lane networks as connective threads.

micro-simulating
the impact of road diet

This study investigates the impact of a planned road diet on 10th Street NW on roadway performances. A microscopic traffic simulation, building upon the work of Treiber et al. (2000), was conducted for two scenarios (i.e., before and after the road diet) under varying AADTs. The findings suggest that the road diet will significantly reduce peak-hour speed, and traffic flow is projected to moderately decrease by 11% due to the reduced capacity.

Inequalities in Food Access in Atlanta

Food is everywhere, but healthy food is not everywhere. Many neighborhoods in U.S. cities are surrounded by fast/junk food outlets and have limited access to fresh foods. This dashboard demonstrates which neighborhoods in the City of Atlanta are at risk of being public health hazards and how it is correlated with the neighborhoods' income.

publications

Hwang, U., Lieu, S., Dalmeijer. K., Guan. H., Guhathakurta, S., & Van Hentenryck, P. (in press). Measuring Transit Equity of an On-demand Multimodal Transit System. Journal of the American Planning Association.
Hwang, U., Kim, I., Guhathakurta, S., & Van Hentenryck, P. (2024). Comparing Different Methods for Connecting Bike Lanes to Generate a Complete Bike Network and Identify Potential Complete Streets in Atlanta. Journal of Cycling and Micromobility Research, 100015.
Hwang, U. (2023). Breaking Myths behind “Bikelash”: Empirical Analyses on The Role of Protected Bike Lanes on Creating a Sustainable, Equitable, and Safer Transportation Environment [Doctoral dissertation, Georgia Institute of Technology].
Hwang, U., & Guhathakurta, S. (2023). Exploring the Impact of Bike Lanes on Transportation Mode Choice: A simulation-based, route-level impact analysis. Sustainable Cities and Society, 104318.
Koo, B., Hwang, U., & Guhathakurta, S. (2023). Streetscapes as Part of Servicescapes: Can walkable streetscapes make local businesses more attractive?. Computers, Environment and Urban Systems, 106, 102030
Hwang, U., & Woo, M. (2020). Analysis of inter-relationships between urban decline and urban sprawl in city-regions of South Korea. Sustainability, 12(4), 1656.