Tao Liu | 刘韬

Graduating PhD Candidate in Computer Science

Teaching (Higher Education) | Embedded AI & IoT Research | Engineering & Technical Support

Queensland University of Technology

[email protected] Brisbane, Australia
Profile

About

Experienced university teaching staff with a multidisciplinary background across computer science and engineering, including embedded systems, electronics, wireless networking, cybersecurity, and AI/ML. I have several years of experience delivering university-level teaching across both foundational and specialised computer science subjects, with consistently strong student feedback for clear explanations, effective communication, responsiveness, and practical technical support.

My teaching is supported by substantial hands-on academic and technical experience. Alongside classroom and laboratory teaching, I work with students and researchers in electronics, robotics, embedded systems, and embedded AI, providing practical engineering support, troubleshooting, and guidance on project development. This breadth allows me to connect theoretical concepts with real systems and to support students with varied technical backgrounds.

I am also completing a PhD in Computer Science, with research focused on low-power wireless systems and post-quantum security. This combination of teaching, research, and technical experience allows me to contribute across teaching delivery, laboratory education, student supervision, curriculum support, and broader academic and technical functions.

Career

Experience

Research

Key Academic Publications

Academic

Service

External Reviewer

  • IEEE International Conference on Blockchain and Cryptocurrency (ICBC 2026)
  • IEEE International Conference on Trust, Privacy, and Security in Intelligent Systems and Applications (TPS 2025)
  • IEEE Transactions on Industrial Informatics
Academic Background

Education

2022 – Nov 2026 (Expected)

PhD Candidate - Computer Science

Queensland University of Technology

  • Thesis on Post-Quantum Security Establishment for Low-Power Internet of Things. Submitted and under examination.
2020 – 2022

Master of Information Technology (Computer Science)

Queensland University of Technology

  • International Merit Scholarship
  • Three times Faculty of Science Dean’s List (GPA 6.5+)
2016 – 2017

Master of Engineering

Queensland University of Technology

2012 – 2016

Bachelor of Engineering

The University of Queensland

Capabilities

Skills

Academic Delivery

Experienced university teaching staff, specialised in delivering hands-on activities. Also familiar with course coordination responsibilities.

Programming

Python, C/C++, Agent-assisted development and rapid prototyping

Embedded, IoT & Networking

Zephyr RTOS, nRF52/54 Series, Raspberry Pi, Arduino, Bluetooth/BLE, LoRaWAN

AI/ML

Embedded AI, TinyML, sensor-data processing and feature engineering

Languages

Mandarin Chinese (native), English (IELTS Academic 8.0, 2017)

Professional

References

References available upon request.