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Dr Kai Li Lim

St Baker Fellow in E-Mobility

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

St Baker Fellow in E-Mobility - Res

Dow Centre for Sustainable Engineering Innovation
Faculty of Engineering, Architecture and Information Technology

Affiliate of Dow Centre for Sustain

Dow Centre for Sustainable Engineering Innovation
Faculty of Engineering, Architecture and Information Technology
kaili.lim@uq.edu.au

Overview

Dr Kai Li Lim is the inaugural St Baker Fellow in E-Mobility at the UQ Dow Centre for Sustainable Engineering Innovation. Specialising in data science, engineering, and emerging technologies, Dr Lim focuses on real-time vehicle telematics, infrastructure management, and computer vision-based autonomous driving.

At UQ, Dr Lim's research centres on electric vehicle (EV) usage and charging patterns to inform adoption policies and strategies. His work includes examining trends for incentive design and assessing the environmental and economic impacts of EVs. Dr Lim's current focus is on charging reliability and addressing EV drivers' pain points. His research has been featured in academic, industry, and media publications, facilitating discussions with various stakeholders.

Dr Lim has published a range of articles, book chapters, and conference papers in reputable venues. He has delivered invited talks and appeared in media outlets such as ABC, Courier Mail, and The Conversation. Collaborating with various UQ schools, including Civil Engineering, Electrical Engineering and Computer Science (EECS), Economics, and Environment, Dr Lim has secured funding for projects on topics like carbon emissions offset after EV uptake and evaluating price incentives for EV charging using real-time data.

In addition to his work at UQ, Dr Lim collaborates closely with the UC Davis Electric Vehicle Research Center, where he recently completed a six-month visiting fellowship on EV charging. He engages in speaking events and networking opportunities centred on sustainability and transportation innovation, delivering keynote speeches at conferences and industry roundtables.

Dr Lim holds 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, supported by the Australian Government under the Research Training Programme.

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 advanced platforms to collect and analyse electromobility (e-mobility) data, particularly addressing EV charging reliability and consumer challenges. The availability of high-speed internet allows vehicles and infrastructures to transmit substantial real-time data with high precision. However, many existing data platforms are device-specific, creating manufacturer-restricted data silos.

In his role as the St Baker Fellow, Dr Lim designs and develops a unified data platform that consolidates information from various connected mobility devices using cloud computing, initially focusing on data from EVs, particularly Tesla vehicles.

His research aims to improve the understanding of spatial EV usage and charging patterns. By integrating data analytics with machine learning, Dr Lim provides insights and predictions about EV behaviours, with an emphasis on enhancing charging reliability and addressing consumer pain points. These findings support the development of effective adoption policies, incentive designs, and strategies to address the environmental and economic impacts of electric vehicles. This work keeps industry and government collaborators informed about emerging EV trends, thereby enhancing the broader impact on electromobility.

Qualifications

  • 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

Publications

View all Publications

Grants

View all Grants

Supervision

  • Autonomous vehicle control strategies for driving safety

    Doctor Philosophy

View all Supervision

Publications

Book Chapter

  • REView: a unified telemetry platform for electric vehicles and charging infrastructure

    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

  • Cooperative multi-robot navigation–SLAM, visual odometry and semantic segmentation

    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

  • RFID and dead-reckoning- based indoor navigation for visually impaired pedestrians

    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

  • RFID and dead-reckoning-based indoor navigation for visually impaired pedestrians

    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

  • Assistive navigation systems for the visually impaired

    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

  • Data in mobility as a service: a real-world trial in Queensland, Australia

    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.

  • Driving and charging an EV in Australia: A real-world analysis

    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.

  • Integrated modular safety system design for intelligent autonomous vehicles

    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

  • A Modular Software Framework for Autonomous Vehicles

    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

  • Implementation of semantic segmentation for road and lane detection on an autonomous ground vehicle with LIDAR

    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

  • Uninformed multigoal pathfinding on grid maps

    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

  • Autonomous vehicle control strategies for driving safety

    Doctor Philosophy — Associate Advisor

    Other advisors:

This staff member is a UQ Expert for media in the following fields:

electric vehicles, self-driving cars

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ORCID: 0000-0002-9278-0344

Scopus ID: 57200753561

Personal Profile: Link

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