Dr. Taotao Cai
Senior Lecturer (Level C) · Program Director, Master of Cyber Security
Cartoon portrait of Taotao Cai
Senior Lecturer in Computing · UniSQ

Dr. Taotao Cai

Artificial intelligence, graph learning, and trustworthy AI for real-world systems, with a strong focus on translational, industry-engaged research.

Graph Learning Trustworthy AI Industry Collaboration Sustainable Systems

Profile

Dr Taotao Cai is a Senior Lecturer in Computing at the University of Southern Queensland (UniSQ), Program Director for the Master of Cyber Security, and an Honorary Lecturer at Macquarie University. He has also undertaken leadership roles in HDR coordination and major course convenorship in Data Science and Artificial Intelligence.

He commenced his fully funded PhD in Computer Science at The University of Western Australia in January 2017 and transferred to Deakin University in March 2019 following his principal supervisor’s move. He completed his PhD at Deakin University in November 2020. Prior to this, he obtained an M.Phil. in Computer Science from Shenzhen University. Before joining UniSQ, he was an Associate Research Fellow at Deakin University and a Postdoctoral Research Fellow at Macquarie University.

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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CSC2220 Artificial Intelligence

An interactive atlas of AI history, agent systems, world models, landmark papers, and videos for students and curious visitors.

AI timeline Papers Videos

Teaching & Supervision

Course leadership, curriculum design, and HDR supervision across AI and software systems.

Courses Mentoring UniSQ

Service & Professional Activities

Editorial roles, reviewer contributions, and conference organization for the research community.

Reviewer PC Member Organizer

Miscellaneous

Personal favorites and selected videos that reflect interests beyond academic work.

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