Ultrasonic Sensing Methods Professors in Global

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Alison Barth
Carnegie Mellon University United States of America
anatomical methods
statistical methods
molecular methods
physiological methods
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Mayank Goel
Carnegie Mellon University United States of America
sensing systems
health sensing technologies
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Paul Arora
University of Toronto Canada
statistical methods
causal inference methods
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Kassel Hingee
Australian National University Australia
statistical methods
remote sensing
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Truong Vo-van
Concordia University Canada
optical characterization methods
sensing devices based on plasmonic properties
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Michael Szafron
University of Saskatchewan Canada
statistical methods
biostatistical methods
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Professorship Biometry Molecular Medicine
Ludwig Maximilian University of Munich Germany
statistical methods
biostatistical methods
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Paul Mclachlan
Technical University of Denmark Denmark
statistical methods
modeling techniques
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Kate Hong
Carnegie Mellon University United States of America
anatomical methods
statistical methods
physiological methods
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Ginny Catania
University of Texas at Austin United States of America
radar methods
gps methods
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Dongzhu Liu
University of Glasgow United Kingdom
multimodal sensing
integrated sensing
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Allison Enright
University of New Brunswick Canada
geophysical methods
passive sensor-based approaches
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Viacheslav Adamchuk
McGill University Canada
sensor systems
soil and plant sensing technologies
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Hongquan Zhang
University of Alberta Canada
ultrasensitive assays
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Tong Yu
University of Alberta Canada
microsensor techniques
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Raffaella Righetti
Texas A&M University United States of America
ultrasonic imaging
ultrasound methods for imaging mechanical behavior of soft tissues
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Yongkang Xue
University of California Los Angeles United States of America
remote sensing methodology
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Kelvin Jones
University of Alberta Canada
electrodiagnostic methods
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J Okeme
McMaster University Canada
modelling methods
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Mayank Goel
Carnegie Mellon University United States of America
sensing systems
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Suranjan Panigrahi
Purdue University United States of America
sensing systems
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