Taotao Cai
Taotao Cai

Dr. Taotao Cai

Senior Lecturer in Computing, University of Southern Queensland (UniSQ)
Contact & Links

About

Dr. Taotao Cai is a Senior Lecturer in Computing at the University of Southern Queensland (UniSQ) and an Honorary Lecturer at Macquarie University. He earned his Ph.D. degree from Deakin University in 2020, following two years at The University of Western Australia (Jan 2017 – Mar 2019) and over a year at Deakin University (Mar 2019 – Jul 2020) during his doctoral studies. Dr. Cai also holds a Master’s degree in Computer Science from Shenzhen University (2016).

Before joining UniSQ, Dr. Cai worked as a Postdoctoral Research Fellow at Macquarie University (Mar 2021 – Jan 2023) and as an Associate Research Fellow at Deakin University (Jul 2020 – Feb 2021). He has served in a range of teaching and academic leadership roles.

Research Interests

Grants & Key Projects

IG250200014 — SafeBuild AI: Intelligent Safety and Efficiency for Construction SMEs (2026–2027)
Role: Lead Chief Investigator (Lead CI) · Funding: AEA Ignite Round 2 · Amount: $549,886 (AEA $474,886 + Industry $75,000)

This project aims to develop an AI-powered safety assurance platform to reduce incidents and ease administrative burdens in Australian construction. We will create a lightweight, domain-specific LLM with construction-savvy reasoning using partner data. The key deliverable is a TRL 5 Proactive Safety Assurance Module, validated in the partner’s environment, that automates SWMS compliance auditing and generates dynamic safety checklists. Advancing the technology from TRL 3 to TRL 5 provides a clear commercialisation pathway for construction SMEs.

Official announcement: AEA Ignite news
High-Impact Recognition: Selected as the featured project for Queensland in the Australian Government’s official announcement (only one representative initiative per state). The release specifically highlighted this project’s capacity “to improve construction safety using AI compliance detection.”
IG240100414 — Intelligent FCAS Agent for Renewable Energy Power Systems (2025–2026)
Role: Chief Investigator (CI) (Lead: Dr. Yanming Zhu, Griffith University) · Funding: AEA Ignite Round 1 · Amount: $508,442 (AEA $429,720 + Industry $78,722)

The goal is to analyse grid data and predict grid frequency fluctuations to optimise power dispatch and battery storage in solar power systems, enabling efficient intelligent energy management. This reduces power supply costs and enhances the stability and efficiency of the national grid. Building on the team’s TRL 3 techniques, the project targets a semi-integrated system and aims to reach TRL 5 to support commercialisation.

News (recent)

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