Research Interests

I have a broad range of theoretical and practical interests. On the theoretical side I am interested generally in computer vision and machine learning. More specifically I am interested in perception using novel types of sensors (asynchronous/neuromorphic vision, event cameras, multi-spectral sensing, raman spectrometers, etc), reinforcement learning and autonomous behaviours. I am also interested in machine learning "meta-problems" such as explainable AI, privacy and fairness in AI, security/resilience of AI systems and federated learning. I apply these theoretical interests in a range of application domains including perception and autonomy in robotics (navigation, planning, manipulation, obstacle avoidance), as well as various space-based applications (space-situational awareness, autonomous on-orbit assembly, GNC) and applications in the autonomous vehicles and creative industries.

Research Projects

My current and previous ongoing research projects are listed below. Click the project logos for more information.

	PhD studentships: various industrial partners, with topics ranging from next-generation sensing, to autonomous vehicles, nuclear decomissioning, explainable AI, robotics and deep-learning.
	FLEXBOT - Building a [Fl]exible, [Ex]tensible Co[bo]t Pla[t]form for Farmers
	Reflexive robotics using asynchronous perception
	Demonstrating an Innovative, Flexible and Intelligent Payload Chain for High Data Throughput on Small EO Satellites
	ROSSINI: Reconstructing 3D structure from single images: a perceptual reconstruction approach
	PeRsOnalized nutriTion for hEalthy livINg
	SMILE: Scalable Multimodal sign language Technology for sIgn language Learning and assessmEnt