Samuel Gerber

Samuel Gerber

Staff R&D Engineer

Sam studied computer science at the University of Applied Sciences and Arts Northwestern Switzerland, before he completed his Ph.D. at the University of Utah. Prior to joining Kitware, he served as a research scientist at the College of Arts & Sciences Information Technology (CASIT) at the University of Oregon. There, he focused on data analysis methodology. Sam also worked as a visiting assistant professor at Duke University and as a research assistant at the University of Utah. He has won several awards for his efforts, including Best Paper in the “Journal of Medical Image Analysis.”

  1. H. Greer, S. Gerber, M. Niethammer, R. Kwitt, M. McCormick, D. Chittajallu, N. Siekierski, M. Oetgen, K. Cleary, and S. Aylward, "Scoliosis screening and monitoring using self contained ultrasound and neural networks," in Proceedings of the IEEE International Symposium on Biomedical Imaging, 2018. [URL]
  2. D. Chittajallu, N. Siekierski, S. Lee, S. Gerber, J. Beezley, D. Manthey, D. Gutman, and L. Cooper, "Vectorized persistent homology representations for characterizing glandular architecture in histology images," in Proceedings of the IEEE International Symposium on Biomedical Imaging, 2018. [URL]
  3. D. Chittajallu, M. McCormick, S. Gerber, T. Czernuszewicz, R. Gessner, M. Willis, M. Niethammer, R. Kwitt, and S. Aylward, "Image-based methods for phase estimation, gating and temporal super-resolution of cardiac ultrasound," IEEE Transactions on Biomedical Engineering, pp. 1-1, 2018. [URL]
  4. S. Gerber and M. Maggioni, "Multiscale Strategies for Computing Optimal Transport," Journal of Machine Learning Research, vol. 18, no. 1, pp. 2440-2471, Jan. 2017. [URL]
  5. S. Gerber, M. Jallais, H. Greer, M. McCormick, S. Montgomery, B. Freeman, D. Kane, D. Chittajallu, N. Siekierski, and S. Aylward, "Automatic Estimation of the Optic Nerve Sheath Diameter from Ultrasound Images," in Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. Springer International Publishing, 2017, pp. 113-120. [URL]
  6. M. Maggioni and S. Gerber, "Multiscale dictionaries, transforms, and learning in high-dimensions," in SPIE Optical Engineering + Applications, 2013. [URL]
  7. S. Gerber and R. Whitaker, "Regularization-free Principal Curve Estimation," Journal of Machine Learning Research, vol. 14, no. 1, pp. 1285-1302, May 2013. [URL]
  8. K. Potter, S. Gerber, and E. Anderson, "Visualization of Uncertainty without a Mean," IEEE Computer Graphics and Applications, vol. 33, no. 1, pp. 75-79, Jan. 2013. [URL]
  9. S. Gerber, O. Rübel, P. Bremer, V. Pascucci, and R. Whitaker, "Morse–Smale Regression," Journal of Computational and Graphical Statistics, vol. 22, no. 1, pp. 193-214, Jan. 2013. [URL]
  10. S. Gerber and K. Potter, "Data Analysis with the Morse-Smale Complex: The msr Package for R," Journal of Statistical Software, vol. 50, no. 2, 2012. [URL]
  11. P. Zhu, S. Awate, S. Gerber, and R. Whitaker, "Fast Shape-Based Nearest-Neighbor Search for Brain MRIs Using Hierarchical Feature Matching," in Proceedings of the Internation Conference on Medical Image Computing and Computer Assisted Intervention, 2011. [URL]
  12. S. Gerber, T. Tasdizen, P. Thomas Fletcher, S. Joshi, and R. Whitaker, "Manifold modeling for brain population analysis," Medical Image Analysis, vol. 14, no. 5, pp. 643-653, Oct. 2010. [URL]
  13. S. Gerber, P. Bremer, V. Pascucci, and R. Whitaker, "Visual Exploration of High Dimensional Scalar Functions," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1271-1280, Nov. 2010. [URL]
  14. A. Agarwal, H. Daumé, III, and S. Gerber, "Learning Multiple Tasks Using Manifold Regularization," in Proceedings of the International Conference on Neural Information Processing Systems, 2010. [URL]
  15. S. Gerber, T. Tasdizen, and R. Whitaker, "Dimensionality reduction and principal surfaces via Kernel Map Manifolds," in Proceedings of the IEEE International Conference on Computer Vision, 2009. [URL]
  16. S. Gerber, T. Tasdizen, S. Joshi, and R. Whitaker, "On the Manifold Structure of the Space of Brain Images," in Proceedings of the Internation Conference on Medical Image Computing and Computer Assisted Intervention, 2009. [URL]
  17. R. Tao, P. Fletcher, S. Gerber, and R. Whitaker, "A Variational Image-Based Approach to the Correction of Susceptibility Artifacts in the Alignment of Diffusion Weighted and Structural MRI," in Proceedings of the International Conference on Information Processing in Medical Imaging, 2009. [URL]
  18. M. Fuchs and S. Gerber, "Variational shape detection in microscope images based on joint shape and image feature statistics," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2008. [URL]
  19. S. Gerber, T. Tasdizen, and R. Whitaker, "Robust non-linear dimensionality reduction using successive 1-dimensional Laplacian Eigenmaps," in Proceedings of the International Conference on Machine Learning, 2007. [URL]