Dr Kai Li Lim

St Baker Fellow in E-Mobility

School of Chemical Engineering
Faculty of Engineering, Architecture and Information Technology


As the inaugural St Baker Fellow in E-Mobility at The UQ Dow Centre for Sustainable Engineering Innovation, Dr Kai Li Lim specialises in data science, engineering, and emerging technologies. His expertise is applied to real-time vehicle telematics, infrastructure management, and computer vision-based autonomous driving, with a notable thesis on "Connected Autonomous Electromobility."

Dr Lim's research at UQ concentrates on EV usage and charging patterns to inform adoption policies and strategies. He empirically examines trends for incentive design, along with the environmental and economic impacts of electric vehicles. His research has been featured in numerous academic, industry, and media publications, leading to valuable discussions with various stakeholders.

Throughout his career, Dr Lim has published a range of articles, book chapters, and conference papers in reputable venues. He has delivered invited talks and made media appearances in outlets such as the ABC, Courier Mail, and The Conversation. Dr Lim actively collaborates with various schools at UQ, including Information Technology and Electrical Engineering (ITEE), Civil Engineering, Economics, and Earth and Environmental Sciences (SEES). He has successfully secured funding for UQ projects, exploring topics like carbon emissions offset after EV uptake and evaluating price incentives for EV charging using real-time data.

Dr Lim actively engages in speaking events and networking opportunities centred on sustainability and innovation in transportation. He has delivered keynote speeches at conferences and industry roundtables, fostering connections within the field.

Holding a BEng (Hons) degree in electronic and computer engineering from the University of Nottingham, an MSc degree in computer science from Lancaster University, and a PhD degree from The University of Western Australia, Dr Lim was fully supported by the Australian Government under the Research Training Programme for his PhD studies.

Research Interests

  • Electric vehicles
    Vehicle electronics, system design, telematics, data management
  • Autonomous vehicles
    Visual navigation, machine learning, sensor fusion, sensor integration, path planning, software architecture design

Research Impacts

Dr Kai Li Lim's research focuses on developing innovative platforms to collect and analyse electromobility (e-mobility) data. With the widespread availability of high-speed internet, vehicles and their infrastructures transmit vast amounts of real-time data with high precision and interoperability. However, many current data platforms are device-specific, resulting in manufacturer-restricted data silos.

In his role as the Fellow, Dr Lim designs and develops a cohesive data platform to consolidate information from a wide range of connected mobility devices. He builds the platform using cloud computing, with initial data sourced from electric vehicles (EVs), particularly Tesla vehicles.

Dr Lim's research contributes to a better understanding of spatial EV usage and charging patterns. By integrating data analytics with machine learning, his work offers valuable insights and predictions regarding EV behaviours. These findings have the potential to inform and guide adoption policies, incentive design, and strategies addressing the environmental and economic impacts of electric vehicles. This research ultimately serves to keep industry and government collaborators informed of emerging EV behaviours and trends, further enhancing the impact of his work on electromobility.


  • Doctor of Philosophy of Artificial Intelligence and Robotics, University of Western Australia
  • Masters (Research) of Computer Science, Lancaster University
  • Bachelor (Honours) of Electrical and Computer Engineering, University of Nottingham


View all Publications


  • Doctor Philosophy

View all Supervision


Book Chapter

  • Lim, Kai Li, Speidel, Stuart and Bräunl, Thomas (2020). REView: a unified telemetry platform for electric vehicles and charging infrastructure. Connected vehicles in the Internet of Things: concepts, technologies and frameworks for the IoV. (pp. 167-219) edited by Zaigham Mahmood. Cham, Switzerland: Springer Nature . doi: 10.1007/978-3-030-36167-9_8

  • Reid, Robert G., Lim, Kai Li and Bräunl, Thomas (2020). Cooperative multi-robot navigation–SLAM, visual odometry and semantic segmentation. Cooperative localization and navigation: theory, research, and practice. (pp. 181-198) edited by Chao Gao, Guorong Zhao and Hassen Fourati. Boca Raton, FL, United States: CRC Press. doi: 10.1201/9780429507229-10

  • Lim, Kai Li, Seng, Kah Phooi, Yeong, Lee Seng and Ang, Li-Minn (2018). RFID and dead-reckoning- based indoor navigation for visually impaired pedestrians. Smart technologies: breakthroughs in research and practice. (pp. 1-16) edited by Information Resources Management Association. Hershey, PA, United States: IGI Global. doi: 10.4018/978-1-5225-2589-9.ch001

  • Lim, Kai Li, Seng, Kah Phooi, Yeong, Lee Seng and Ang, Li-Minn (2017). RFID and dead-reckoning-based indoor navigation for visually impaired pedestrians. Handbook of research on recent developments in intelligent communication application. (pp. 380-396) edited by Siddhartha Bhattacharyya, Nibaran Das, Debotosh Bhattacharjee and Anirban Mukherjee. Hershey, PA United States: IGI Global. doi: 10.4018/978-1-5225-1785-6.ch015

  • Lim, Kai Li, Yeong, Lee Seng, Seng, Kah Phooi and Ang, Li-Minn (2015). Assistive navigation systems for the visually impaired. Encyclopedia of Information Science and Technology, Third Edition. (pp. 315-327) Hershey, PA, United States: IGI Global. doi: 10.4018/978-1-4666-5888-2.ch030

Journal Article

Conference Publication

  • Rahbar, Maisie, Lim, Kai Li, Whitehead, Jake and Hickman, Mark (2022). Data in mobility as a service: a real-world trial in Queensland, Australia. Australasian Transport Research Forum 2022 Proceedings, Adelaide, SA Australia, 28-30 September 2022. Canberra, ACT Australia: Australasian Transport Research Forum.

  • Philip, Thara, Lim, Kai Li and Whitehead, Jake (2022). Driving and charging an EV in Australia: A real-world analysis. Australasian Transport Research Forum (ATRF), Adelaide, SA, Australia, 28-30 September 2022.

  • Drage, Thomas, Lim, Kai Li, Hai Koh, Joey En, Gregory, David, Brogle, Craig and Braunl, Thomas (2021). Integrated modular safety system design for intelligent autonomous vehicles. 2021 IEEE Intelligent Vehicles Symposium (IV), Nagoya, Japan, 11-17 July 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IV48863.2021.9575662

  • Lim, Kai Li, Drage, Thomas, Podolski, Roman, Meyer-Lee, Gabriel, Evans-Thompson, Samuel, Lin, Jason Yao-Tsu, Channon, Geoffrey, Poole, Mitchell and Bräunl, Thomas (2018). A Modular Software Framework for Autonomous Vehicles. 2018 IEEE Intelligent Vehicles Symposium (IV), Changshu, China, 26-30 June 2018. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IVS.2018.8500474

  • Lim, Kai Li, Drage, Thomas and Bra, Thomas (2017). Implementation of semantic segmentation for road and lane detection on an autonomous ground vehicle with LIDAR. 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Daegu, Korea, 16-18 November 2017. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/MFI.2017.8170358

  • Lim, Kai Li, Yeong, Lee Seng, Ch'Ng, Sue Inn, Seng, Kah Phooi and Ang, Li-Minn (2014). Uninformed multigoal pathfinding on grid maps. Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/InfoSEEE.2014.6946181

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Associate Advisor

    Other advisors: