Featured academics
The researchers behind the standing
Independently verified: current affiliation, public profile and published contact confirmed from the open record.
Matija StrlicSubject Award Winner 2026
Honorary Professor of Heritage Science at UCL's Institute for Sustainable Heritage, Matija Strlic co-led a cross-disciplinary archaeological, chemical and sensory analysis of the smell of ancient Egyptian mummified bodies, with partners in Ljubljana, Cairo and Krakow, demonstrating the key role of olfactory information in the understanding and conservation of heritage collections as well as their communication through olfactory exhibitions.
Mark EmbertonSubject Award Winner 2026
Professor Emberton pioneered precision diagnosis and focal therapy for prostate cancer and serves as Dean of UCL's Faculty of Medical Sciences. He co-authored a multi-institution Science review on the early detection of cancer, setting out how earlier diagnosis across tumour types could transform outcomes and guide future research priorities.
Gianluca BaioSubject Award Winner 2026
Professor of Statistics and Health Economics and Head of Statistical Science at UCL, Gianluca Baio develops Bayesian methods for health evaluation. In a five country collaboration with Imperial College and European partners he modelled regional excess mortality during the 2020 COVID-19 pandemic, quantifying the true toll of the outbreak beyond reported deaths.
Susan Michie
Susan Michie, Professor of Health Psychology and Director of the Centre for Behaviour Change at UCL, co-developed the Behaviour Change Intervention Ontology with collaborators across several universities, creating a shared framework for representing interventions and their evaluation that enables machine-assisted evidence synthesis and more precise decision making in behavioural science.
Danail Stoyanov
Professor Stoyanov develops surgical robotics and artificial intelligence for minimally invasive interventions and co-directs the UCL Hawkes Institute. He co-authored a landmark multi-institution Medical Image Analysis paper mapping how surgical data science can move from concepts toward clinical translation, setting priorities for data driven improvement of interventional healthcare.