John A. Saghri

Associate Professor

Phone: 805-756-1462
E-mail: jsaghri@calpoly.edu
Office: 20-303
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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

 

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