Professor Mingguang He

Head of Ophthalmic Epidemiology

Professor Mingguang He leads CERA’s ophthalmic epidemiology research and has a particular interest in twin studies, randomised clinical trials and imaging technology.

Professor Mingguang He

Head of Ophthalmic Epidemiology


Professor Mingguang He is the Professor of Ophthalmic Epidemiology at the University of Melbourne.

He undertook his medical training in China and holds a Master of Public Health degree from Johns Hopkins University in Baltimore, and PhD in ophthalmology at Moorfields Eye Hospital in London.

Professor He is a global expert in vision-related clinical and epidemiologic research. He has led some important epidemiological studies and clinical trials, including the first population-based study on myopia in China, the first population-based study on glaucoma in China, a clinical trial to prove the efficacy of increased outdoor time on myopia prevention published in JAMA 2015 and a prophylactic clinical trial on angle closure glaucoma published in Lancet 2019.  His publications have attracted more than 13K citations.

He has received > $10 million in major research grants in Australia, including the prestigious NHMRC investigator Grant and Medical Research Future Fund for his research on artificial intelligence.

He founded and served as the first president of the Asia Pacific Tele-Ophthalmology Society, and is a founding council member of Asia Pacific Myopia Society and Deputy Secretary-General for Asia Pacific Academy of Ophthalmology.

Professor He is actively recruiting postdoc fellows, PhD/Master students and visiting fellows for his ongoing research projects.

Key research questions
  • How can artificial intelligence-assisted screening for diabetic retinopathy and other eye diseases be applied in different care models in non-ophthalmology settings, like GP clinics, endocrinology clinics and Aboriginal medical services and other screening programs?
  • What is the accuracy, cost-efficiency and acceptancy of the care models in real-world practice?
  • How can we integrate existing and further evolved deep learning technology to develop and validate a clinical decision system that is able to predict disease outcomes and prognosis?

Current projects

Selected publications

My team

Key collaborators

Funding and support

Current projects

  • Artificial intelligence system to detect eye and cardiovascular diseases
  • Artificial intelligence-assisted screening of diabetic retinopathy as a novel point-of-care model at endocrinology clinics and Aboriginal medical services.
  • Artificial intelligence in ophthalmology: from data to algorithm and real-world application
  • Eye health and chronic conditions in an adult population in NSW – findings from a large-scale cohort study

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