The takeoff of Sputnik in 1957, fittingly enough, also launched Louis Scharf’s 46-year career in engineering. A teenager at the time of the Soviet Union’s satellite launch, Scharf witnessed the start of the space age and was enthusiastic about pursuing a career in engineering.
“I was caught up in the generation of young people following the Sputnik launch. We were swept into mathematics, science, and engineering in the early days of the space race,” Scharf said.
Scharf is one of six UW engineering alums to be honored with a UW College of Engineering Diamond Award. Scharf is recognized specifically for distinguished achievements in academia.
“I was surprised and gratified,” Scharf said about receiving the award. “The UW is where I was educated, so this does have a special significance.”
Born and raised in Longview, Washington, Scharf moved to Seattle in 1960 to attend UW, where he earned his B.S, M.S, and Ph.D. degrees in Electrical Engineering. He first became interested in signal processing after taking courses in detection and estimation theory from his Ph.D. advisor, Dean Lytle.
“I was captivated by signal processing and communication theory and Professor Lytle encouraged my interest,” Scharf said.
Following his Ph.D. in 1969, Scharf taught at Colorado State University, University of Rhode Island, and the University of Colorado. He is currently Research Professor of Mathematics and Emeritus Professor of Electrical and Computer Engineering at Colorado State University, Fort Collins.
During his 46-year career, Scharf’s research has been focused on statistical signal processing, as it applies to radar, sonar, imaging and wireless communication. He is best known for his work on modal analysis, invariance theories for subspace signal processing, and for his recent work on coherence statistics for space-time signal processing. Scharf’s work on modal analysis has been applied to mode tracking in power systems, and his work on matched and adaptive subspace detectors has been applied in radar, sonar and hyperspectral imaging. He is the author of two graduate-level texts on statistical signal processing.
The secret to his success, Scharf says, is his collaboration with students and colleagues, totaling more than 150 from 25 different countries. He has strived to place his research in the context of technologies that are addressed to topical engineering problems.
Scharf’s advice to students is to address problems at their most fundamental level, abstract them into a framework that illuminates their essence, and solve them. In other words, solve problems the way engineers solve problems.