Welcome!
This is the website of
JARVIS HAUPT, Postdoctoral Research Associate in the DSP group
at Rice
University. My research interests include
statistical signal processing and learning theory, compressed sensing,
and adaptive sampling techniques, with applications in communications,
networks,
remote sensing, and imaging.
My current research focus is DISTILLED SENSING, a multi-step adaptive sampling and refinement procedure for recovery of sparse signals in noise. Our work shows that dramatic improvements that are achievable using adaptivity in sampling, relative to the best methods based on non-adaptive sampling -- for example, adaptivity enables reliable recovery (detection and estimation) of sparse signals in otherwise prohibitively-low SNR regimes. This is joint work with Rui Castro at Columbia University and Robert Nowak at the University of Wisconsin.
Our full-length Distilled Sensing paper is now available!
My current research focus is DISTILLED SENSING, a multi-step adaptive sampling and refinement procedure for recovery of sparse signals in noise. Our work shows that dramatic improvements that are achievable using adaptivity in sampling, relative to the best methods based on non-adaptive sampling -- for example, adaptivity enables reliable recovery (detection and estimation) of sparse signals in otherwise prohibitively-low SNR regimes. This is joint work with Rui Castro at Columbia University and Robert Nowak at the University of Wisconsin.
Our full-length Distilled Sensing paper is now available!