BeautyCenter Computational Neuroanatomy &  Neurofunctions

Address

Medical Science Center 5785
1300 University Ave
Madison, WI 53706

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

Job Opening

Postdoctoral fellowships on multimodal twin brain imaging study is available for years 2017-2020.Read More

Group Emailing List

I maintain a group emailing list that discusses various methodological issues on brain image and network analysis, news on jobs and conferences.  

Research

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 and network shape variations in both normal and clinical populations using various mathematical, computational and statistical techniques. A major challenge in the field is caused by the massive amount of nonstandard high dimensional non-Euclidean imaging and network data that are difficult to analyze using available techniques. This requires new computational solutions that are formulated in a differential geometric and algebraic topological setting in addressing more complex scientific hypotheses. Other than computational neuroanatomy, my interest lies in shape analysis, network analysis, medical image analysis, functional data analysis, random fields theory,  and diffusion equations.Read More

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 Department of Statistics and 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. He has written two books on brain image analysis and working on the third book that will be published in 2018. Full CV