
Overview
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
Qualifications
- Doctor of Philosophy, Northwestern University
Research interests
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Machine Learning and Artificial Intelligence (AI) applications in transport and logistics
Data-driven modelling of traffic networks and mobility services; Data-driven traffic simulation; AI and multi-agent systems (reinforcement learning, imitation learning)
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Predictive analytics for real-time traffic management and operations
Real-time traffic estimation and prediction for Intelligent Transportation Systems (ITS); Traffic incident management; Decision support systems and automation
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Urban Trajectory Data Analytics
Urban vehicle trajectories in large-scale networks: data mining, pattern recognition, trajectory prediction and generation, and visualization; urban mobility insights and travel behavour
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Traffic simulation and Traffic flow theory
Traffic simulation (microsimulation/mesosimulation); Dynamic traffic assignment (DTA); Scenario generation and analysis
Works
Search Professor Jiwon Kim’s works on UQ eSpace
2024
Journal Article
Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections
Yang, Zhiwei, Zheng, Zuduo, Kim, Jiwon and Rakha, Hesham (2024). Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections. Transportation Research Part C: Emerging Technologies, 165 104683, 104683. doi: 10.1016/j.trc.2024.104683
2023
Journal Article
Toward data-driven simulation of network-wide traffic: a multi-agent imitation learning approach using urban vehicle trajectory data
Sun, Jie and Kim, Jiwon (2023). Toward data-driven simulation of network-wide traffic: a multi-agent imitation learning approach using urban vehicle trajectory data. IEEE Transactions on Intelligent Transportation Systems, 25 (7), 6645-6657. doi: 10.1109/tits.2023.3343452
2023
Journal Article
Variables affecting the risk of vehicle collisions in Australian road tunnels
Hidayat, Edwin, Lange, David, Karlovsek, Jurij and Kim, Jiwon (2023). Variables affecting the risk of vehicle collisions in Australian road tunnels. Journal of Road Safety, 34 (4), 20-30. doi: 10.33492/JACRS-D-22-00032
2023
Journal Article
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 Part C: Emerging Technologies, 156 104354. doi: 10.1016/j.trc.2023.104354
2023
Journal Article
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 Part C: Emerging Technologies, 154 104238, 1-19. doi: 10.1016/j.trc.2023.104238
2023
Journal Article
A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersections
Islam, Sheikh Manirul, Washington, Simon, Kim, Jiwon and Haque, Md Mazharul (2023). A hierarchical multinomial logit model to examine the effects of signal strategies on right-turn crash injury severity at signalised intersections. Accident Analysis and Prevention, 188 107091, 1-14. doi: 10.1016/j.aap.2023.107091
2023
Conference Publication
Map-matching on wireless traffic sensor data with a sequence-to-sequence model
Zhu, Zichun, He, Dan, Hua, Wen, Kim, Jiwon and Shi, Hua (2023). Map-matching on wireless traffic sensor data with a sequence-to-sequence model. 24th IEEE International Conference on Mobile Data Management (MDM), Singapore, Singapore, 3-6 July 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/mdm58254.2023.00048
2023
Conference Publication
A deep learning framework to generate synthetic mobility data
Arkangil, Eren, Yildirimoglu, Mehmet, Kim, Jiwon and Prato, Carlo (2023). A deep learning framework to generate synthetic mobility data. 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Nice, France, 14-16 June 2023. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/mt-its56129.2023.10241677
2023
Journal Article
A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration
Islam, Sheikh Manirul, Washington, Simon, Kim, Jiwon and Haque, Md. Mazharul (2023). A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration. Accident Analysis and Prevention, 184 106993, 106993. doi: 10.1016/j.aap.2023.106993
2023
Journal Article
Autonomous anomaly detection on traffic flow time series with reinforcement learning
He, Dan, Kim, Jiwon, Shi, Hua and Ruan, Boyu (2023). Autonomous anomaly detection on traffic flow time series with reinforcement learning. Transportation Research Part C: Emerging Technologies, 150 104089, 1-21. doi: 10.1016/j.trc.2023.104089
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.
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.
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.
2023
Conference Publication
Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning
Lin, Lin, Kim, Jiwon, Sun, Jie and Ahn, Sanghyung (2023). Interpretable data-driven car-following modelling with adversarial inverse reinforcement learning. Transportation Research Board Annual Meeting, Washington, DC, United States, 8-12 January 2023.
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.
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
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
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.
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.
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.
Funding
Current funding
Past funding
Supervision
Availability
- Associate Professor Jiwon Kim is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
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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.
