Matthew Ellis

Dr. Matthew Ellis is a Lecturer in Machine Learning and Director of Undergraduate Admissions at the University of Sheffield's School of Computer Science, Department of Computer Science. He holds a MPhys in Theoretical Physics (2011) and a PhD in Physics (2015) from the University of York. His research focuses on energy-efficient machine learning algorithms and neuromorphic systems, particularly leveraging magnetic devices such as nanomagnetic reservoirs and stochastic synapses. He leads the Machine Learning Group and collaborates with Materials Science departments on neuromorphic hardware development.

His postdoctoral work included roles at Trinity College Dublin (2015–2019) and the University of Sheffield (2019–present). Key research areas include neuromorphic computing, spintronics, and computational magnetism. Ellis has secured grants totaling £2.25M from EPSRC, including leading projects like Spintronic Reservoir Fusion (2025–2027) and MARCH (2021–2025).

Publications span journals like Neuromorph. Comput. Eng., Applied Physics Letters, and Physical Review B, with a focus on magnetic systems' computational applications. His work emphasizes device-agnostic models, hierarchical networks, and low-power reservoir computing architectures.