The Ma Lab at Fred Hutchinson Cancer Research Center specializes in statistical and computational methods for big biomedical data. We employ a variety of statistical learning methods, ranging from dimension reduction, graphical models, and high-dimensional data analysis, to address the analytical challenges faced with interpreting complex health data. The long-term goals of our research are to enhance biomarker discoveries through powerful and robust statistical inference, and to translate these findings to advance clinical research.
Our current research interests include statistical learning, network analysis, and systems biology, with applications to cancer biology and aging.
Advising: We are recruiting motivated and hard-working students interested in statistical learning for bimedical data. If you are an undergrad or graduate student at the University of Washington, and you are interested in any of the papers or projects listed on this website, send me an email with your interests and CV.
I will be visiting Department of Statistics at Texas A&M University as Assistant Professor, during the academic year 2019-2020.
Jing received award from The Jayne Koskinas Ted Giovanis Foundation for Health and Policy, joint with Minjoung Kyoung, Michael Konopka, Tara Sigdel, Young Hwan Chang on a proposal titled ``Understanding Therapeutics Failures Through 4D Single-cell Analysis of Metabolic Heterogeneity”.