John A. Saghri
Associate Professor
Phone: 805-756-1462
E-mail: jsaghri@calpoly.edu
Office: 20-303
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Curriculm Vitae Download
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Course Schedule - Fall 2009
| Course | Section | Date/Time | Room |
|---|---|---|---|
| Continuous-Time Signals and Systems | EE 228-01 |
Monday, Wednesday, Thursday, Friday
8:10 a.m.-9 a.m. |
Room: 186-C200 |
| Continuous-Time Signals and Systems | EE 228-02 |
Monday, Wednesday, Thursday, Friday
9:10 a.m.-10 a.m. |
Room: 186-C200 |
| Electric Circuit Analysis Laboratory II | EE 241-04 |
Thursday
12:10 p.m.-3 p.m. |
Room: 020-0149 |
Bio
John Saghri received his BS degree in electronic engineering from Cal Poly, San Luis Obispo, in 1973, his MS degree in electrical and computer engineering from Oregon State University in 1975, and his Ph.D. in electrical and Systems engineering from Rensselaer Polytechnic Institute, Troy, New York, in 1979. He joined the signal processing group of the Aerospace Corporation, El Segundo, California, In 1979. In 1988, he joined Lockheed Martin Palo Alto Research Laboratories as a senior scientist in the Electronic Sciences Laboratory. In September 2000, he joined the faculty of electrical and computer engineering at Cal Poly, San Luis Obispo, California. Dr. Saghri's research interests are in remote sensing, digital signal/image processing, bandwidth compression, Automatic Target Recognition, and Computer Vision. His publication record includes over fifty papers and several textbook chapter contributions. He has been supervising sponsored student research projects in remote sensing for over a decade. His professional community services include technical reviewing for several journals and conference organization activities. Dr. Saghri is a fellow of the International Society of Optical Engineering (SPIE) and a senior member of the IEEE.
Education
BS Electronic Engr., Cal Poly San Luis Obispo, '73 MS Electerical & Computer Engr., Oregon State University, '75 PhD Electrical & System Engr., Rensselaer Polytechnic Inst., 79
Teaching and Research Interests
Digital Image & Signal Processing
Remote Sensing
Computer Vision & Pattern Recognition
Bandwidth Compression & Coding