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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
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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
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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)
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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
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Doctor Philosophy
Zonal inference in congestion modelling
Principal Advisor
Other advisors: Honorary Professor Carlo Prato, Professor Zuduo Zheng
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Doctor Philosophy
Data-driven Modelling of Urban Traffic Networks using Spatial Trajectory Data
Principal Advisor
Other advisors: Dr SangHyung Ahn
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Doctor Philosophy
Hybrid Deep Learning Platform for Real-time Traffic Incident Prediction and Management
Principal Advisor
Other advisors: Professor Mark Hickman
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Doctor Philosophy
Model interpretation and data-centric modeling for advanced traffic prediction (MINDMAP)
Principal Advisor
Other advisors: Dr SangHyung Ahn, Dr Mehmet Yildirimoglu
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Doctor Philosophy
Model interpretation and data-centric modelling for advanced traffic prediction
Principal Advisor
Other advisors: Dr Mehmet Yildirimoglu
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Master Philosophy
Synthetic Travel Demand Generation using Data-Driven Methods
Principal Advisor
Other advisors: Honorary Professor Carlo Prato, Professor Zuduo Zheng
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Master Philosophy
Deep Representation Learning of Spatio-Temporal Trajectory Data
Principal Advisor
Other advisors: Professor Mark Hickman
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Doctor Philosophy
Interpretable Adversarial Inverse Reinforcement Learning for Driving Behaviour Learning
Principal Advisor
Other advisors: Dr SangHyung Ahn
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Doctor Philosophy
Graph-based Learning Platform for Real-time Traffic Incident Prediction and Management
Principal Advisor
Other advisors: Professor Mark Hickman
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Doctor Philosophy
Methods for Public Transport Operations Planning and Management
Associate Advisor
Other advisors: Professor Mark Hickman
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Doctor Philosophy
Real-time Analytics on Urban Trajectory Data for Road Traffic Management
Associate Advisor
Other advisors: Dr Mehmet Yildirimoglu
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Master Philosophy
Visualisation of passenger and freight transport flows
Associate Advisor
Other advisors: Professor Mark Hickman
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Doctor Philosophy
An investigation on the allocation of fast-charging stations considering renewable energy sources
Associate Advisor
Other advisors: Dr Mehmet Yildirimoglu
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Doctor Philosophy
Real-time Analytics on Urban Trajectory Data for Road Traffic Management
Associate Advisor
Other advisors: Dr Miao Xu
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Doctor Philosophy
Modelling Driving Behaviour of Mixed Autonomous and Human-Driven Vehicles Flow
Associate Advisor
Other advisors: Professor Zuduo Zheng
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Doctor Philosophy
Autonomous Eco-driving in the Vicinity of Signalized Intersection Using Deep Reinforcement Learning
Associate Advisor
Other advisors: Professor Zuduo Zheng
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Doctor Philosophy
Operation Strategy of Shared Autonomous Vehicles with Various Passenger Capacity on the Basis of Ridesharing
Associate Advisor
Other advisors: Professor Zuduo Zheng
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Doctor Philosophy
Operation Strategy of Shared Autonomous Vehicles with Various Passenger Capacity on the Basis of Ridesharing
Associate Advisor
Other advisors: Professor Zuduo Zheng
Completed supervision
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2024
Doctor Philosophy
Safety Evaluation on Right-turn Traffic Control Strategies at Signalised Intersection using Hierarchical Models
Principal Advisor
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2023
Doctor Philosophy
Solid-phase temperature analysis and correction for multi-scale fire experimentation
Principal Advisor
Other advisors: Dr Cristian Maluk, Dr Juan Hidalgo Medina, Dr Felix Wiesner
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2021
Master Philosophy
Estimating Link Flows from Limited Traffic Volume and Sparse Trajectory Data: Generative Modelling Approaches
Principal Advisor
Other advisors: Professor Zuduo Zheng
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2020
Doctor Philosophy
Understanding Spatial Dependency Structure in Urban Road Traffic Networks: Methodology and Applications in Short Term Traffic Prediction
Principal Advisor
Other advisors: Honorary Professor Carlo Prato
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2020
Master Philosophy
Automatic detection and analysis of long-term changes in travel patterns of public transport passengers using Smart-Card data
Principal Advisor
Other advisors: Professor Mark Hickman
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2024
Doctor Philosophy
Development of a risk management framework for enhancing tunnel safety operation
Associate Advisor
Other advisors: Dr Jurij Karlovsek, Associate Professor David Lange
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2023
Doctor Philosophy
Capture, Processing and Analysis of Vehicle Trajectories from Multiple Unmanned-Aerial-Vehicles with Computer-Vision and Artificial-Intelligence
Associate Advisor
Other advisors: Dr SangHyung Ahn
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2020
Doctor Philosophy
Developing a Model for Targeted Transit Advertising using Smart Card Data
Associate Advisor
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2019
Doctor Philosophy
Understanding and Modelling the Car-Following Behaviour of Connected Vehicles
Associate Advisor
Other advisors: Professor Zuduo Zheng
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2018
Master Philosophy
Computer vision based pedestrian trajectory analysis
Associate Advisor
Other advisors: Dr SangHyung Ahn
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2018
Doctor Philosophy
Leveraging Connected Vehicle Technology and Model Predictive Control to Improve Traffic Network Performance
Associate Advisor
Other advisors: Professor Mark Hickman
Media
Enquiries
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