PhD, University of Utah, 2016

Professor Zhang completed her PhD in computer science at the University of Utah. She was a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. Professor Zhang received the Medical Image Computing and Computer Assisted Intervention (MICCAI) young scientist award in 2014 and was a runner-up for the young scientist award in 2016. She has been a member of MICCAI society and was an area chair for MICCAI 2018, 2019. She also served as an area chair for International Symposium on Biomedical Imaging (ISBI) 2020 and Medical Imaging with Deep Learning (MIDL) 2021.


  • Best Poster Award, 26th international conference on Information Processing in Medical Imaging (IPMI) 2019
  • Best Paper Finalist, 19th MICCAI 2016
  • Best Paper Award, 17th International Conference on Medical Image Computing and Computer-Assisted (MICCAI) 2014

Research Interests

  • Biomedical Image Analysis
  • Statistical Shape Analysis
  • Machine Learning

Selected Publications

  • Bayesian Principal Geodesic Analysis for Estimating Intrinsic Diffeomorphic Image Variability ABS Zhang, Miaomiao. 2016. Ph.D. diss., The University of Utah
  • Frequency diffeomorphisms for efficient image registration ABS Zhang, M., Liao, R., Dalca, A. V., Turk, E. A., Luo, J., Grant, E. P., and Golland, P. International Conference on Information Processing in Medical Imaging (IPMI), 2017 (Oral Presentation)
  • Using the variogram for vector outlier screening: application to feature-based image registration ABS Jie Luo, Sarah Frisken, Ines Machado, Zhang, M., et al. International Journal of Computer Assisted Radiology and Surgery, 2018
  • Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms ABS Zhang, M., Wells III, W. M., and Golland, P. Medical Image Analysis (MEDIA), 2017
  • Statistical shape analysis: From landmarks to diffeomorphisms ABS Zhang, M. and Golland, P. Medical Image Analysis (MEDIA), 2016
  • Bayesian principal geodesic analysis for estimating intrinsic diffeomorphic image variability ABS Zhang, M. and Fletcher, P. T. Medical Image Analysis (MEDIA), 2015

Courses Taught

  • Machine Learning in Image Analysis Fall 2021
  • Machine Learning for Engineers Spring 2021
  • Digital Image Processing Fall 2020
  • Foundation of Data Analysis Spring 2020