Associate Professor Jiwon Kim
Associate Professor

Jiwon Kim

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Phone: 
+61 7 334 63008

Background

Jiwon Kim is an Associate Professor in Transport Engineering and the Director of Higher Degree by Research in the School of Civil Engineering at the University of Queensland. She was a DECRA Fellow (2019-2022) sponsored by the Australian Research Council. She joined UQ in 2014 after completing her PhD research at Northwestern University. Prior to joining Northwestern, she worked at Samsung C&T (Engineering & Construction Group). She received Bachelor’s and Master’s degrees in civil engineering from Korea University.

Her research interests broadly encompass the application of Artificial Intelligence and Machine Learning (AI/ML) to enhance prediction, automation, and insight generation in transportation and urban mobility. She is passionate about developing intelligent autonomous systems that facilitate real-time traffic management and control, mobility service optimization, and traveller support. Her current research explores the potential of deep learning, reinforcement learning, and other cutting-edge AI/ML approaches to achieve these objectives.

Availability

Associate Professor Jiwon Kim is:
Available for supervision

Fields of research

Built Environment and Design Civil engineering Engineering Information and Computing Sciences Transport engineering Urban and regional planning

Qualifications

  • Doctor of Philosophy, Northwestern University

Research interests

  • Machine Learning and Artificial Intelligence (AI) applications in transport and logistics

    Intelligent decision support and automation for transport networks and mobility services (generative AI and LLMs, multi-agent systems, deep learning, reinforcement learning)

  • Real-time traffic management and operations

    Leveraging predictive analytics, anomaly detection, and Digital Twin technology to enhance situational awareness and support data-driven decision-making

  • Spatiotemporal trajectory mining

    Analysing movement trajectories from diverse mobile sensors (GPS, drones, IoT) across urban environments, leveraging data mining, pattern recognition, entity linking, and visualisation techniques for actionable insight generation

  • Traffic simulation and traffic flow theory

    Traffic simulation (microsimulation/mesosimulation), dynamic traffic assignment (DTA), population synthesis and synthetic data generation

Search Professor Jiwon Kim’s works on UQ eSpace

114 works between 2010 and 2025
All (114) Journal Article (46) Conference Publication (67) Other Outputs (1)

61 - 80 of 114 works

2018

Journal Article

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

Yildirimoglu, Mehmet and Kim, Jiwon (2018). Identification of communities in urban mobility networks using multi-layer graphs of network traffic. Transportation Research Part C: Emerging Technologies, 89, 254-267. doi: 10.1016/j.trc.2018.02.015

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

2018

Journal Article

Time-dependent route scheduling on road networks

Li, Lei, Kim, Jiwon, Xu, Jiajie and Zhou, Xiaofang (2018). Time-dependent route scheduling on road networks. SIGSPATIAL Special, 10 (1), 10-14. doi: 10.1145/3231541.3231545

Time-dependent route scheduling on road networks

2018

Conference Publication

A large-scale neural network model for real-time crash prediction in urban road networks

Wang, Guangxing and Kim, Jiwon (2018). A large-scale neural network model for real-time crash prediction in urban road networks. Transportation Research Board Annual Meeting, Washington, DC USA, 7-11 January 2018.

A large-scale neural network model for real-time crash prediction in urban road networks

2018

Conference Publication

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

Yildirimoglu, Mehmet and Kim, Jiwon (2018). Identification of communities in urban mobility networks using multi-layer graphs of network traffic. Transportation Research Board Annual Meeting, Washington, DC USA, 7-11 January 2018.

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

2018

Conference Publication

Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data

Ahn, Sanghyung, Hislop-Lynch, Samuel Richard, Kim, Jiwon and Zhu, Roy (2018). Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data. 2017 Winter Simulation Conference, WSC 2017, Las Vegas, NV United States, 3-6 December 2017. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2017.8248193

Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data

2018

Conference Publication

Inferring socioeconomic attributes of public transit passengers using classifiers

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2018). Inferring socioeconomic attributes of public transit passengers using classifiers. ATRF 2018 - Australasian Transport Research Forum 2018, Darwin, NT Australia, 30 October – 1 November 2018. Canberra ACT Australia: ATRF, Commonwealth of Australia.

Inferring socioeconomic attributes of public transit passengers using classifiers

2018

Conference Publication

Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2018). Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data. Australasian Transport Research Forum, Darwin, NT, Australia, 30 October – 1 November 2018.

