Dr Matt Ellis

School of Computer Science

Senior Lecturer in Machine Learning

Director of UG Admissions

Admissions Tutor

Member of the Machine Learning research group

Matt Ellis headshot
Profile picture of Matt Ellis headshot
m.o.ellis@sheffield.ac.uk
+44 114 222 1949
Regent Court (CS)

Full contact details

Dr Matt Ellis
School of Computer Science
Regent Court (CS)
211 Portobello
Sheffield
S1 4DP
Profile

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 ±¬ÁÏTV 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.

Research interests

Dr Ellis is interested in developing energy efficient machine learning algorithms and systems based on neuromorphic computing. In particular, he is interested in developing models of physical systems that can be utilised as machine learning processing devices, such as devices for physical reservoir computing or neuromorphic hardware based on magnetic systems. Beyond machine learning he is interested in developing large scale models of magnetic devices including developing gpu accelerated models.

Publications

Show: Featured publications All publications

Journal articles

  • Evans RFL, Fan WJ, Chureemart P, Ostler TA, Ellis MOA & Chantrell RW (2014) . Journal of Physics: Condensed Matter, 26(10), 103202-103202.

All publications

Journal articles

  • Manneschi L, Ellis MOA & Donati E (2026) . 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) . Nature Communications, 16(1).
  • Strungaru M, Ellis MOA, Ruta S, Evans RFL, Chantrell RW & Chubykalo-Fesenko O (2024) . Physical Review B, 109(22).
  • 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) . Applied Physics Letters, 122(4).
  • 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) . Nanotechnology, 33(48).
  • Ababei RV, Ellis MOA, Vidamour IT, Devadasan DS, Allwood DA, Vasilaki E & Hayward TJ (2021) . Scientific Reports, 11(1).
  • Welbourne A, Levy ALR, Ellis MOA, Chen H, Thompson MJ, Vasilaki E, Allwood DA & Hayward TJ (2021) . Applied Physics Letters, 118(20).
  • Dawidek RW, Hayward TJ, Vidamour IT, Broomhall TJ, Venkat G, Mamoori MA, Mullen A, Kyle SJ, Fry PW, Steinke N , Cooper JFK et al (2021) . Advanced Functional Materials, 31(15).
  • Strungaru M, Ellis MOA, Ruta S, Chubykalo-Fesenko O, Evans RFL & Chantrell RW (2021) . Physical Review B, 103(2).
  • Manneschi L, Ellis MOA, Gigante G, Lin AC, Giudice PD & Vasilaki E (2020) Exploiting Multiple Timescales in Hierarchical Echo State Networks.. Frontiers Appl. Math. Stat., 6, 616658-616658.
  • Ellis MOA, Galante M & Sanvito S (2019) . Physical Review B, 100(21).
  • Galante M, Ellis MOA & Sanvito S (2019) . Physical Review B, 99(1).
  • Ababei R-V, Ellis MOA, Evans RFL & Chantrell RW (2019) . Physical Review B, 99(2).
  • Ellis MOA, Stamenova M & Sanvito S (2017) . Physical Review B, 96(22).
  • Ellis MOA, Ababei R-V, Wood R, Evans RFL & Chantrell RW (2017) . Applied Physics Letters, 111(8).
  • Ellis MOA, Fullerton EE & Chantrell RW (2016) . Scientific Reports, 6.
  • Ellis MOA, Evans RFL, Ostler TA, Barker J, Atxitia U, Chubykalo-Fesenko O & Chantrell RW (2015) . Low Temperature Physics, 41(9), 705-712.
  • Ellis MOA, Evans RFL, Ostler TA, Barker J, Atxitia U, Chubykalo-Fesenko O & Chantrell RW (2015) The Landau-Lifshitz equation in atomistic models. Fizika Nizkikh Temperatur, 41(9), 908-916.
  • Ellis MOA & Chantrell RW (2015) . Applied Physics Letters, 106(16).
  • Evans RFL, Fan WJ, Chureemart P, Ostler TA, Ellis MOA & Chantrell RW (2014) . Journal of Physics: Condensed Matter, 26(10), 103202-103202.
  • Manneschi L & Ellis MOA () . Nature Computational Science.
  • Vidamour IT, Ellis MOA, Griffin D, Venkat G, Swindells C, Dawidek RWS, Broomhall TJ, Steinke N-J, Cooper JFK, Maccherozzi F , Dhesi SS et al () Quantifying the computational capability of a nanomagnetic reservoir computing platform with emergent magnetization dynamics.
  • Ostler TA, Ellis MOA, Hinzke D & Nowak U () . Physical Review B, 90(9).
  • Ellis MOA, Ostler TA & Chantrell RW () . Physical Review B, 86(17).

Conference proceedings

  • Hayward TJ, Vidamour IT, Ellis MO, Welbourne A, Dawidek RW, Broomhall TJ, Chambard M, Drouhin M, Keogh AM, Mullen A , Kyle SJ et al (2021) . Spintronics XIV (pp 59-59), 1 August 2021 - 5 August 2021.

Preprints

  • Vidamour I, Manneschi L, Stenning K, Swindells C, Venkat G, Hariga D, Griffin D, Stepney S, Branford W, Gartside J , Hayward T et al (2024) , Springer Science and Business Media LLC.
  • Manneschi L, Vidamour IT, Stenning KD, Swindells C, Venkat G, Griffin D, Gui L, Sonawala D, Donskikh D, Hariga D , Stepney S et al (2024) , arXiv.
  • Ellis MOA, Welbourne A, Kyle SJ, Fry PW, Allwood DA, Hayward TJ & Vasilaki E (2023) , arXiv.
  • Allwood DA, Ellis MOA, Griffin D, Hayward TJ, Manneschi L, Musameh MFK, O'Keefe S, Stepney S, Swindells C, Trefzer MA , Vasilaki E et al (2022) , arXiv.
  • Ababei RV, Ellis MOA, Vidamour IT, Devadasan DS, Allwood DA, Vasilaki E & Hayward TJ (2021) , Research Square Platform LLC.
  • Manneschi L, Ellis MOA, Gigante G, Lin AC, Del Giudice P & Vasilaki E (2021) , arXiv.
Grants
  • Spintronic Reservoir Fusion: connecting heterogeneous magneticnano-devices for energy-efficient computing, EPSRC, 01/2025 - 12/2027, £563,599, as PI
  • MARCH: , EPSRC, 02/2021 - 07/2025, £936,815, as Co-PI
  • From Stochasticity to Functionality: , EPSRC, 04/2019 - 11/2023, £755,424, as Co-PI

Links

Machine Learning research group