Localization Methods Professors in Global

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Caleb Pomeroy
University of Toronto Canada
statistical methods
computational methods
experimental methods
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John Anderson
Carnegie Mellon University United States of America
statistical methods
mathematical methods
computational methods
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Dave Touretzky
Carnegie Mellon University United States of America
statistical methods
mathematical methods
computational methods
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Thees Spreckelsen
University of Glasgow United Kingdom
research methods
experimental methods
survey research methods
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Maurice Fallon
University of Oxford United Kingdom
localization
probabilistic methods
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Aboelmagd Noureldin
Queen's University Canada
localization
wireless positioning
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Edmond Jonckheere
University of Southern California United States of America
geographical localization
coarse geometry methods
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Harold Kushner
Brown University United States of America
approximation methods
optimization methods
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Stephen Haben
University of Oxford United Kingdom
clustering methods
optimization methods
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Thea Engstrøm Vejlin
Aarhus University Denmark
visualization methods
spatial techniques
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Daniel Bloch
Stanford University United States of America
statistical methods
research methods
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Carsten Rockstuhl
Karlsruhe Institute of Technology Germany
light localization
numerical methods
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Wendy Chan
University of Pennsylvania United States of America
statistical methods
partial identification methods
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Ozan Kuru
National University of Singapore Singapore
survey methods
experimental methods
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Wei Chen
University of Pittsburgh United States of America
statistical methods
computational methods
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Tim Burness
University of Bristol United Kingdom
probabilistic methods
computational methods
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Kosuke Imai
Harvard University United States of America
statistical methods
survey methodology
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Eli Ben-michael
Carnegie Mellon University United States of America
statistical methods
computational methods
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Bernard Baffour
Australian National University Australia
statistical methods
survey methodology
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Karen Mckinnon
University of California Los Angeles United States of America
statistical methods
computational methods
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Mike Tarr
Carnegie Mellon University United States of America
statistical methods
mathematical methods
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