Investigating the correlation between activity similarity and trip similarity of public transit passengers using smart card data

2018

Conference Publication

Identifying relevant predictors and spatial relations of traffic parameters for network-wide short-term traffic prediction

Hasan, Md Mahmud, Kim, Jiwon and Prato, Carlo (2018). Identifying relevant predictors and spatial relations of traffic parameters for network-wide short-term traffic prediction. Transportation Research Board Annual Meeting, Washington, DC, United States, 7-11 January 2018.

Identifying relevant predictors and spatial relations of traffic parameters for network-wide short-term traffic prediction

2018

Conference Publication

Balancing computational requirements with performance in model predictive traffic control

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai (2018). Balancing computational requirements with performance in model predictive traffic control. Transportation Research Board Annual Meeting, Washington, DC, United States, 7-11 January 2018.

Balancing computational requirements with performance in model predictive traffic control

2017

Journal Article

Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data

Kim, Jiwon, Corcoran, Jonathan and Papamanolis, Marty (2017). Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data. Transportation Research. Part C: Emerging Technologies: an international journal, 83, 146-164. doi: 10.1016/j.trc.2017.08.005

Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data

2017

Journal Article

Spatial-temporal similarity correlation between public transit passengers using smart card data

Faroqi, Hamed, Mesbah, Mahmoud and Kim, Jiwon (2017). Spatial-temporal similarity correlation between public transit passengers using smart card data. Journal of Advanced Transportation, 2017 1318945, 1-15. doi: 10.1155/2017/1318945

Spatial-temporal similarity correlation between public transit passengers using smart card data

2017

Journal Article

Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai L. (2017). Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation. Transportation Research Part C: Emerging Technologies, 82, 43-62. doi: 10.1016/j.trc.2017.06.014

Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation

2017

Conference Publication

Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks

Kim, Jiwon, Zheng, Kai, Corcoran, Jonathan, Ahn, Sanghyung and Papmanolis, Marty (2017). Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks. Transportation Research Board 96th Annual Meeting, Washington DC United States, December 2016. Washington, DC United States: Transportation Research Board.

Trajectory Flow Map: Graph-based approach to analyse temporal evolution of aggregated traffic flows in large-scale urban networks

2017

Conference Publication

Balancing computational requirements with performance in model predictive traffic control

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai L. (2017). Balancing computational requirements with performance in model predictive traffic control. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra ACT Australia: ATRF, Commonwealth of Australia.

Balancing computational requirements with performance in model predictive traffic control

2017

Conference Publication

A large scale neural network model for crash prediction in urban road networks

Wang, Guangxing and Kim, Jiwon (2017). A large scale neural network model for crash prediction in urban road networks. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

A large scale neural network model for crash prediction in urban road networks

2017

Conference Publication

Combining intersection control schedule optimisation with green light optimal speed advisory in a connected vehicle environment

Stebbins, Simon, Hickman, Mark, Kim, Jiwon and Vu, Hai (2017). Combining intersection control schedule optimisation with green light optimal speed advisory in a connected vehicle environment. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2017.

Combining intersection control schedule optimisation with green light optimal speed advisory in a connected vehicle environment

2017

Conference Publication

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

Yildirimoglu, Mehmet and Kim, Jiwon (2017). Identification of communities in urban mobility networks using multi-layer graphs of network traffic. 20th EURO Working Group on Transportation Meeting, EWGT 2017, Budapest, Hungary, 4-6 September 2017. Elsevier. doi: 10.1016/j.trpro.2017.12.070

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

2017

Conference Publication

Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces

Hislop-Lynch, Samuel R., Ahn, SangHyung and Kim, Jiwon (2017). Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Pedestrian tracking framework utilising computer vision for rapid analysis of public spaces

2017

Conference Publication

Spatial variable selection methods for network-wide short-term traffic prediction

Hasan, Md. Mahmud, Kim, Jiwon and Prato, Carlo (2017). Spatial variable selection methods for network-wide short-term traffic prediction. ATRF 2017 - Australasian Transport Research Forum 2017, Auckland, New Zealand, 27 - 29 November 2017. Canberra, ACT Australia: ATRF, Commonwealth of Australia.

Spatial variable selection methods for network-wide short-term traffic prediction

2017

Conference Publication

Granger causality method to detect spatial dependency in a road traffic network and its application in traffic flow prediction

Hasan, Md Mahmud and Kim, Jiwon (2017). Granger causality method to detect spatial dependency in a road traffic network and its application in traffic flow prediction. Transportation Research Board Annual Meeting, Washington, DC, United States, 8 - 12 January 2017.

