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.
Example topics
Brain-inspired positioning for fast, energy-efficient, resilient robotics
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.
Work Package 1: Neuromorphic foundations for energy- and latency-optimised localisation. Most event-based systems still rely on conventional, frame-based algorithms, limiting their true potential for speed and efficiency. This work package establishes the foundations for asynchronous neuromorphic positioning, combining sparse spectral processing, predictive sensing and hardware acceleration to achieve sub-millisecond updates with millijoule-level energy use.
Work Package 2: Resilient and sustainable deployments of neuromorphic localisation. This work package translates neuromorphic positioning into resilient deployments for long-duration, collaborative operation in energy-, bandwidth- and environment-constrained settings where conventional systems fail, so that robots remain resilient and cooperative even when communication or power is limited.
Work Package 3: Global platforms and community adoption. This work package embeds the advances in the open-source ecosystem that drives the field forward, expanding RoboStack and VSLAM-LAB with neuromorphic algorithms, adaptive controllers and datasets, and testing them in marine and industrial demonstrators.
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.
Adaptive and efficient robot positioning
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 QUTScene understanding for underwater imagery
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 QUTWho I'm looking for
- A bachelor's or master's degree in robotics, computer vision, computer science, mathematics, mechatronics or a related area (marine or environmental science for the underwater topic).
- A strong background in, or interest in, machine learning, deep learning, computer vision or robotics.
- Proficiency in programming languages such as Python, C++, MATLAB or similar.
- Very good analytical and problem-solving skills.
- Strong written and verbal communication skills.
Both international and domestic applicants are welcome. Scholarships, eligibility and application rounds are described on QUT's research scholarships and how to apply pages.
Diversity
I highly encourage applications from underrepresented groups, including women in STEM and First Nations peoples. The QUT Centre for Robotics makes safety, inclusivity and support a priority so that staff and students have the best possible chance to succeed. Many Centre members, including myself, are part of the QUT Ally network and are trained to understand sexuality and gender issues. I am also a co-chair of the IEEE RAS Women in Engineering Committee.
Interested?
Please complete the expression-of-interest form rather than emailing me your CV. It asks for your background, your CV and, optionally, your transcripts; because of the file uploads, Google asks you to sign in with a Google account.