PhD Positions

I am always looking for motivated PhD students to join my group at the QUT Centre for Robotics. The topics below are examples of current and upcoming projects; you are also welcome to propose your own topic in my research areas. If you are interested, please complete the expression-of-interest form rather than emailing me your CV.

Expression-of-interest form

Example Topics

Adaptive and efficient robot positioning

Co-supervised with Prof Michael Milford, Prof Niko Sünderhauf, Dr Dimity Miller

Visual place recognition and robot localisation that adapts to changing environments and runs efficiently on edge devices, including neuromorphic place recognition with event cameras and spiking neural networks. Part of my ARC DECRA Fellowship, with top-up scholarships available.

Full description at QUT

Scene understanding for underwater imagery

Co-supervised with Dr Scarlett Raine

AI for monitoring and restoring coral reefs: interpreting continuous ecological indicators such as coral health, re-identifying coral reseeding devices, and recognising previously unseen marine species.

Full description at QUT

Brain-inspired, fast and energy-efficient robot positioning

ARC Future Fellowship · starting November 2027

I am looking for highly motivated PhD students to join my ARC Future Fellowship project on brain-inspired robot positioning. Robots need to know where they are to move safely, yet today’s localisation systems are slow and power-hungry, and they fail when satellite positioning or communication links are unavailable: underwater, underground, or in space. This project will develop neuromorphic positioning systems that update a robot’s position in under a millisecond using very little energy.

Research Program 1: Neuromorphic foundations for fast localisation. Event cameras report only what changes in a scene, but most current methods turn their output back into conventional images, losing much of their speed and efficiency. This program will develop new representations of event data that stay robust to changes in lighting, appearance and viewpoint; sensing strategies that activate only the most informative parts of the sensor; and event-based geometric methods for accurate, drift-free navigation.

Research Program 2: Hardware-accelerated, energy-aware localisation. This program will bring these algorithms onto dedicated low-power hardware, such as neuromorphic processors and FPGAs, to achieve end-to-end localisation in under a millisecond, and develop controllers that continuously balance speed, accuracy and power, switching to high-precision localisation only when the robot’s confidence drops.

Research Program 3: Resilient, cooperative localisation. This program will develop hierarchical systems that pair a fast, low-power layer with a slower, high-confidence one; compact map representations that let teams of robots share information over very limited communication links; and new benchmarks that measure mission success, not only accuracy.

Research Program 4: Real-world deployment and open platforms. This program will take the methods into challenging real environments such as coral reefs and underground sites, through staged trials from controlled settings to multi-day field missions, and release open-source software and benchmark datasets for the wider community.

PhD scholarships are available for students working on the Fellowship’s research program, with opportunities to work with industry and government partners and with state-of-the-art neuromorphic sensors and processors.