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Dr. Tobias Elze is a computational vision scientist at Schepens Eye Research Institute of Mass. Eye and Ear. His research addresses the methodology of basic and clinical vision science, such as optimal design of experiments and clinical studies and optimal data analysis (particularly for large and high-dimensional datasets). Dr. Elze's current projects include the functional characterization of eye diseases like glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy, and the relationship between retinal structure and functional vision loss. Dr. Elze also develops adaptive sampling techniques for efficient clinical function testing and investigates display technology for clinical applications. As a former member of the research group “Complex Structures in Biology and Cognition” at Max Planck Institute for Mathematics in the Sciences, Dr. Elze focused on methodology in visual neuroscience and psychophysics. In 2011, he joined the laboratory of Dr. Peter Bex at Schepens Eye Research Institute of Mass. Eye and Ear, where he started to investigate ophthalmic diseases using psychophysical and bioinformatical methods and machine learning. In 2013, he became an Instructor in Ophthalmology and in 2017 an Assistant Professor of Ophthalmology at Harvard Medical School. His group works in the intersection among mathematics, computer science, and clinical ophthalmology.

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Dr. Mengyu Wang (name in Chinese: 王孟渝) is a faculty in the Department of Ophthalmology at Schepens Eye Research Institute (SERI) of Massachusetts Eye and Ear and Harvard Medical School (HMS) with a diverse research background including ophthalmology, radiology, machine learning, image processing and computational mechanics. Dr. Wang's current research focuses on developing mathematical, statistical and artificial intelligence models to enhance our knowledge and understanding of eye diseases and ultimately improve clinical treatment of eye diseases. Furthermore, Dr. Mengyu Wang is a recipient of the NIH K99/R00 Pathway to Independence Award as well as a co-inventor on four patents. In Dr. Mengyu Wang's personal life, he is an enthusiastic amateur of writing songs and music apart from playing guitar and piano. Here is an incomplete collection of his songs and music.

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Harvard Catalyst Profile
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Biography

Nazlee Zebardast, MD is focused on developing machine learning based tools for disease detection, aiding clinicians in assessing for disease progression and eventually optimizing patient-related outcomes. Currently, in collaboration with researchers at Ocular Genomics Institute and Massachusetts General Hospital she is using statistical genetics and machine learning methods for glaucoma genetic risk prediction. Specifically, her research focuses on imaging genetics with aim to 1) develop a polygenic risk score for open angle glaucoma and construct deep learning models for glaucoma genetic risk prediction using fundus imaging and 2) define structural and longitudinal endophenotypes using machine learning methods that are closely aligned with disease subtype and progression and identify novel genetic markers for disease. This work could lay the foundation for optimized machine learning based screening tests built on fundus images and/or genetic risk profiling.

In addition to this work, Dr Zebardast has an established track record in global health and epidemiology research. She is currently working with a number of large datasets including NHANES, IFACE, SEE, UK Biobank, IRIS registry, Medicare and NEISS to answer important clinical questions. Specifically, she is currently exploring the extensive IRIS registry to better understand the current use of MIGS in the US and delineate which patients may most benefit from these procedures and using Medicare claims data to identify sociodemographic predictors of outcomes, healthcare utilization and cost among older adults with glaucoma.