Machine Learning for Experimental Materials Data

KEY DETAILS

  • DATE

    2nd April 2026

  • TIME

    10:00 – 17:00

  • Registration fee

    £0 – IOP & Associate Member

  • £15 – Student Non-Member

  • £30 – Non-Member

  • Registration Deadline

    20th March 2026

EVENT LOCATION

  • institute of physics

    37 Caledonian Rd, London N1 9BU

Join our IOP–AIchemy co-sponsored mini-symposium on machine learning for experimental materials data. This event will unite experimentalists and computational scientists to identify shared challenges, exchange practical solutions, and showcase how ML accelerates analysis across scattering, microscopy, tomography, and spectroscopy; driving faster, more insightful materials discovery.

This event is open to everyone, whatever your background — whether you’re a practising physicist or simply curious to explore the subject.

Speakers:

  • Sam Cooper, Imperial College London
  • Kim Jelfs, Imperial College London
  • Andrew McClusky, University of Bristol
  • Dylan Owen, University of Birmingham
  • Rob Palgrave, University College London
  • Shijing Sun, University of Cambridge

Organised by:

  • Kelvin Wong, Post Graduate Teaching Assistant – University College London
  • Keith Butler, Associate Professor in Computational Materials Chemistry – University College London
  • Aron Walsh – Professor at Imperial College & CSO at CuspAI