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Jeff is an applied harmonic analyst studying composite dilation wavelets and compressed sensing. With applications to digital signal processing, these fields explore the mathematics of efficient representation and acquisition of signals. This has led to excursions in probability, high dimensional geometry, and random matrix theory. His research in compressed sensing, matrix completion, and algorithms for high performance computing with graphical processing units has been supported by the National Science Foundation.

Jeff has fond memories of hobbies. Occasionally, he goes for a run and thinks about what it would be like to have time to play golf.