Concurrent Data Structures Professors in Global

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Sean Chester
Aarhus University Denmark
data structures
parallel algorithms
massive datasets
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Danupon Na Nongkai
KTH Royal Institute of Technology Sweden
data structures
data stream algorithms
theoretical databases
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Bengt Jonsson
Uppsala University Sweden
verification of concurrent systems
semantics of concurrent systems
real-time distributed systems
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Martin Schulz
Technical University of Munich Germany
parallel distributed architectures
parallel programming paradigms
quantum computing architectures
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Shamkant Navathe
Georgia Institute of Technology United States of America
data mining
data integration
data modeling
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Franco Preparata
Brown University United States of America
data structures
parallel algorithms
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Norbert Zeh
Dalhousie University Canada
data structures
parallel algorithms
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Doron Nussbaum
Carleton University Canada
data structures
parallel computing
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Doron Nussbaum
Carleton University Canada
data structures
parallel computing
parallel distributed computing
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Solon Pissis
Vrije Universiteit Amsterdam Netherlands
data structures
data mining
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Pankaj Agarwal
Duke University Singapore
data structures
data mining
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Mo Chen
Simon Fraser University Canada
data structures
data mining
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Faith Ellen
University of Toronto Canada
data structures
sequential models
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Marc Schweitzer
University of Bonn Germany
spatial data structures
parallel computing
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Charlie Garrod
Carnegie Mellon University United States of America
data structures
distributed database systems
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Gustavo Rodriguez-rivera
Purdue University United States of America
data structures
real-time systems
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Awos Kanan
University of Victoria Canada
parallel algorithms
parallel computing
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Ananth Grama
Purdue University United States of America
parallel computing
distributed computing architectures
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Elli Anastasiadi
Aalborg University Denmark
concurrent programs
parallel programs
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Kaizhong Zhang
Western University Canada
sequential parallel algorithms
data mining
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Ian Foster
University of Chicago United States of America
parallel computing
data-intensive computing
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