Dirk Colbry
Director of HPC Studies, Department of Computational Mathematics, Science and Engineering (CMSE)
Room 1516, Engineering Building
428 S. Shaw Ln.
(517) 432-0455
colbrydi@msu.edu
- About Me
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Dr. Dirk Colbry is the Director of HPC Studies in the newly formed Department of Computational Mathematics, Science and Engineering.
An alumnus of MSU, Colbry has a Ph.D. in Computer Science and his principle areas of research include machine vision and pattern recognition (specializing in scientific imaging). Dr. Colbry also does research in computational education and high performance computing. From 2009 until 2015, Dr. Colbry worked for the Institute for Cyber Enbled Research as a computational consultant and Director of the HPCC. Dr. Colbry collaborates with scientists from multiple disciplines including Engineering, Toxicology, Plant and Soil Sciences, Zoology, Mathematics, Statistics and Biology. Recent projects include research in Image Phenomics; developing a commercially-vable large scale, cloud based image pathology tool; and helping develop methods for measuring the Carbon stored inside of soil. Dr. Colbry has taught a range of courses, including; communication "soft" skills, introduction to computational modeling, microprocessors, artificial intelligence, scientific image analysis, compilers, exascale programing, and courses in programming and algorithm analysis.
- May 31, 2016
- Selected Publications
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[1]I. Sagert, J. Howell, A. Staber, T. Strother, D. Colbry, and W. Bauer, “Knudsen-number dependence of two-dimensional single-mode Rayleigh-Taylor fluid instabilities,” Physical Review E, vol. 92, no. 1, p. 013009, 2015.[2]I. Sagert, W. Bauer, D. Colbry, J. Howell, R. Pickett, A. Staber, and T. Strother, “Hydrodynamic shock wave studies within a kinetic Monte Carlo approach,” Journal of Computational Physics, vol. 266, pp. 191–213, 2014.[3]R. Nault, D. Colbry, C. Brandenberger, J. R. Harkema, and T. R. Zacharewski, “Development of a Computational High-Throughput Tool for the Quantitative Examination of Dose-Dependent Histological Features,” Toxicologic pathology, p. 0192623314544379, 2014.
- Teaching
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FS17: CMSE 491 Section 002 Numerical Linear Algebra
SS18: CMSE 890 Section 001 Image Processing Techniques
Click "Teaching" link to see past courses.