Jeon-1
(734) 936-1442
Methodologies: Biology Applications, Data, Statistics and Stochastic Methods

Jihyoun Jeon

Assistant Research Scientist, Epidemiology

Jihyoun Jeon is an Assistant Research Scientist in the Department of Epidemiology, in the School of Public Health. She is also a member of the University of Michigan Comprehensive Cancer Center (UMCCC), and an affiliate at the Fred Hutchinson Cancer Research Center (FHCRC). Her research interests focus on developing biologically based mathematical models and statistical methods to evaluate the impact of risk factors on various cancers, and the efficacy of screening to reduce cancer incidence and/or mortality. The goal of these modeling efforts is to better understand the underlying mechanism of the natural history of cancer, develop innovative methodologies to solve important public health questions, and assist public health policy makers in their decision process.

She is a core member of large multidisciplinary national consortia: the Lung Cancer group of the NCI consortium ‘Cancer Intervention and Surveillance Modeling Network (CISNET)’, Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), and Colorectal Transdisciplinary (CORECT) Study in the Genetic Associations and Mechanisms in Oncology (GAME-ON). She is particularly interested in developing mathematical models and simulation tools to investigate the synergistic impacts of tobacco control policies and CT screening on lung cancer risk in the US and in some middle-income countries. And she is also interested in developing risk prediction models for colorectal cancer that incorporate genetic variants identified form GWAS study along with environmental risk factors and modifiable lifestyle factors in population based and prospective studies. These models would provide a more accurate risk stratification of individuals, which would be useful to suggest individually tailored health strategies given the person’s risk profile in terms of genetic variants as well as lifestyle and environmental risk factors collectively.