Granger causality method to detect spatial dependency in a road traffic network and its application in traffic flow prediction

Current funding

  • 2024 - 2028
    Safe and efficient eco-driving using connected and automated vehicles
    ARC Discovery Projects
    Open grant
  • 2020 - 2025
    Making Spatiotemporal Data More Useful: An Entity Linking Approach
    ARC Discovery Projects
    Open grant

Past funding

  • 2022 - 2024
    Framework and Conceptual Solution for Integrating Road Network Operations Planning into Real-time Traffic Management
    iMove Cooperative Research Centre
    Open grant
  • 2022 - 2023
    UQ AWARE - Jiwon Kim
    UQ Amplify Women's Academic Research Equity
    Open grant
  • 2020 - 2021
    UQ AWARE - Dr Jiwon KIM
    UQ Amplify Women's Academic Research Equity
    Open grant
  • 2019 - 2024
    Real-time Analytics on Urban Trajectory Data for Road Traffic Management
    ARC Linkage Projects
    Open grant
  • 2019 - 2022
    An Integrated Demographic and Transport Demand Modelling Framework (ID-TDM)
    iMove Cooperative Research Centre
    Open grant
  • 2019 - 2023
    Data-driven Simulation of Large Traffic Networks using Trajectory Data
    ARC Discovery Early Career Researcher Award
    Open grant
  • 2018 - 2019
    Urban mobility analytics-based crash risk prediction for real-time traffic incident management
    UQ Early Career Researcher
    Open grant

Availability

Associate Professor Jiwon Kim is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • We are currently hiring a research assistant / software developer.

    This Advanced Research Assistant will work as a part of Dr Jiwon Kim's research team to provide a technical support for developing and maintaining open-source software that is designed to analyse large-scale urban mobility data, specifically spatio-temporal trajectory data of vehicles and people travelling around a city (e.g., trajectories from GPS, Bluetooth, cellphones, and transit smart cards).

    Please contact jiwon.kim@uq.edu.au for more information.

  • Intelligent Transport Systems (ITS)

    - Big data analytics and artificial intelligence (AI) applications

    - Real-time traffic management and control

    - Spatio-temporal analysis of trajectory data in road networks

    - Data-driven approaches to traffic estimation and prediction

    - Congestion management and avoidance

    - Incident detection and traffic incident management

  • AI and Machine Learning for Urban Mobility

    - Learning human mobility behaviours from large-scale movement data

    - Imitation learning for human behaviour modelling in traffic networks

    - Multi-agent reinforcement learning for network traffic managmenet

  • Traffic flow theory and simulation

    - Advanced analysis techniques for micro- and meso-scopic traffic simulation models

    - Analysis of traffic flow breakdown phenomena

    - Modeling driver behavior and traffic flow characteristics under a connected and/or autonomous vehicle environment (e.g., V2V, V2I, and self-driving car)

    - Analysis of traffic flow variables using new sources of data (e.g., GPS devices, RFID tags, radar, and video)

  • Other topics

    - Use of video data (e.g., CCTV, drones) for traffic data collection and analysis

    - Resilient transport systems; vulnerability and risk assessment of road networks related to extreme weather events

    Dr. Kim is also happy to consider other topics related to transport planning and operations, traffic modeling and analysis, and urban traffic management.

Supervision history

Current supervision

  • Doctor Philosophy

    Model interpretation and data-centric modeling for advanced traffic prediction (MINDMAP)

    Principal Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Model interpretation and data-centric modelling for advanced traffic prediction

    Principal Advisor

  • Doctor Philosophy

    Real-time Analytics on Urban Trajectory Data for Road Traffic Management

    Associate Advisor

    Other advisors: Dr Miao Xu

  • Doctor Philosophy

    An investigation on the allocation of fast-charging stations considering renewable energy sources

    Associate Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Methods for Public Transport Operations Planning and Management

    Associate Advisor

    Other advisors: Professor Mark Hickman

  • Doctor Philosophy

    Queue Length Estimation and Prediction at Isolated Signalized Intersections

    Associate Advisor

    Other advisors: Dr Mehmet Yildirimoglu

  • Doctor Philosophy

    Modelling Driving Behaviour of Mixed Autonomous and Human-Driven Vehicles Flow

    Associate Advisor

    Other advisors: Professor Zuduo Zheng

Completed supervision

Enquiries

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communications@uq.edu.au