My research is motivated by the scale and rapid development of the Internet of Things (IoT), which promises trillions of intelligent computing devices embedded pervasively into society and the built/natural environment. However, the effective powering of these systems - from tiny connected intelligent sensors to powerful edge computing devices - is far from solved. My research vision is for these devices and systems to be truly energy autonomous, intelligently managing and optimising use of their limited resources.
My research is rethinking the design of power-constrained embedded systems, where the available energy, its dynamics, and its consumption, are a primary design parameter. Much of my research in this area is concerned with managing IoT-like devices powered from energy harvested from the environment (e.g. solar), and more recently has focussed on 'intermittently' powered systems which are unintentionally off for much of the time.
Machine learning enables computers to learn from data they have previously observed, building models and using them to make decisions or predictions in the future. Embedding this into everyday objects - such as the Internet of Things (IoT) - requires processing data on electronic devices, but the computing power needed to cater for these machine learning models is too great for current low-energy handheld devices to manage. My research is addressing this, and enabling energy-efficient computation for intelligence.
Power- and energy-efficiency continues to be a primary concern in the design and management of computing systems, through from mobile devices (battery life and temperature) to HPC (electricity bills and temperature). Managing this is an increasingly complex task, as systems shift from having a single processing element to multi- and many-core computing platforms with numerous cores of differing types. My research is investigating runtime management (RTM) approaches to tackle this challenge.
I am a member of the Cyber Physical Systems Research Group; a group which cuts across the boundary between Electronic Engineering and Computer Science.
I am a member of the School's Strategic Research Centre for Internet of Things and Pervasive Systems, having previous been Head of Centre from 2018-24. The Centre has research activities in a full spectrum of topics cutting across the full IoT system stack, from underpinning semiconductor and sensor devices, through to machine intelligence and data science.
I was Co-Director of the Arm-ECS Research Centre from 2020-24, an award-winning industry-academia collaboration with Arm Research. The Centre received the "Research Group of the Year" award from the NMI in 2015, and was a runner-up for the TechWorks "Research Collaboration of the Year" award in 2018.