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

121 works between 2010 and 2025
All (121) Journal Article (53) Other Outputs (1) Conference Publication (67)

21 - 40 of 121 works

2023

Conference Publication

An autonomous eco-driving strategy for mixed traffic in the vicinity of signalized intersection using deep reinforcement learning

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2023). An autonomous eco-driving strategy for mixed traffic in the vicinity of signalized intersection using deep reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC USA, 8-12 January 2023.

An autonomous eco-driving strategy for mixed traffic in the vicinity of signalized intersection using deep reinforcement learning

2023

Conference Publication

MSGNN: a multi-structured graph neural network model for real-time incident prediction in large traffic networks

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2023). MSGNN: a multi-structured graph neural network model for real-time incident prediction in large traffic networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2023.

MSGNN: a multi-structured graph neural network model for real-time incident prediction in large traffic networks

2023

Conference Publication

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2023). Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation. Transportation Research Board Annual Meeting, Washington, DC United States, 8-12 January.

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

2023

Conference Publication

Automatic traffic flow anomaly detection with reinforcement learning

He, Dan, Kim, Jiwon, Ruan, Boyu and Shi, Hua (2023). Automatic traffic flow anomaly detection with reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC USA, 8-12 January 2023.

Automatic traffic flow anomaly detection with reinforcement learning

2023

Journal Article

Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach

Zhong, Miner, Kim, Jiwon and Zheng, Zuduo (2023). Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach. IEEE Open Journal of Intelligent Transportation Systems, 4, 14-29. doi: 10.1109/ojits.2022.3233904

Estimating link flows in road networks with synthetic trajectory data generation: inverse reinforcement learning approach

2022

Journal Article

An efficient algorithm for maximum trajectory coverage query with approximation guarantee

He, Dan, Zhou, Thomas, Zhou, Xiaofang and Kim, Jiwon (2022). An efficient algorithm for maximum trajectory coverage query with approximation guarantee. IEEE Transactions on Intelligent Transportation Systems, PP (99), 1-13. doi: 10.1109/tits.2022.3207499

An efficient algorithm for maximum trajectory coverage query with approximation guarantee

2022

Conference Publication

Online traffic incident prediction with hybrid graph-based neural network and continual learning

Tran, Thanh, He, Dan, Kim, Jiwon and Hickman, Mark (2022). Online traffic incident prediction with hybrid graph-based neural network and continual learning. Australasian Transport Research Forum, Adelaide, SA Australia, 28-30 September 2022.

Online traffic incident prediction with hybrid graph-based neural network and continual learning

2022

Conference Publication

A cooperative eco-driving system for mixed traffic on urban roads

Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2022). A cooperative eco-driving system for mixed traffic on urban roads. Australasian Transport Research Forum, Adelaide, 28-30 September 2022.

A cooperative eco-driving system for mixed traffic on urban roads

2022

Conference Publication

Threshold-free anomaly detection on traffic flow data with reinforcement learning

He, Dan, Ruan, Boyu, Kim, Jiwon and Shi, Hua (2022). Threshold-free anomaly detection on traffic flow data with reinforcement learning. Australasian Transport Research Forum, Adelaide, SA Australia, 28-30 September 2022.

Threshold-free anomaly detection on traffic flow data with reinforcement learning

2022

Journal Article

Transformer-based map-matching model with limited labeled data using transfer-learning approach

Jin, Zhixiong, Kim, Jiwon, Yeo, Hwasoo and Choi, Seongjin (2022). Transformer-based map-matching model with limited labeled data using transfer-learning approach. Transportation Research Part C: Emerging Technologies, 140 103668, 103668. doi: 10.1016/j.trc.2022.103668

Transformer-based map-matching model with limited labeled data using transfer-learning approach

2022

Journal Article

A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: an application of hierarchical crash frequency model

Manirul Islam, Sheikh, Washington, Simon, Kim, Jiwon and Haque, Mazharul (2022). A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: an application of hierarchical crash frequency model. Accident Analysis and Prevention, 171 106663, 106663. doi: 10.1016/j.aap.2022.106663

A comprehensive analysis on the effects of signal strategies, intersection geometry, and traffic operation factors on right-turn crashes at signalised intersections: an application of hierarchical crash frequency model

2022

Journal Article

Targeted advertising in the public transit network using smart card data

Faroqi, Hamed, Mesbah, Mahmoud, Kim, Jiwon and Khodaii, Ali (2022). Targeted advertising in the public transit network using smart card data. Networks and Spatial Economics, 22 (1), 97-124. doi: 10.1007/s11067-022-09558-9

Targeted advertising in the public transit network using smart card data

2022

Conference Publication

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2022). Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation. Australasian Transport Research Forum, Adelaide, SA, Australia, 28-30 September 2022.

Multivariate time-varying Kalman filter approach for cycle-based maximum queue length estimation

2021

Journal Article

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

Sun, Jie and Kim, Jiwon (2021). Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks. Transportation Research. Part C: Emerging Technologies, 128 103114, 103114. doi: 10.1016/j.trc.2021.103114

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

2021

Journal Article

TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2021). TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning. Transportation Research Part C: Emerging Technologies, 128 103091, 103091. doi: 10.1016/j.trc.2021.103091

TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

2021

Journal Article

Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors

Sharma, Anshuman, Zheng, Zuduo, Kim, Jiwon, Bhaskar, Ashish and Mazharul Haque, Md. (2021). Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors. Transportation Research Part C: Emerging Technologies, 124 102934, 1-21. doi: 10.1016/j.trc.2020.102934

Assessing traffic disturbance, efficiency, and safety of the mixed traffic flow of connected vehicles and traditional vehicles by considering human factors

2021

Conference Publication

TrajGAIL: generating urban vehicle trajectories using generative adversarial imitation learning

Choi, Seongjin, Kim, Jiwon and Yeo, Hwasoo (2021). TrajGAIL: generating urban vehicle trajectories using generative adversarial imitation learning. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

TrajGAIL: generating urban vehicle trajectories using generative adversarial imitation learning

2021

Conference Publication

Maximum queue length estimation at signalized intersections using shockwave theory and Kalman filter

Abewickrema, Wanuji, Yildirimoglu, Mehmet and Kim, Jiwon (2021). Maximum queue length estimation at signalized intersections using shockwave theory and Kalman filter. Australasian Transport Research Forum 2021, Brisbane, QLD Australia, 8-10 December 2021. Australasian Transport Research Forum.

Maximum queue length estimation at signalized intersections using shockwave theory and Kalman filter

2021

Conference Publication

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

Sun, Jie and Kim, Jiwon (2021). Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

2021

Conference Publication

Estimating link flows from limited traffic volume and sparse trajectory data: reinforcement learning approaches

Zhong, Miner, Kim, Jiwon and Zheng, Zuduo (2021). Estimating link flows from limited traffic volume and sparse trajectory data: reinforcement learning approaches. Transportation Research Board Annual Meeting, Washington, DC, United States, 25-29 January 2021.

Estimating link flows from limited traffic volume and sparse trajectory data: reinforcement learning approaches

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

Looking for a supervisor? Read our advice on how to choose 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

    SEEN ¿ A Sustainable Energy-Efficient Novel Driver Behaviour Model for the Future of Transport: Development, Assessment, and Application

    Associate Advisor

    Other advisors: Professor Zuduo Zheng

  • Doctor Philosophy

    Methods for Public Transport Operations Planning and Management

    Associate Advisor

    Other advisors: Professor Mark Hickman

  • Doctor Philosophy

    A Study on Map-Matching on Wireless Traffic Sensor Data

    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

Completed supervision

Enquiries

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