The NLM Colloquia on Biomedical Data Science and Computational Biology Research is a regularly scheduled series of scientific lectures presented by the NLM Division of Intramural Research (DIR), a premier hub of innovation for computational biology and biomedical data science.
The NLM DIR invites experts from outside NLM to present at the Colloquia, where they can share their insights with research communities across NIH and worldwide in the rapidly evolving fields of biomedical data science and computational biology research, as well as how their work impacts these topic areas.
2026 NLM Colloquia Series
Diverse Applications of Computational Research and Artificial Intelligence in Ophthalmology
Event Date: Thursday, February 12, 2026
Time: 11:00am–12:00pm
Speaker: Tiarnán Keenan, MD, PhD
Location: The Lister Hill Center Auditorium (LHC, building 38A), and virtual via NIH Videocast
Abstract:
Ophthalmology is ideally positioned to benefit from recent advances in computational data science and artificial intelligence. As a highly image-based specialty, it offers non-invasive, high-resolution views of the microvascular circulation and the central nervous system, creating rich opportunities for computational analysis with direct clinical relevance. This seminar will present diverse applications of advanced biostatistics, computational research, and machine learning techniques in ophthalmology, with a focus on age-related macular degeneration, the leading cause of blindness in industrialized countries, and cataract, the leading cause of blindness worldwide. Topics will include automated disease detection, quantitative severity classification, and prognostic prediction of disease progression from retinal imaging data, with and without the integration of genetic information. Methodological themes will span deep feature extraction, label transfer, and multi-modal, multi-task learning frameworks.
Speaker Bio:
Tiarnán Keenan, MD, PhD, is a Stadtman Tenure-Track Investigator in retinal disease within the Division of Epidemiology and Clinical Applications at the National Eye Institute, National Institutes of Health. As a clinician-scientist, he combines clinical practice as a retina specialist with research into retinal disease, particularly age-related macular degeneration, the leading cause of legal blindness in all industrialized countries. His research is focused on the application of computational, advanced statistical, and deep learning approaches to understanding, diagnosing, and treating retinal disease, often using multimodal retinal imaging. He received his undergraduate and medical degrees as a scholar at the University of Oxford and completed integrated academic-clinical training in ophthalmology and biomedical research predominantly at the Manchester Royal Eye Hospital and the Oxford Eye Hospital, followed by post-graduate research as a Fulbright Scholar in the United States. With over 150 publications in peer-reviewed journals, he has expertise across multiple scientific disciplines, ranging from basic science and multi-omics approaches to clinical research, epidemiology/big data, nutritional research, and interventional clinical trials. Through collaborations with investigators at the National Library of Medicine, he has experience in large deep learning projects related to retinal images and multidimensional datasets. He has briefed the United States Congress on applications of AI for retinal disease.
How to Join:
Location: The Lister Hill Center Auditorium (LHC, Building 38A)
This talk will also be broadcast live: NIH Videocast
Interpreting services are available upon request. Individuals with disabilities who need reasonable accommodation to participate in this lecture should contact NLMColloquia@nih.gov or the Federal Relay (1-800-877-8339).
Questions during the presentation can be sent to: NLMColloquia@nih.gov.
Sponsored by:
Richard Scheuermann, PhD
Scientific Director, Division of Intramural Research, National Library of Medicine