Cluster Computing Professors in Global

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Matias Carrasco Kind
University of Illinois United States of America
clustering
scientific computing
machine learning
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Lyle Ungar
University of Pennsylvania United States of America
clustering
machine learning
distributed scheduling
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Jinjun Xiong
University of Illinois United States of America
cognitive computing
machine learning
distributed computing storage systems
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Mara Kirdani-ryan
University of Washington United States of America
critical computing
postsecondary computing
neurodivergence computing
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Bipin Rajendran
King's College London United Kingdom
stochastic computing
intelligent computing systems
event-driven computing
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Justin Wan
University of Waterloo Canada
scientific computing
numerical computation
machine learning
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Zbigniew Leyk
Texas A&M University United States of America
scientific computing
machine learning
high-performance parallel computing
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Muhammad Shafique
New York University Tandon School of Engineering United States of America
robust computing
brain-inspired computing
energy-efficient computing
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Vladimir Vlassov
KTH Royal Institute of Technology Sweden
cloud distributed computing
machine learning
large-scale distributed systems
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Peter Beerel
University of Southern California United States of America
machine learning
energy-efficient computing
sustainable computing
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Yi Ding
Purdue University United States of America
machine learning
computer systems
sustainable computing
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Pui-kuen Yeung
Georgia Institute of Technology United States of America
massively parallel computation
heterogeneous computing
computational algorithms
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Oktay Günlük
Georgia Institute of Technology United States of America
clustering
machine learning
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Sara Wade
University of Edinburgh United Kingdom
clustering
machine learning
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Sara Wade
University of Edinburgh United Kingdom
clustering
machine learning
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Mahmoud El-sakka
Western University Canada
clustering
machine learning
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Rebecka Jörnsten
Chalmers University of Technology Sweden
clustering
machine learning
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Atsuto Maki
KTH Royal Institute of Technology Sweden
clustering
machine learning
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Gal Mishne
University of California, San Diego United States of America
clustering
machine learning
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Ashish Dutt
Monash University Australia
clustering
mixed data clustering
machine learning
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Sharareh Akbarian
University of New South Wales Australia
clustering
machine learning
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