Bio

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 an area chair for MICCAI since 2018. She is also an active area chair for International Symposium on Biomedical Imaging (ISBI) and Medical Imaging with Deep Learning (MIDL).

Awards

  • NIH Trailblazer R21 Award 2023
  • NSF CAREER Award 2023
  • UVA Research Innovation Award 2023
  • Best Poster Award, IPMI 2019
  • Best Paper Finalist, MICCAI 2016
  • MIT IMPACT Fellow 2016
  • Best Paper Award, MICCAI 2014

Research Interests

  • Biomedical Image Analysis
  • Statistical Shape Analysis
  • Machine Learning

In the News

Selected Publications

  • Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers ABS Wang, J. and Zhang, M. NeurIPS 2022
  • DeepFLASH: An efficient network for learning-based medical image registration ABS Wang, J. and Zhang, M. CVPR 2020
  • 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
  • Bayesian Principal Geodesic Analysis for Estimating Intrinsic Diffeomorphic Image Variability ABS Zhang, Miaomiao. 2016. Ph.D. diss., The University of Utah
  • 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
Google Scholar
ResearchGate

Courses Taught

  • Machine Learning in Image Analysis Fall 2021, 2022, 2023
  • Machine Learning for Engineers Spring 2021
  • Digital Image Processing Fall 2020
  • Foundation of Data Analysis Spring 2020, 2023
Course Catalog