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Ray Ptucha

Ray Ptucha
Assistant Professor

Phone: 585-475-2623
Office: GLE-3441

Ray is an assistant professor in the Computer Engineering Department, Rochester Institute of Technology. Ray received a B.S. degree in Computer Science and a B.S. degree Electrical Engineering, both from the State University of New York at Buffalo. He received a M.S. degree in Imaging Science and a Ph.D. degree in Computer Science, both from Rochester Institute of Technology.

Prior to joining RIT, Ray was a research scientist with Eastman Kodak Company for 20 years where he worked on computational imaging algorithms. He has over two dozen publications and holds 16 U.S. patents with an additional 32 patent applications on file. Ray is Secretary of the IEEE Rochester Section, serves as reviewer for Journal of Electronic Imaging, Journal of Image Science and Technology, and Transactions on Affective Computing, and is on the Technical Committee for the 2014 IEEE International Conference on Multimedia & Expo. His research interests include machine learning, computer vision, and robotics.

Selected Publications

  • R.W. Ptucha, A. Savakis, “LGE-KSVD:  Robust Sparse Representation Classification”, IEEE Transactions on Image Processing, Volume 23, Issue 4, 2014.
  • R.W. Ptucha, A. Savakis, “Manifold Based Sparse Representation for Facial Understanding in Natural Images”, Image and Vision Computing, vol. 31, pp. 365-378, 2013.
  • R.W. Ptucha, A. Savakis, “Facial Expression Recognition”, IGI Global Encyclopedia of Information Science and Technology, 3rd Edition, 2013.
  • Savakis, R. Rudra, R.W. Ptucha, “Gesture Control Using Active Difference Signatures and Sparse Learning”, Proceedings of International Conference on Pattern Recognition, Stockholm, Sweden, 2014.
  • R.W. Ptucha, A. Savakis, “LGE-KSVD: Flexible Dictionary Learning for Optimized Sparse Representation Classification”, Proceedings of AMFG Workshop, Computer Vision and Pattern Recognition, Portland, OR, 2013.
  • R.W. Ptucha, A. Savakis, “Joint Optimization of Manifold Learning and Sparse Representations”, Proceedings of Automatic Face and Gesture Recognition, Shanghai, China, 2013.
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