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
- Sarah Haigh, University of Manchester
- Shelley Conroy, Imperial College London
Poster Abstracts
We invite contributions for poster presentations. If you are interested in presenting a poster, please submit a short abstract (max 250 words) by email to claire.garland@iop.org by 20 March 2026. Posters will be A0 in portrait orientation.
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
