Mengyu Wang, PhD, Receives International Research Collaborators Award

January 9, 2023

Mengyu WangMengyu Wang, PhD, Assistant Professor of Ophthalmology at Harvard Medical School and Co-Director of the Harvard Ophthalmology Artificial Intelligence Lab, is a recipient of the Research to Prevent Blindness International Research Collaborators Award. Dr. Wang has a longstanding interest in developing mathematical, statistical, and artificial intelligence models to enhance our knowledge and understanding of a number of eye diseases and ultimately improve clinical treatment for these diseases.

This award will provide $75,000 in funding to Dr. Wang and his collaborator, Franziska Rauscher, OD, PhD, a researcher at Leipzig University in Germany, to use retinal anatomical features to improve the circumpapillary retinal nerve fiber layer thickness (RNFLT) norms with linear regression and deep learning models using a dataset with healthy subjects. The clinical utility of the new circumpapillary RNFLT norms personalized by individual retina anatomy will be validated through glaucoma patients from Mass Eye and Ear. The success of this project will provide personalized RNFLT profile norms based on individual retinal anatomy.

As part of the award, Dr. Wang will spend a period of time working with Dr. Rauscher in Germany to gain new knowledge and skills and deepen the collaborative relationship. 

Dr. Wang came to Mass Eye and Ear as a postdoctoral fellow in 2015 to focus on developing statistical models and artificial intelligence (AI) based methods to improve glaucoma diagnosis and monitoring. He joined the faculty as an instructor in 2017 and received a prestigious NIH K99/R00 Pathway to Independence Award for his study on the relationship between glaucoma and the three-dimensional optic nerve head related structure. In 2020 he was promoted to Assistant Professor. 

Dr. Wang's most important contribution to ophthalmology research is pioneering the effort of developing AI based approaches to better understand structural and functional changes in glaucoma to eventually improve diagnosis and prognosis of glaucoma. His representative research work includes reporting that retinal surface contour is a biomarker for glaucoma progression; developing an unsupervised AI based glaucoma progression detection method; and building deep learning models to reduce artifacts and noise in structural and functional measurements. He is a co-inventor on a number of patents leveraging AI techniques to improve the diagnosis and prognosis of glaucoma.

See also: Awards, Research