John Collomosse

Background

About John Collomosse

Professor John Collomosse is a Sr. Principal Scientist and Distinguished Inventor at Adobe Research. He leads research for Adobe’s Content Authenticity Initiative (CAI) and is a core technical advisor to the initiative since his involvement in its inception in 2019. Now with 4K+ members, CAI leads a cross-industry standards group (C2PA; Coalition for Content Provenance and Authenticity) where John chairs the cross-industry task forces on watermarking, and distributed ledgers (Blockchain) and previously also chaired a task force on fingerprinting. He is elected a Fellow of the IET (FIET), Fellow of the British Computer Society (FBCS) and a Fellow of the Royal Society of Arts (FRSA). Since 2008 he is a Chartered Engineer (CEng). John’s research intersects Artificial Intelligence (AI) and Distributed Ledger Technology (DLT), with focus on media provenance to fight misinformation and online harms, and on improving data integrity and attribution for responsible AI. John’s content fingerprinting research is used to protect millions of images daily across Adobe’s platforms such as Photoshop, Lightroom and generative AI Firefly tools. John has also pioneered several visual search technologies, such as style, sketch and pose based search. These technologies have been demoed at Adobe MAX several times and shipped in products such as Behance.net. John has presented to various government bodies on provenance, authenticity and AI opt out including the European Commision, UK House of Lords and APPG Blockchain. Whilst leading the cross-modal representation learning (XRL) research group at Adobe, John is concurrently a full professor at the University of Surrey where he is the founder and director of DECaDE, the UKRI Research Centre for the Decentralized Digital Economy. Notably, he led the ARCHANGEL project which pioneered use of AI and Blockchain to tamper-proof National Archives around the world and was called out as a highlight of the 10 year UK Science Council (EPSRC) Digital Economy research programme. John’s early/PhD research (early developed some of the earliest computer vision based technologies to create the kind of non-photorealistic (artistic) filtering effects now commonly found in products like Photoshop, and was featured in the BBC, New Scientist among others. John has also spent previous periods of time in industry R&D elsewhere, including at Vodafone Munich and IBM Research Hursley. From 2018-2024 he was on the UKRI/EPSRC advisory team for Information & Communication Technologies (ICT).