The Cogan award recognizes “researchers aged 45 or younger who have made important research contributions in ophthalmology and visual science that are directly related to the disorders of the visual system and who show substantial promise for future contributions.” The 2026 joint Cogan awardees, Drs. Aaron Y. Lee and Cecilia S. Lee who are both innovative physician scientists, have indeed made major contributions by leading the application of artificial intelligence (AI) to ophthalmology research and clinical care and they show great potential for future contributions. They are partners in life as well as in research. The closest example of such life partners includes the combined forces of Drs. Barbara and Ron Klein who received the Friedenwald Award well into the very productive careers as epidemiologists in 2005 from Association of Research in Vision and Ophthalmology (ARVO).
Dr. Aaron Lee is the newly appointed chair of the Department of Ophthalmology at the John Hardesty, MD, Department of Ophthalmology and Visual Sciences at Washington University of School of Medicine in St. Louis, Missouri, where he is the Arthur W. Stickle Distinguished Professor. Dr. Cecilia Lee is the Jane Hardesty Poole Distinguished Professor, in the Department of Ophthalmology and Visual Science at Washington University. Dr. Cecilia Lee earned her undergraduate (Summa Cum Laude) and medical degrees at Emory University where she also received her residency training in ophthalmology. Dr. Aaron Lee earned his undergraduate degree at Harvard (Magna Cum Laude) and both his medical degree and Master of Science in Clinical Investigations simultaneously from the Washington University (St. Louis, MO, USA) where he also received his ophthalmology residency training. They both attended the Moorfields Eye Hospital for medical retina fellowship training. Dr. Cecilia Lee also received uveitis fellowship training from Washington University and Dr. Aaron Lee received surgical retina training from the University of British Columbia (UBC, Vancouver, Canada).
Drs. Aaron and Cecilia Lee focused on the translation of machine learning concepts into ophthalmology research, clinical research, and clinical care. They recognize the need to harmonize large clinical, electronic health record datasets in combination with genetic and ophthalmic imaging. Their laboratory was the very first to leverage these large datasets to apply deep learning models in multi-modal images, including the optical coherence tomography (OCT). Dr. Aaron Lee has led a team of pioneering machine learning scientists to apply deep learning techniques to ophthalmic imaging. This work has led to many innovations, using deep learning to assess the severity of age-related macular degeneration (AMD), a common cause of blindness, and he helped to develop a novel continuous grading system based on retinal images for staging a rarer neurodegenerative disease, macular telangiectasia type 2, that causes a gradual visual impairment. Dr. Aaron Lee has created foundational AI models that can be trained for various types of retinal imaging without a great deal of training or the need for additional data. He has identified genetic factors influencing the formation of macula using advanced data-driven methods. These accomplishments have also included the collaboration of Dr. Cecilia Lee. Altogether, these advances have greatly improved imaging techniques used to detect macular degeneration and rare retinal diseases. He has collaborated with the US Food and Drug Administration to develop polices for regulating machine learning devices, and created report guidelines for AI studies, while running the first multicenter study of autonomous AI devices for screening for diabetic eye disease.
Dr. Cecilia Lee is a clinician-scientist whose research intersects with retinal imaging, clinical epidemiology, and big data, to evaluate the eye as a potential retinal biomarker for evaluating systemic and neurodegenerative diseases. Her National Institutes of Health (NIH) grant supports her unique ancillary study of the Adult Changes in Thought (ACT), which evaluates the investigation of the relationship between aging eyes and the aging brains in a well-characterized longitudinal cohort. This is a large complex study investigating retinal biomarkers of Alzheimer's disease using both prospective and retrospective data which include retinal and neuroimaging, clinical and electronic health record data, and generating a multimodal dataset for machine learning analysis. No other study has the unique combination on extensive clinical eye disease and decades of visual impairment history data, state-of-the art neuropathology data from over 1000 autopsy cases, and prospective longitudinal retinal imaging data obtained from a well-characterized, community-based, longitudinal cohort of older adults. Both AMD and Alzheimer's disease are growing exponentially in the numbers of people affected with these conditions globally. The public health impact of these investigations is enormous.
Together, Drs. Cecilia and Aaron Lee have received a prestigious award from the NIH Common Funds, a large NIH project which is funded at $31.5 M with $7 M for the initial year. They are principal investigators of the Bridge2AI project (OT2OD32644) which is entitled AI-READi/Salutogenesis, the Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) Project. The primary aim of this project is to create and share an ethically sourced dataset of type 2 diabetes from several clinical sites, and the data will be optimized for future AI and machine learning analysis that could provide critical insights on the salutogenic pathways from diabetes, diseased state to return to health. The team of investigators have collected a cross-sectional dataset of 4000+ people across the United States. The long-term objective for this project is to develop a foundational dataset in diabetes, agnostic to existing classification criteria or biases, which can be used to reconstruct a temporal atlas of type 2 diabetes development and reversal towards health (i.e. salutogenesis). This demonstrates the power of their intellectual input into an enormous public health problem. The partnership of Drs. Cecilia and Aaron Lee has also extended to numerous investigators who are involved with the large project, demonstrating their highly collaborative nature. This is truly team science at its best. They have already created data downloaded by other researchers.
This duo has been recognized by many of our professional societies for their enormous contributions. Their most important collaboration is their home-grown project, the raising of their 8-year-old daughter, Ibby Lee, who is destined toward an interesting and productive life given her DNA and her nurturing environment. Both Drs. Aaron and Cecilia Lee have proven to be outstanding mentors who have provided their young trainees with fulfilling and exciting research opportunities which include first authored publications and training in the use of AI which will become an important and necessary skill for future ophthalmic researchers and clinicians alike. They are role models for providing outstanding clinical care. Dr. Cecilia Lee, having spent some of her formative years in Buenos Aires, is fluent in Spanish in addition to her competency in Korean and this versatile language fluency provides great comfort to her patients.
This recognition of the Cogan Award is well deserved by these two kind, humble, generous, hard-working, and immensely talented individuals, Drs. Aaron and Cecilia Lee. We are confident that their continued contributions to this area of research may likely transform our research and our clinical care process. We will no doubt continue to applaud them in the future for the positive impact to our field. Congratulations!!
Acknowledgments
Supported in part by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author were made as part of her official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the author and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.