Overview
I am a member of the Matter Community in the Physics Department and the London Centre for Nanotechnology. My present work focuses on new paradigms of computing, that can improve energy efficiency. The energy cost of computing is ballooning. More than 20% of global energy production will be used in ICT by 2030. More energy-efficient computation is essential to meeting net zero commitments.

• Physical machine learning –hardware inspired by the brain and/or optimised architectures for machine learning algorithms. The two key differences with conventional computers are that the computation is massively parallel, and that it happens in the memory, rather than having logic and memory done by separate devices.
• Magnetic writing, readout and data storage technologies –filed patents for next-generation nanomagnetic writing and readout technologies, and is benchmarking their capabilities for use in both conventional data storage, and in-memory computing applications.
• Magnonics – the cause of the colossal energy cost of modern computing is Joule heating.. Magnonics replaces electrical charges in computing with GHz spin waves, allowing. information transmission without any transport of particles.

The work employs Artificial Spin Ice, a metamaterial embodying complexity physics and frustration. Nanofabrication of magnetic arrays creates frustrated geometries where the interactions cannot be simultaneously satisfied. Frustration is critical to how we reach decisions in the brain and how social and financial networks evolve.

I have a strong interest in the fundamental physics that governs the magnetism and transport in materials and nanostructures. In particular I am interested in magnetization dynamics and magneto-optical coupling phenomena.

If you are interested in a genaral overview of my research, you can watch my Inaugural Lecture, which is in the media links on my homepage. The title is 'How physics made AI possible, and how it can make it more efficient'. Inaugural lectures are public lectures which showcase the research of newly promoted professors.