Michelle Wang's directory photo.

Michelle Wang

Associate Professor

Primary Affiliation

Multimodal Vascular Imaging


Status Part-time Faculty

Home Department of Statistics

Phone 244-2694


Address 2127 Beckman Institute, 405 North Mathews Avenue

  • Biography

    Michelle Yongmei Wang is an associate professor in the Department of Statistics. Her primary affiliation is Multimodal Vascular Imaging. She is affiliated with computational imaging. Her expertise is in quantitative/mathematical methods and modeling in psychology as well as brain and cognitive sciences.


    Ph.D., Yale University

  • Research

    Research areas:

    • Quantitative and cognitive psychology

    • Precision medicine

    Research interests:

    • Statistical/mathematical methods

    • Machine learning and data mining

    • Signal and imaging processing

    • Computation and Analysis

    Professor Wang’s research involves various topics within engineering & materials science, medicine & life sciences, and mathematics. She is well informed on MRI and functional neuroimaging.

  • 2015

    • M. Y. Wang, and C. E. Zwilling, Multivariate computing and robust estimating for outlier and novelty in data and imaging sciences. Advances in Bioengineering, pp. 317-336, 2015.


    • Xia, J.; Wang, M. Y., Particle Filtering with Sequential Parameter Learning for Nonlinear Bold FMRI Signals. Advances and Applications in Statistics 2014, 40, (1), 61-74.
    • Zhou, C.; Zwilling, C. E.; Calhoun, V. D.; Wang, M. Y., Efficient Blockwise Permutation Tests Preserving Exchangeability. International Journal of Statistics in Medical Research 2014, 3, (2), 145-152.


    • Vo, L. T. K.; Walther, D. B.; Kramer, A. F.; Erickson, K. I.; Boot, W. R.; Voss, M. W.; Prakash, R. S.; Lee, H.; Fabiani, M.; Gratton, G.; Simons, D. J.; Sutton, B. P.; Wang, M. Y., Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity. PLOS One 2011, 6, (1).
    • Wang, M. Y.; Zhou, C.; Xia, J., Statistical analysis for recovery of structure and function from brain images. In Biomedical Engineering, Trends, Researches and Technologies, Komorowska, M. A.; Olsztynska-Janus, S., Eds. InTech: 2011; pp 169-190.


    • Sakoglu, U.; Pearlson, G. D.; Kiehl, K. A.; Wang, Y. M.; Michael, A. M.; Calhoun, V. D., A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia. Magnetic Resonance Materials in Physics Biology and Medicine 2010, 23, (5-6), 351-366.


    • Wang, Y. M.; Xia, J., Unified framework for robust estimation of brain networks from fMRI using temporal and spatial correlation analyses, IEEE Transactions on Medical Imaging, 2009; 28, (8), 1296-1307.
    • Xia, J.; Liang, F.; Wang, Y. M., fmri analysis through Bayesian variable selection with a spatial prior, IEEE International Symposium on Biomedical Imaging, 2009; pp 714-717.
    • Zhou, C; Wang, H.; Wang, Y. M., Efficient moments-based permutation tests, Neural Information Processing Systems (NIPS), 2009; in press.
    • Xia, J.; Liang, F.; Wang, Y. M., On Clustering fMRI using Potts and Mixture Regression Models, IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, 2009; pp 4795-4798.
    • Zhou, C.; Wang, Y. M., New Blockwise Permutation Tests Preserving Exchangeability in Functional Neuroimaging, IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, 2009; pp 6977-6980.


    • Zhou, C. X.; Wang, Y. M., Hybrid Permutation Test with Application to Surface Shape Analysis. Statistica Sinica 2008, 18, (4), 1553-1568.


    • Wang, Y. M.; Xia, J., Functional interactivity in fMRI using multiple seeds’ correlation analyses – novel methods and comparisons, Information Processing in Medical Imaging, 2007, pp. 147-159.


    • Liu, H.; Wang, Y. M.; Simpson, D. G., Bi-criterion clustering and selecting the optimal number of clusters via agreement measure, Joint Statistical Meetings, 2006, pp. 2098-2105.


    • Bansal, R.; Staib, L. H.; Whitman, R.; Wang, Y. M.; Peterson, B. S., ROC based assessments of 3D cortical surface-matching algorithms, Neuroimage, 2005, 24, (1), 150-162.


    • Wang, Y. M.; Zhang, H., Detecting image orientation based on low-level visual content, Computer Vision and Image Understanding, 2004, 93, (3), 328-346.
    • Wang, Y. M.; Zhang, J.; Zhang, Z.; Guo, B., Directional coherence interpolation for three-dimensional grey-level images, International Journal of Image and Graphics, 2004, 4, (4), 535-561.


    • Wang, Y.; Peterson, B. S.; Staib, L. H., 3D brain surface matching based on geodesics and local geometry, Computer Vision and Image Understanding, 2003, 89, (2-3), 252-271.  


    • Wang, Y.; Staib, L. H., Physical model based non-rigid registration incorporating statistical shape information, Medical Image Analysis, 2000, 4, (1), 7-20.
    • Wang, Y.; Staib, L. H., Boundary finding with prior shape and smoothness models, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22, (7), 738-743.