Bio

PhD Applied Mathematics and Scientific Computation University of Maryland 2005MS Electrical Engineering Vanderbilt University 2001BS Physics and Mathematics Vanderbilt University 1999

"We teach and develop techniques that allow us to make better sense of signals, images, and digital data in general."

Gustavo Kunde Rohde, Associate Professor

Dr. Rohde develops computational predictive models using machine learning and signal and image processing with applications in pathology, radiology, systems biology, and mobile sensing. He earned B.S. degrees in physics and mathematics in 1999, and the M.S. degree in Electrical Engineering in 2001 from Vanderbilt University. He received a doctorate in applied mathematics and scientific computation in 2005 from the University of Maryland. He is Professor of Biomedical Engineering and Electrical and Computer Engineering at the University of Virginia.

Research in the Imaging and Data Science Lab aims to contribute ideas in support of biomedical imaging, mobile, and remote sensing applications. We specialize on objective and quantitative modeling of data from imaging and other types of sensors by incorporating knowledge from multiple disciplines including applied mathematics, signal processing, machine learning and statistics.

Research Interests

  • Medical and Molecular Imaging
  • Signal and Image Processing
  • Biomedical Data Sciences
  • Computer Graphics and Vision
  • Biomedical Data Sciences
  • Machine Learning
Open portrait of Gustavo Rohde

Gustavo Rohde, PhD, Associate Professor of Biomedical Engineering and Electrical and Computer Engineering

In the News

Selected Publications

  • Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning | S Kundu, BG Ashinsky, M Bouhrara, EB Dam, S Demehri, ...GK Rohde ABS Proceedings of the National Academy of Sciences 117 (40), 24709-24719
  • Parametric signal estimation using the cumulative distribution transform | AHM Rubaiyat, K Hallam, J Nichols, M Hutchinson, S Li, G Rohde ABS IEEE Transactions on Signal Processing (2020)
  • Cell image classification: a comparative overview | M Shifat‐E‐Rabbi, X Yin, CE Fitzgerald, GK Rohde ABS Cytometry Part A 97 (4), 347-362 (2020)
  • Generalized sliced wasserstein distances | S Kolouri, K Nadjahi, U Simsekli, R Badeau, G Rohde ABS Advances in Neural Information Processing Systems 261-272 (2019)
  • Methods to label, image, and analyze the complex structural architectures of microvascular networks | BA Corliss, C Mathews, R Doty, G Rohde, SM Peirce ABS Microcirculation 26 (5), e12520 (2019)
  • The cumulative distribution transform and linear pattern classification SR Park, S Kolouri, S Kundu, GK Rohde ABS Applied and Computational Harmonic Analysis 45 (3), 616-641 (2018)
  • Optimal mass transport: Signal processing and machine-learning applications | S Kolouri, SR Park, M Thorpe, D Slepcev, GK Rohde ABS IEEE signal processing magazine 34 (4), 43-59 (2017)