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Dr Kai Li Lim
Dr

Kai Li Lim

Email: 
Phone: 
+61 7 344 36210

Overview

Background

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.

Availability

Dr Kai Li Lim is:
Available for supervision
Media expert

Qualifications

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

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.

Works

Search Professor Kai Li Lim’s works on UQ eSpace

24 works between 2014 and 2024

21 - 24 of 24 works

2016

Journal Article

Pathfinding for the navigation of visually impaired people

Lim, Kai Li, Seng, Kah Phooi, Yeong, Lee Seng, Ang, Li Minn, Ch', Sue Inn and ng, N.A. (2016). Pathfinding for the navigation of visually impaired people. International Journal of Computational Complexity and Intelligent Algorithms, 1 (1). doi: 10.1504/ijccia.2016.077467

Pathfinding for the navigation of visually impaired people

2015

Journal Article

Uninformed pathfinding: A new approach

Lim, Kai Li, Seng, Kah Phooi, Yeong, Lee Seng, Ang, Li-Minn and Ch'Ng, Sue Inn (2015). Uninformed pathfinding: A new approach. Expert Systems with Applications, 42 (5), 2722-2730. doi: 10.1016/j.eswa.2014.10.046

Uninformed pathfinding: A new approach

2015

Book Chapter

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

Assistive navigation systems for the visually impaired

2014

Conference Publication

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

Uninformed multigoal pathfinding on grid maps

Funding

Past funding

  • 2022 - 2023
    Highlighting the benefits of price incentives for electric vehicle charging: evidence from a field experiment with telematics data
    Energy Consumers Australia Influence Grants
    Open grant
  • 2022 - 2023
    Emissions and economic modelling of road and rail freight in NSW
    iMove Cooperative Research Centre
    Open grant
  • 2021 - 2023
    Longitudinal and spatial database of vehicle ownership and energy consumption
    Australian Urban Research Infrastructure Network
    Open grant

Supervision

Availability

Dr Kai Li Lim is:
Available for supervision

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

Supervision history

Current supervision

  • Doctor Philosophy

    Autonomous vehicle control strategies for driving safety

    Associate Advisor

    Other advisors: Dr Mehmet Yildirimoglu

Media

Enquiries

Contact Dr Kai Li Lim directly for media enquiries about:

  • electric vehicles
  • self-driving cars

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au