Dr. Chenglong Yu is a genetic epidemiologist and statistical geneticist, serving as a Senior Research Fellow with the Public Health Genomics group at the School of Public Health and Preventive Medicine, and as an Adjunct Senior Research Fellow at the Victorian Heart Institute (VHI), Monash University. His expertise spans genome-wide association studies, polygenic risk scores, population genetics, genotype-environment interactions, risk prediction, and epigenetics. Dr. Yu currently oversees the genomics research programs for the ASPirin in Reducing Events in the Elderly (ASPREE) study, Australia’s largest randomized controlled trial and genomic cohort focused on aging.

Chenglong’s research journey began with a strong foundation in mathematics (B.Sc., M.Sc., and Ph.D.). During his Ph.D. at the Chinese University of Hong Kong and his early postdoctoral work at the University of Illinois Chicago, he focused on the mathematical theories and applications of molecular evolution and phylogenetics. In recent years, his research has shifted entirely to genetic epidemiology and statistical genetics, leading to substantial publication outputs and successful research funding. Chenglong is deeply gratified that his work directly contributes to advancing human health and remains committed to long-term engagement in this impactful field.

Chenglong's research focuses on exploring the effect of genetic factors on a range of complex diseases. As the leading author, he has published his findings in high-profile journals across various fields, including major depression (Transl Psychiatry 2017, 2018; J Affect Disord 2017, 2018 [2]; Psychiatry Res 2017), cancer (Cancer Epidemiol Biomarkers Prev 2021; Cancers 2021; Epigenetics 2022), cardiovascular disease (JAHA 2023; JACC: Advances 2024; Eur Heart J Cardiovasc Pharmacother 2025), dementia (Alzheimer's & Dementia 2023), age-related macular degeneration (Ophthalmology 2024), and women's health (eBioMedicine 2024), among others.

• Genetic Epidemiology
• Statistical Genetics
• Bioinformatics
• Biostatistics