Randomized Sensing Methods Professors in Global

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Nicholas Makris
Massachusetts Institute of Technology United States of America
remote sensing
statistical estimation sensing
physics sensing
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Andrew Mason
Michigan State University United States of America
neural sensing
environmental sensing
biochemical sensing
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Caleb Pomeroy
University of Toronto Canada
statistical methods
experimental methods
computational methods
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Thees Spreckelsen
University of Glasgow United Kingdom
experimental methods
research methods
survey research methods
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Ivan Kryven
Utrecht University Netherlands
randomized algorithms
numerical methods
random approximation algorithms
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John Anderson
Carnegie Mellon University United States of America
statistical methods
computational methods
behavioral methods
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Sreeraman Rajan
Carleton University Canada
compressive sensing
sensors
sensor systems
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Felix Krahmer
Technical University of Munich Germany
randomized sensing methods
compressed sensing
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Remko Uijlenhoet
Delft University of Technology Netherlands
remote sensing techniques
opportunistic sensing
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Pulkit Grover
Carnegie Mellon University United States of America
sensing strategies
neural sensing
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Kassel Hingee
Australian National University Australia
remote sensing
statistical methods
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Tara Boroushaki
Yale University United States of America
sensing technologies
wireless sensing
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Tianxing Li
Michigan State University United States of America
human sensing systems
mobile sensing
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Lei Zou
Texas A&M University United States of America
remote sensing
social sensing
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Marisa Casillas
University of Chicago United States of America
observational methods
experimental methods
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Justin Chan
Carnegie Mellon University United States of America
mobile sensing
environmental sensing
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Jesper Hinrich
Technical University of Denmark Denmark
probabilistic methods
tensor methods
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John Albertson
Cornell University Netherlands
remote sensing
sensors
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Chunyuan Diao
University of Illinois United States of America
remote sensing
computational remote sensing
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Leif Eriksson
Chalmers University of Technology Sweden
remote sensing
radar remote sensing
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Chris Backhouse
University of Waterloo Canada
remote sensing
sensors
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