Tim McGraw is an Assistant Professor of Computer Graphics Technology. His areas of interest are virtual reality, scientific visualization, real-time computer graphics, medical image processing and computational art. Specific projects include modeling and mesh editing in VR, diffusion tensor MRI (DT-MRI) visualization, and mesh processing. He was awarded 4 patents related to DT-MRI visualization projects performed with Siemens Corporate Research. He has previous industry experience as a Mechanical Engineer and as a game developer (Electronic Arts, Schell Games, Rainbow Studios). He received his Ph.D. in Computer and Information Science and Engineering from the University of Florida.
Ph.D. Computer and Information Science and Engineering, University of Florida
B.S. Mechanical Engineering, University of Florida
- Outstanding Faculty in Discovery, 2016.
- Phi Kappa Phi Honor Society, Faculty Member, Inducted 2010.
- Winner of Best Paper Award at International Symposium on Visual Computing (2009).
- Image selected for cover of IEEE Transactions on Visualization and Computer Graphics, Vol. 13,No. 6, November / December 2007.
Video accepted to IEEE Visualization 2007 Conference “Scientific Animation Theater.”
U.S. Patents Granted
T. McGraw, “Diffusion Tensor Surface Visualization,” United States Patent 8077938, Awarded December 13, 2011.
T. McGraw, “System and Method for Stochastic DT-MRI Connectivity Mapping on the GPU,” United States Patent 7672790, Awarded March 2, 2010.
T. McGraw, Z. Wang, “System and Method for Fast Tensor Field Segmentation,” United States Patent 7630530, Awarded December 8, 2009.
T. McGraw, “System and Method for Fast Texture-Based Tensor Field Visualization for DT - MRI,” United States Patent 7602180, Awarded October 13, 2009.
McGraw, T., Guayaquil-Sosa, A., Hybrid Rendering for Medical Image Atlas Visualization, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2017.
Zheng, H., Adamo-Villano, N., McGraw, T., Griggs, R., Using Computer Animation for Emergency Medicine Education. International Journal of Technology Enhanced Learning, 2017
McGraw, T., Garcia, E., McGraw, J., Parker, L., Fractal Image Editing with PhotoFrac. Journal of Science and Technology of the Arts, 8(2), 7-17, 2016.
Herring, D., McGraw, T., Inter-color NPR Lines: A Comparison of Rendering Techniques. The Computer Games Journal, 5(1), 39-53, 2016.
McGraw, T., Kang, J., Herring, D., Sparse Non-negative Matrix Factorization for Mesh Segmentation, International Journal of Image and Graphics, 2016.
McGraw, T. “ Fast Bokeh Effects Using Low-Rank Linear Filters. The Visual Computer, 2014, 1-11.
T. McGraw, T. Kawai, I. Yassine, L. Zhu, “Visualizing High-Order Symmetric Tensor Field Structure with Differential Operators,” Journal of Applied Mathematics, Volume 2011, July 2011, 27 pages.
T. McGraw, T. Kawai, J. Richards, “Allometric Scaling for Character Design,” Computer Graphics Forum, Volume 30, Issue, 1, March 2011, pp. 153-168.
T. McGraw, B.C. Vemuri, E. Ozarslan, Y. Chen, T. Mareci, “Variational Denoising of Diffusion-Weighted MRI,” Inverse Problems and Imaging, Volume 3, Number 4, November 2009, pp. 625-648.
T. McGraw, “Generalized Reaction-Diffusion Textures,” Computers and Graphics, Volume 32, Number 1, February 2008, pp. 82-92.
T. McGraw, M. Nadar, “Stochastic DT-MRI Connectivity Mapping on the GPU,” IEEE Transactions on Visualization and Computer Graphics, Volume 13, Number 6, November/December 2007, pp. 1504-1511.
T. McGraw, B. C. Vemuri, Y. Chen, M. Rao, T. Mareci, “DT-MRI Denoising and Neuronal Fiber Tracking,” Medical Image Analysis, Volume 8, Issue 2, June 2004, pp. 95-111.
McGraw, T., Glitch Style Visualization of Disrupted Neuronal Connectivity in Parkinson’s Disease. In IEEE Vis Arts Program (pp. 3-13), 2016.
Byrd, V.*, McGraw, T., Chen, Y., Connolly, P. (2016). Curriculum Development for Visualization Capacity Building. In ASEE Engineering Design Graphics Division 71st Mid-Year Conference, Nashua, NH (pp. 45-49), 2016.
Garcia, E., McGraw, T. , Bodygraphe: Gestural Computing for Visual Music, International Symposium on Non-Photorealistic Animation and Rendering (collocated with Eurographics 2016).
