Moo K. Chung

Associate Professor
Department of Biostatistics and Medical Informatics
University of Wisconsin-Madison



Vancouver 2003

Cover art for NeuroImage 2003

Book published in 2012



     



NIH Biosketch

Full CV

Publications

Software

Teaching


Address

Medical Science Center 4750
1300 Highland Ave
Madison, WI 53706

Tel: 608-217-2452
Email:mkchung@wisc.edu


Research Interest

My main research area is computational neuroanatomy, where non invasive brain imaging modalities such as magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) are used to map spatiotemporal dynamics of the human brain. Computational neuroanatomy deals with the computational problems arising from the quantification of the structure and the function of the human brain. My research has been concentrated on the methodological development of quantifying anatomical shape variations in both normal and clinical populations using various mathematical and statistical techniques. A major challenge in the field is caused by the massive amount of nonstandard high dimensional non-Euclidean imaging data that are difficult to analyze using available techniques. This requires new computational solutions that are formulated in a differential geometric setting in addressing more complex scientific hypotheses. Other than computational neuroanatomy, my interest lies in shape analysis, medical image analysis, nonparametric regression, functional data analysis, random fields theory,  and partial differential equations. If you are interested in working with me as a graduate student or a postdoc, please contact me.

Short Bio

Moo K. Chung, Ph.D. is an Associate Professor in the Department of Statistics, Biostatistics and Medical Informatics at the University of Wisconsin-Madison. He is also affiliated with the Waisman Laboratory for Brain Imaging and Behavior. Dr. Chung received Ph.D. in Statistics from McGill University under Keith J. Worsley and James O. Ramsay in 2001. Dr. Chung’s main research area is computational neuroanatomy, where noninvasive brain imaging modalities such as magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) are used to map the spatiotemporal dynamics of the human brain. His research concentrates on the methodological development required for quantifying and contrasting anatomical shape variations in both normal and clinical populations at the macroscopic level using various mathematical, statistical and computational techniques. Recently, Dr. Chung won Vilas Associate Award for years 2013-2014 for his applied topological research (persistent homology) to medical imaging and the Editor's Award for best paper published in Journal of Speech, Language, and Hearing Research in year 2011 for the paper that analyzed vocal tract CT images.