Marios S. Pattichis
Computer Engineering Program Chair
Ph.D., Computer Engineering, The University of Texas at Austin, 1998
M.S.E., Electrical Engineering, The University of Texas at Austin, 1993
B.A. (high honors), Mathematics, The University of Texas at Austin, 1991
B.Sc. (high honors and special honors), Computer Sciences (minor in EE),
The University of Texas at Austin, 1991
Dr. Pattichis is director of ECE’s Image & Video Processing and Communication Lab. The lab interests are summarized into four broad areas:
Mathematical and statistical representations for image and video processing:
The goal here is to develop general models and methods that can be applied to a wide-range of image and video processing applications. The current focus is on the development of multi-objective and constrained optimization methods, and adaptive multi-scale AM-FM models.
Biomedical and space image processing methods and applications:
In this inter-disciplinary effort, the goal is to develop new or adapt existing image processing methods that can be successfully applied to a wide range of clinical and space imaging applications. In terms of methods, the current focus is on the development of spectral-methods for robust motion estimation, the development of high-efficiency video coding (HEVC) metrics and algorithms for biomedical video compression, and adaptive multi-scale AM-FM methods for computer aided diagnosis (CAD). In terms of applications, the methods have been applied to atherosclerotic plaque ultrasound motion analysis, stroke image analysis, multiple-sclerosis (MRI), diabetic retinopathy screening using fundus images. Emerging applications are in brain imaging (fMRI, MRI) and solar image analysis.
Dynamically reconfigurable systems for image processing:
The goal of this research is to develop dynamically-reconfigurable computing architectures that can be used for satisfying real-time constraints on power, performance, and performance. Previous research in this area focused on the development of dynamic arithmetic and high-speed dynamic partial reconfiguration. The current focus is on the development of dynamically reconfigurable compression (HEVC), video image analysis, and packet-based parallel video processing.
Research in teaching digital image and video processing to middle school students from under-represented groups:
In this inter-disciplinary effort, the goal is to develop an out-of-school curriculum for teaching digital image and video processing to middle-school students. The emphasis here is to integrate middle-school mathematics with image processing and to investigate what keeps students engaged and excited. The curriculum was implemented for the first time in the Summer of 2012.
Dr. Pattichis is currently an Associate Editor for IEEE Transactions on Image Processing. He has served as an Associate Editor for IEEE Transactions on Industrial Informatics, and a Guest Associate Editor for IEEE Transactions on Information Technology in Biomedicine.
For his undergraduate studies (1987-1991), he was awarded a full scholarship from the Cyprus America Scholarship Program to double-major in Computer Sciences and Mathematics (with a minor in Electrical Engineering). In 2003, he was recognized by Xilinx Corporation for his development of the digital logic design labs at UNM. He also received UNM ECE’s 2003 Teacher of the Year award and the 2006 UNM School of Engineering Harrison Faculty Excellence Award. In 2006, he received a best paper award from the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI06). He received the 2010 Silver Zia award from the Santa Fe Public School system. In 2011, he received an AFRL Summer Faculty fellowship. He is also a Senior member of IEEE and holds a joint appointment with UNM’s Department of Radiology.
J1.    Llamocca, D. and Pattichis, M.S., “A Dynamically Reconfigurable Pixel Processor System Based on Power/Energy-Performance-Accuracy Optimization,” in press, IEEE Transactions on Circuits and Systems for Video Technology.
J2.    Jeromin, O.M. and Pattichis, M.S., “Spectral Statistical Interpolation Models of Magnitude and Phase Spectra for the Reconstruction of Satellite Imagery,” IEEE Transactions on Geosciences and Remote Sensing, vol. 50, no. 10, pp. 3678-3692, Oct. 2012.
J3.    Panayides, A., Pattichis, M.S., Pattichis, C.S., Loizou, C.P., Patziaris, M., and Pitsillides, A., “Atherosclerotic Plaque Ultrasound Video Encoding, Wireless Transmission, and Quality Assessment Using H.264,” IEEE Transactions on Information Technology in Biomedicine, vol. 15, no. 3, pp. 387-397, May 2011, PMID: 21233053.
J4.    Murray, V., Rodriguez, P. and Pattichis, M.S., “Multi-scale AM-FM Demodulation and Reconstruction Methods with Improved Accuracy,” IEEE Transactions on Image Processing, vol 19, no. 2, pp. 1138-1152, May 2010, PMID: 20071260.
J5.    Agurto, C., Murray, V., Barriga, E., Murillo, S., Pattichis, M.S., Davis, H., Russell, S.R., Abramoff, M.D., and Soliz, P., “Multiscale AM-FM Methods for Diabetic Retinopathy Lesion Detection,” IEEE Transactions on Medical Imaging, vol. 29, no. 2, pp. 502-512, February 2010, PMID: 20129850.