Dr Matt Ellis

About

Dr Matthew Ellis is a Lecturer in Machine Learning and member of the Machine Learning Group at the Department of Computer Science.He graduated with a MPhys in Theoretical Physics from the University of York in 2011, before staying at York to undertake a PhD in Physics under Prof. Roy Chantrell.After completing his PhD in 2015 he joined the group of Prof. Stefano Sanvito at Trinity College Dublin as a post-doctoral research fellow. In 2019, he joined the University of Sheffield as a post-doctoral research associate in the Bio-Inpsired Machine Learning group under Prof. Eleni Vasilaki developing machine learning models for neuromorphic computing in collaboration with the Department of Materials Science.

Selected publications

• Evans RFL, Fan WJ, Chureemart P, Ostler TA, Ellis MOA & Chantrell RW (2014) Atomistic spin model simulations of magnetic nanomaterials. Journal of Physics: Condensed Matter, 26(10), 103202-103202.
• Ellis MOA & Manneschi L (2026) Can stochastic hardware mitigate the energy demands of AI?. Newton, 2(8), 100599-100599.
• Manneschi L, Ellis MOA & Donati E (2026) Beyond Subject-Specific Models in Dynamical Human–Machine Interaction: Benchmarking and Optimization Strategies. IEEE Transactions on Neural Networks and Learning Systems, PP(99), 1-14.
• Manneschi L, Vidamour IT, Stenning KD, Swindells C, Venkat G, Griffin D, Gui L, Sonawala D, Donskikh D, Hariga D , Donati E et al (2025) Noise-aware training of neuromorphic dynamic device networks. Nature Communications, 16(1). View this article in WRRO
• Strungaru M, Ellis MOA, Ruta S, Evans RFL, Chantrell RW & Chubykalo-Fesenko O (2024) Route to minimally dissipative switching in magnets via terahertz phonon pumping. Physical Review B, 109(22). View this article in WRRO
• Ellis MOA, Welbourne A, Kyle SJ, Fry PW, Allwood DA, Hayward TJ & Vasilaki E (2023) Machine learning using magnetic stochastic synapses.. Neuromorph. Comput. Eng., 3, 21001-21001.
• Allwood DA, Ellis MOA, Griffin D, Hayward TJ, Manneschi L, Musameh MFKH, O'Keefe S, Stepney S, Swindells C, Trefzer MA , Vasilaki E et al (2023) A perspective on physical reservoir computing with nanomagnetic devices. Applied Physics Letters, 122(4). View this article in WRRO
• Vidamour I, Ellis MOA, Griffin D, Venkat G, Swindells C, Dawidek RWS, Broomhall TJ, Steinke N-J, Cooper J, Maccherozzi F , Dhesi S et al (2022) Quantifying the computational capability of a nanomagnetic reservoir computing platform with emergent magnetisation dynamics. Nanotechnology, 33(48). View this article in WRRO
• Ababei RV, Ellis MOA, Vidamour IT, Devadasan DS, Allwood DA, Vasilaki E & Hayward TJ (2021) Neuromorphic computation with a single magnetic domain wall. Scientific Reports, 11(1). View this article in WRRO
• Welbourne A, Levy ALR, Ellis MOA, Chen H, Thompson MJ, Vasilaki E, Allwood DA & Hayward TJ (2021) Voltage-controlled superparamagnetic ensembles for low-power reservoir computing. Applied Physics Letters, 118(20). View this article in WRRO