ProfessorDaniel Quevedo

Project Opportunities

Title: Control and Communications for Human-Machine Collaboration

Summary of opportunity:

This project examines fundamental theories and technologies crucial for advancing wireless Human-Machine Collaboration within the context of Industry 5.0, an emerging industrial transformation. The project will lay the groundwork for co-designing wireless communications and cyber-human collaborative controls to optimise operational efficiency and prioritise human well-being.

Research Area:

Wireless Communications; Control Systems; Cyberphysical and Human Systems; Machine Learning

Supervisors:

• Professor Yonghui Li
• Professor Daniel Quevedo
• Dr Wanchun Liu

Opportunity synopsis:

Industry 4.0 is rapidly transforming the global manufacturing landscape, accelerating the demand for intelligent and collaborative control systems in industrial environments. While control automation in Industry 4.0 is designed for fast and repetitive tasks without human intervention, it lacks the creativity and cognitive capability of humans. Emerging Industry 5.0 will strongly emphasise harmonious collaboration between humans and intelligent machines, delivering significant benefits for both humanity and the environment. Achieving this vision requires robust communication networks and control algorithms.

These will facilitate seamless interaction between humans and various automated systems, including vehicles, robots, and cloud resources.  
Wireless Human-Machine Collaboration (wHMC) emerges as a cornerstone of Industry 5.0, promising to redefine factory operations with seamless, adaptive, and scalable human-machine interactions.

To unlock its full potential, a wHMC system must integrate both automatic as well as human control loops. The design of wHMC systems requires new system models, tractable stability and performance analysis methods, and high-performance collaborative control architectures.  
This project aims to develop fundamental sciences for wHMC at the intersection of systems control, telecommunications, machine learning and control-oriented modelling of human behaviour. Beyond fundamental underpinnings, proof-of-concept experiments for wHMC will be developed to promote understanding and demonstrate its potential to tackle intricate manufacturing challenges.

Offering:
The successful candidate will be awarded a scholarship for 3.5 years at the RTP stipend rate (currently $41,753 in 2025) subject to satisfactory academic performance. International applicants will receive a tuition fee scholarship for upto 3.5 years.

Successful candidates:

• Must have a Honours degree (First Class or First Class Honours Equivalent) or a Master's degree with a substantial research component in Engineering or Mathematics
  Must have a strong background in control theory or telecommunications

How to apply:
To apply, please email daniel.quevedo@sydney.edu.au and cc yonghui.li@sydney.edu.au and wanchun.liu@sydney.edu.au with the subject line "PhD Application" and your name. Please include the following:

• CV,
• Transcript, and
• A brief cover letter