ProfessorSam Cooper
Professor of Artificial Intelligence for Materials Design
Dyson School of Design Engineering - Faculty of Engineering
Orcid identifier0000-0003-4055-6903 (opens in a new tab)
- Professor of Artificial Intelligence for Materials DesignDyson School of Design Engineering - Faculty of Engineering
- Dyson Building, South Kensington Campus, United Kingdom
GRANTS
- GRANTBuilding AI capability and datasets for science and engineeringHenry Royce Institute1 Nov 2026 - 30 Apr 2027
- GRANTBAT-META: An Open Metadata Framework for AI-Ready Battery ResearchThe Faraday Institution1 Oct 2026 - 31 Mar 2027
- GRANTFULL-MAP: FULLy integrated, autonomous & chemistry agnostic Materials Acceleration Platform for sustainable batteriesEuropean Commission1 Feb 2025 - 31 Jan 2029
- KNOWLEDGE TRSF/EXCHPA5835: Cochlear implants and spatial hearing: Enabling access to the next dimension of hearingEU Underwrite - EPSRC1 Mar 2024 - 29 Feb 2028
- GRANTAn automated high throughput robotic platform for accelerated battery discovery (DIGIBAT)Engineering & Physical Science Research Council (E1 Jan 2023 - 31 Jul 2026
- GRANTMultiscale Modelling ExtensionThe Faraday Institution1 Apr 2021 - 31 Mar 2023
- GRANTFITG Imperial 19-B - Microstructural fingerprint: The application of machine learning methods for the characterisation and optimisation of electrode microstructures.Engineering & Physical Science Research Council (E1 Oct 2019 - 30 Sep 2023
- GRANTInnovate MAT2BAT - A holistic battery system design tool: From materials to packsInnovate UK1 Dec 2018 - 30 Nov 2019
- GRANTHyStERIAA - Hydrogen Storage to Energise Robotics In Air ApplicationsInnovate UK1 Jul 2018 - 31 Mar 2019
- GRANTFaraday Challenge: Multiscale modellingEngineering and Physical Sciences Research Council28 Mar 2018 - 28 Mar 2021
- GRANTABLE - Advanced Battery Lifetime ExtensionInnovate UK1 Mar 2018 - 28 Feb 2019
- GRANTIMPACT - IMproved Power bAttery Cooling TechnologyInnovate UK1 Mar 2018 - 28 Feb 2019
- FELLOWSHIPAIMS-deep: Transforming Materials Science with AI-Enhanced Workflows for Accelerated Innovation and Deep ReproducibilityEngineering and Physical Sciences Research Council