Jiayang Sun

Jiayang Sun brings the sharp focus she uses when rock climbing and ballroom dancing to her role as chair of Mason's College of Engineering and Computing's Department of Statistics. Just as a strategy is a must with both activities, Sun's position requires a similar mindset. Her vision is to put the department in the national spotlight for statistical research and data science.

Jiayang Sun is professor, chair, and Bernard Dunn Eminent Scholar at the Department of Statistics, George Mason University. She received her PhD in statistics from Stanford University. Before joining Mason in August 2019, she was a professor of the Department of Population and Quantitative Health Sciences and the Director of the Center for Statistical Research, Computing and Collaboration (SR2c), Case Western Reserve University. She also served as the inaugurate ASA/ACM/AMS/IMS/MAA/SIAM Science & Technology Policy Fellow, working as the Big Data Senior Fellow for Big Data Analytics in the leadership team for Partnerships for PDI at the USDA ARS, Office of National Programs between 9/1/2019-8/31/2020. 

She is an elected Fellow of the American Statistical Association (ASA), an elected Fellow of the Institute of Mathematical Statistics (IMS), and an elected Member of the International Statistical Institute (ISI). She was the 2016 President of the Caucus for Women in Statistics (CWS) and has been on various committees in the ASA, IMS, CWS, ISI, and other national and international professional panels and boards. Her work has been supported by awards from the NSF, NIH, NSA, DOD, DOE, VA, and ASA.

She has published in top statistical and computational journals, including Annals of Statistics, Journal of American Statistical Association, Annals of Probability, Biometrika, Statistical Science, Biometrical Journal, Statistics in Medicine, JCGS, and SIAM J Sci. & Stat. Comp, and other statistical and scientific journals. Her statistical research has included simultaneous confidence regions and multiple testing, selection bias and measurement errors, mixtures and image analysis, machine learning, causal inference, semiparametric and non-parametric problems, statistical computing, graphics, data analytics, bioinformatics, and big data. Her interdisciplinary work has included cancer, environmental science, imaging, neuroscience, wound care, dental, and other medical sciences, in addition to astronomy, computer science, energy, law, and now agriculture.

Her work has been supported by awards from the NSF, NIH, NSA, DoD, DOE, VA, and ASA.

Research Interests:

• Simultaneous inference and Multiple Testing
• Biased sampling and Measurement Errors
• Mixtures and Statistical Imaging
• Data mining, Longitudinal, and High-dimensional Data
• Bioinformatics and Statistical Computing
• Semi, Non-parametric, and  Random Fields
• Software Research
• Interdisciplinary Work