Welcome!
This is the website of
JARVIS HAUPT. I joined the Department
of Electrical and
Computer Engineering at the University of Minnesota as an
Assistant Professor in August
2010. Prior to that, I was a Postdoctoral
Research Associate
in the DSP
group
at Rice
University. My CV is available here.
My research interests generally include statistical signal processing and learning theory, compressed sensing, and adaptive sampling techniques, with applications in communications, networks, remote sensing, and imaging.
Currently, my research focus is DISTILLED SENSING, a multi-step adaptive sampling and refinement procedure for recovery of sparse signals in noise. Our work in this area shows that dramatic improvements 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 Eindhoven University of Technology and Robert Nowak at the University of Wisconsin, and most recently with Richard Baraniuk at Rice University.
My research interests generally include statistical signal processing and learning theory, compressed sensing, and adaptive sampling techniques, with applications in communications, networks, remote sensing, and imaging.
Currently, my research focus is DISTILLED SENSING, a multi-step adaptive sampling and refinement procedure for recovery of sparse signals in noise. Our work in this area shows that dramatic improvements 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 Eindhoven University of Technology and Robert Nowak at the University of Wisconsin, and most recently with Richard Baraniuk at Rice University.