Multi Modal Sensing Learning Professors in Global

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Nicholas Makris
Massachusetts Institute of Technology United States of America
physics sensing
statistical estimation sensing
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Haim Sompolinsky
Harvard University United States of America
sensory processing
neural learning
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Katerina Papadaki
London School of Economics and Political Science United Kingdom
multiagent reinforcement learning
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Srikant Rangaraju
Yale School of Medicine United States of America
multi-omics modalities
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Valery Sheverev
New York University Tandon School of Engineering United States of America
micro-optical sensing
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Joydeep Ghosh
University of Texas at Austin United States of America
adaptive multi-learner systems
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Chris Freeman
University of Southampton United Kingdom
motor learning control
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Elizabeth Simmons-o'neill
University of Washington United States of America
multilingual teaching and learning
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Khalegh Barati
University of New South Wales Australia
data sensing
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Dong Zhao
Michigan State University United States of America
data sensing
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Fathy Ismail
University of Waterloo Canada
experimental modal analysis
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Yen-hsi Tsai
University of Texas at Austin United States of America
multiscale modeling
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Aleksander Czekanski
York University Canada
multiscale modeling
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William Curtin
Brown University United States of America
multiscale modeling
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Markus Buehler
Massachusetts Institute of Technology United States of America
multiscale modeling
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Raúl Radovitzky
Massachusetts Institute of Technology United States of America
multiscale modeling
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Arash Noshadravan
Texas A&M University United States of America
multiscale modeling
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Jianing Li
Purdue University United States of America
multiscale modeling
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Huan Lei
Michigan State University United States of America
multiscale modeling
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Artem Korobenko
University of Calgary Canada
multiscale modeling
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Talid Sinno
University of Pennsylvania United States of America
multiscale modeling
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