Michael Grauer is a Technical Leader on the data and analytics team at Kitware. He earned a B.A. in computer science and history from the University of Texas at Austin and an M.S. in computer science from Drexel University. At Drexel, his research focus was digital archiving.
Michael’s experience as an engineer is in building scalable server-side processing frameworks that enable scientific workflows over web platforms. At Kitware, he has made contributions to the design, organization, and implementation of Girder. Girder is an open source web-based platform for data management. Michael made similar contributions to the Midas platform for data management, which was the predecessor to Girder.
Michael currently leads projects related to data management and analytics that use scalable infrastructures and cloud-based deployments that rely on the Resonant platform. Michael also helps to drive the Algorithm as a Service offering that is based on Resonant. His work has spanned the domains of medical imaging, neurophysiology, computer vision, software quality, and algorithm evaluation for government, non-profit, and commercial customers.
- O. Ruebel, A. Tritt, B. Dichter, T. Braun, N. Cain, N. Clack, T. Davidson, M. Dougherty, J. Fillion-Robin, N. Graddis, M. Grauer, J. Kiggins, L. Niu, D. Ozturk, W. Schroeder, I. Soltesz, F. Sommer, K. Svoboda, L. Ng, L. Frank, and K. Bouchard, "NWB:N 2.0: An Accessible Data Standard for Neurophysiology," Neuroscience, Jan. 2019. [URL]
- J. Fillion-Robin, M. McCormick, O. Padron, M. Smolens, M. Grauer, and M. Sarahan, "jcfr/scipy_2018_scikit-build_talk: SciPy 2018 Talk | scikit-build: A Build System Generator for CPython C/C++/Fortran/Cython Extensions," presented at SciPy 2018, 2018. [URL]
- C. Harris, P. O'Leary, M. Grauer, A. Chaudhary, C. Kotfila, and R. O'Bara, "Dynamic Provisioning and Execution of HPC Workflows Using Python," in Workshop on Python for High-Performance and Scientific Computing, 2016. [URL]
- M. Grauer, P. Reynolds, M. Hoogstoel, F. Budin, M. Styner, and I. Oguz, "A midas plugin to enable construction of reproducible web-based image processing pipelines," Frontiers in Neuroinformatics, vol. 7, pp. 46, 2013. [URL]
- F. Budin, M. Hoogstoel, P. Reynolds, M. Grauer, S. O'Leary-Moore, and I. Oguz, "Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics," Frontiers in Neuroinformatics, vol. 7, pp. 15, 2013. [URL]