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Harvard Ophthalmology AI Lab
Welcome to Harvard Ophthalmology AI Lab. We aim to transform eye diseases diagnosis and prognosis with the power of artificial intelligence through our passionate research.

Equitable AI for disease screening
Our team is dedicated to developing equitable AI models for disease screening with a special focus on ocular diseases. Recently, we have developed a fair identity normalization technique to improve model performance equity.
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AI for medical data cleaning
Our team is dedicated to developing AI-based data cleaning technologies, aiming to provide cleaner data and enhance diagnostic outcomes for eye diseases.
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AI for identifying imaging endophenotypes for GWAS
Our team proposes to uncover the hidden structural patterns of OCT-derived retina layers with two AI models. These patterns are useful for further genetic-wide analysis studies (GWAS).
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Interpretable AI for pathophysiology discovery
Our team aims to design a deep learning model to quantify the retinal layer importance and regional importance of each retinal layer in predicting various ocular and systematic diseases.
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Vision loss detection and progression prediction
Our team aim to better characterize the functional loss from ocular diseases with the goals of developing novel diagnostic methods and improving the progression prediction.
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Relationship between retinal structure and visual function in eye diseases
Our team are investigating the relationship between damages of retinal structure and their precise effects on functional vision in eye diseases.
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Epidemiology and demographic features related to eye diseases
Our team are participating in the analysis work of two large clinical cohort studies. We aim to investigate the interactions of gene, environment, society and personal lifestyle with disease onset and progression.
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Aging and lifestyle affecting the eye
Our team are participating in a population-based study that includes ocular imaging and a large number of physiological and cognitive parameters to systematically investigate the relationship between retinal parameters and age and lifestyle variables.
Read MoreWhat We Do
We work at the intersection of artificial intelligence and ophthalmology. We aim to develop novel AI models to enhance our knowledge and understanding of ocular diseases and ultimately improve clinical treatment and management through our passionate research. We publish our research in leading medical journals and prominent AI conferences such as CVPR and ICLR. We are committed to promoting knowledge sharing and research collaborations. Our representative research work can be found here.
In this video interview, Dr. Elze discussed the potentials and limitations of AI for detecting glaucoma progression.
Latest News
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Hannah Rana won best poster award at 2025 Harvard Ophthalmology Annual Meeting
June 13, 2025 -
Professor Paul Liang’s seminar
March 19, 2025 -
Professor Yilun Du’s seminar
February 27, 2025 -
Yu Tian secured Assistant Professor job at University of Central Florida
December 10, 2024