PROFILE

Shenying Fang, Professor and doctor supervisor of School of Public Health and Emergency Management of Southern University of Science and Technology (SUSTech), Leading Talents Program of Guangdong Province “Zhujiang Scholar”, Shenzhen Pengcheng Peacock Program Distinguished Professor. Dr. Fang obtained his PhD in biostatistics in the University of Texas Health Science Center in 2008 and then worked as a postdoc in the University of Texas MD Anderson Cancer Center from 2009-2011. He started his research group in the University of Texas MD Anderson Cancer Center as an assistant professor in 2012 and promoted to associate professor in 2019. In 2022, he joined the Sustech as a professor. He was appointed as a distinguished professor in Wuhan University of Science and Technology in 2015 and “Nanshan Scholar” Distinguished Professor in Guangzhou Medical University in 2017. Dr. Fang serves as a reviewer for 13 scientific journals including American Journal of Human Genetics, Journal of National Cancer Institute, PLOS Genetics, International Journal of Cancer, Carcinogenesis, Scientific Reports, and etc., and as an editor or guest editor for PLOS ONE, Advances in Public Health and Frontiers in Oncology. He also serves as a reviewer for the National Science Center (NCN panel NZ7，Poland) and the National Natural Science Foundation of China. He is a member of American Association for Cancer Research, American Society of Human Genetics, and American Statistical Association.

He has applied novel statistical models and epidemiological study design to identify genetic and environmental determinants that contribute to the development and progression of malignant or chronic diseases or new emerging infectious diseases. Dr. Fang has been involved in collecting the largest melanoma case-control cohort and built the melanoma risk prediction model in US. Dr. Fang’s research interests now focus on integrative analysis of multi-omics data with medical image features to promote early cancer diagnosis, to characterize tumor classification, and to predict individualized treatment effect and disease progression, via statistical genetics, bioinformatics, and machines learning approaches. His work is reported in 88 SCI-indexed articles, many in high profile journals, such as Journal of Clinical Oncology, Journal of Investigative Dermatology, Nature Genetics, International Journal of Cancer, The Lancet Oncology, Cancer, and etc.. His research findings were cited and discussed broadly by Cancer network and NEJM, and he was invited to present an oral speech at American Society of Human Genetics in 2011 and at Global Chinese Statistics Annual Conference in 2020.