McGraw, T., Graph-based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling. In Advances in Visual Computing (pp. 3-13), 2015.
McGraw, T., Interactive Procedural Building Generation Using Kaleidoscopic Iterated Function Systems. In Advances in Visual Computing (pp. 102-111), 2015.
Bravo, E.G., McGraw, T., Visualizing Aldo Giorgini’s Ideal Flow. In Advances in Visual Computing (pp. 767-775), 2015.
Garcia, E., McGraw, T. (2015, March) Ideal Flow: The art and science of early computational models by Aldo Giorgini. Balance-Unbalance, Tempe AZ.
Wei, S., Chen, V., McGraw, T. (2015, June) Computer vision aided lip movement correction to improve English pronunciation. ASEE Annual Conference, Seattle WA.
McGraw, T., Herring, D. (2014). High-Order Diffusion Tensor Connectivity Mapping on the GPU. In Advances in Visual Computing (pp. 396-405).
McGraw, T., Herring, D.(2014). Shape Modeling with Fractals. In Advances in Visual Computing (pp. 540-549).
T. McGraw, T. Kawai, “A Spectral Approach to Nonlocal Mesh Editing,” International Symposium on Visual Computing, Las Vegas, NV, Nov/Dec 2010, pp. 634-643.
T. McGraw, T. Kawai, I. Yassine, L. Zhu, “New Scalar Measures for Diffusion-Weighted MRI Visualization,” International Symposium on Visual Computing, Las Vegas, NV, Nov/Dec 2009, pp. 934-943. (Winner of iCORE Best Paper Award.)
I. Yassine, T. McGraw, “4th Order Diffusion Tensor Interpolation With Divergence and Curl Constrained Bezier Patches,” 6th International Symposium on Biomedical Imaging : Macro to Nano, Boston, MA, June 2009, pp. 634-637.
T. McGraw, B. Sowers, “Hardware Accelerated Per-Texel Ambient Occlusion Mapping,” In Proc. 4th International Symposium on Visual Computing, Las Vegas, NV, December 1-3, 2008, pp. 1125-1134.
I. Yassine, T. McGraw, “A Subdivision Approach to Tensor Field Interpolation,” Workshop On Computational Diffusion MRI, September 2008, pp. 117-124.
T. McGraw, M. Nadar, “Fast Texture-Based Tensor Field Visualization for DT - MRI,” 4th IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2007, April 12, 2007, pp. 760-763.
S. Danda, T. McGraw, “A Comparison of the Bilateral Filter and TV-Norm Minimization for Image Denoising,” 4th IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2007, April 12, 2007, pp. 676-679.
T. McGraw, B.C. Vemuri, B. Yezierski, T. Mareci, “Segmentation of High Angular Resolution Diffusion MRI Modeled as a Field of von Mises - Fisher Mixtures”, 9th European Conference on Computer Vision, 2006, May 7, 2006, pp. 461 – 475.
T. McGraw, B.C. Vemuri, B. Yezierski, T. Mareci, “Von Mises - Fisher Mixture Model of the Diffusion ODF”, 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006, April 6, 2006, pp. 65 - 68.
T. McGraw, B. C. Vemuri, Z. Wang, Y. Chen, M. Rao, T. Mareci, “Line Integral Convolution for Visualization of Fiber Tract Maps from DTI,” Medical Image Computing and Computer Assisted Intervention,Tokyo, Japan, August 2002.
B.C. Vemuri, Y. Chen, Z. Wang, T. McGraw, T. Mareci, P. Reier, S. Blackband, “Automated Fiber Tractography from DTI and its Validation,” 2002 IEEE International Symposium on Biomedical Imaging, July 2002.
B. C. Vemuri, Y. Chen, M.Rao, T. McGraw, Z. Wang and T.Mareci, “Fiber Tract Mapping from Diffusion Tensor MRI,” Proceedings of the IEEE Workshop on Variational and Level Set Methods, July 2001, pp. 81-88.
Garcia, E., McGraw, T., Zernack, A., "Bodygraphe",
SIGGRAPH Asia 2016 Art Gallery, Macau, December, 2016
Funding and Gifts from
Eli Lilly and Co.
Lexica (Android), Schell Games, 2013.
Madden NFL 25 (X360, PS3, Xbox One, PS4), Electronic Arts - Tiburon, 2013
Madden NFL 13 (X360, PS3), Electronic Arts - Tiburon, 2012
Star Wars: Racer Revenge (PS2), Rainbow Studios, 2002
Siemens Corporate Research : Diffusion Tensor MRI processing and visualization, compressed sensing for MRI reconstruction
National Biometric Security Project : Face rendering for biometric testing
ACM, IEEE, IGDA