A series of projects on novel spintronic-based AI/ML devices working cross-discipline between Computer Science and Materials Science at the University of Sheffield. The drive behind this work has been developing physics-rich hardware for machine learning and the software to run on it. Particular highlights have been demonstrating a proof of principle neural network with a novel stochastic learning rule running on new hardware (magnetic binary stochastic synapses) and developing a new computational research thread for edge ML hardware, “Voltage-controlled superparamagnetic ensembles for low-power reservoir computing”.

Research Impact and Dissemination

• Published in top peer-reviewed journals and presented at 10+ national and international conferences.
• Championed the emerging field of spintronic neuromorphics via advocacy and networking.

Machine Learning & Research Software Engineering

• Co-developed proof-of-concept magnetic neural networks for energy-efficient AI systems.
• Designed Python frameworks for simulating magnetic thin films and low-power reservoir computing hardware.
• Created scalable control software for lab instrumentation and automated data collection, improving efficiency by 1000x.

Leadership & Collaboration

• Supervised PhD and master’s students, leading interdisciplinary projects.
• Key contributor to research software engineering, lab leadership and safety protocols.
• Advocated for software best practices, including Git integration and collaboration tools.

Outside of my normal work, I am a freelance wedding and events photographer. I provide clients with a guest-eye view of their wedding or event, allowing them to relive the day with candid photos that capture the heart of the event. I have succeeded if follow my two golden rules.

Golden Rules of Events Photography

• Don’t be the story : You are there to capture someone else’s day. Keep it theirs, don’t insert yourself into it.
• Capture their story : Tell the story, its key moments and its emotions with your images. Let your client live it again and again.

Strain-mediated voltage control of magnetic systems is an under-explored, but rich avenue of research with promise for ultra-low-energy next-generation computing devices. My PhD broke ground demonstrating the potential for strain control of advanced magnetic systems as a rewarding avenue of study.

I was based in Cowburn Group at the Cavendish Labs, University of Cambridge. My supervisor was Amalio Fernández-Pacheco a who now heads a world leading lab studying the “Physics of Three-dimensional Nanomaterials”.

Impact and Dissemination

• Thesis, “Strain control of advanced magnetic systems for spintronic applications”, published online with over 40 downloads.
• MOKE image analysis app published online. Over 70 downloads.

Innovation & Design

• Demonstrated strain-controlled spintronic devices for next-gen computing applications.
• Authored software for advanced image analysis with GUI for broader usability in the research community.

Mentorship & Outreach

• Supervised undergraduate and master’s students, fostering technical and theoretical skills.
• Delivered core supervisions for physics undergraduates, leading one student to achieve a top-15 ranking.