Ophthalmic AI Research Lab
EyeMap.ai applies deep learning to retinal imaging for early detection of AMD, diabetic retinopathy, glaucoma, and systemic conditions, turning a routine eye scan into a whole-body health screen.
Navigation
This site is organised in layers — from high-level institute information to project-specific technical content and participant-facing documentation.
Research Lab overview, principal investigators, methodology, and our UK Biobank application context.
Technical pages for each diagnostic model: AMD, Diabetic Retinopathy, and Glaucoma CDR estimation.
Research on vision-assistive devices, including FingerReader 2.0 — a wearable reading aid for visually impaired individuals.
Information sheets, consent documentation, data rights, and contacts for individuals taking part in our studies.
Commercial vision, market opportunity, business model, and fundraising details for prospective investors.
Research
Our computational ophthalmology work spans diagnostic AI, longitudinal biomarker tracking, and assistive device development.
The retina offers a unique, non-invasive window into the systemic vasculature. Our models analyse fundus photographs to detect early signs of AMD, diabetic retinopathy, and glaucomatous changes — and to infer downstream risk for stroke and cardiovascular events.
View AI model documentation →We are applying to access UK Biobank retinal imaging data to validate our diagnostic models across a large, diverse population. This collaboration will enable longitudinal analysis of retinal change and its relationship with incident disease.
Research overview →Parallel to diagnostic AI, we conduct research into devices that restore functional capability to individuals with visual impairment, including the peer-reviewed FingerReader 2.0 wearable reading system published in ACM IMWUT.
FingerReader 2.0 research page →People
EyeMap.ai is led by researchers with backgrounds spanning AI for healthcare, clinical wearables, computer vision, and enterprise scaling.
Recognition
December 2025. EyeMap.ai was awarded third place at the HealthON Hackathon, judged by the Romanian Health Minister Alexandru Rogobete, who tested the system live during the presentation.
EyeMap.ai presented on 24th April 2026 at the Ophthalmology Session of the National Conference on Technology & iHealth in Medicine. Talk title: EyeMap.ai — Scalable Retinal Screening for Early Detection of Ophthalmic Pathologies.