Highly Scalable Algorithms Professors in Global

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Nicole Wein
University of Michigan United States of America
dynamic algorithms
online algorithms
distributed algorithms
parameterized algorithms
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Dimosthenis Pasadakis
Università della Svizzera italiana Switzerland
high-dimensional data analysis
numerical algorithms
extreme-scale computing
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Gerard Gorman
Imperial College London United Kingdom
high-performance computing
adaptive computational algorithms
multi-scale modeling
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Gara Pruesse
Vancouver Island University Canada
optimization algorithms
approximation algorithms
discrete algorithms
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Srinivasa Gummidi
University of Southern Denmark Denmark
optimization algorithms
algorithms
online algorithms
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Marc Renault
University of Wisconsin United States of America
approximation algorithms
online algorithms
search algorithms
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Debarati Das
Pennsylvania State University United States of America
clustering algorithms
approximation algorithms
string algorithms
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Olaf Schenk
Università della Svizzera italiana Switzerland
high-performance computing
multicore algorithms
manycore algorithms
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George Papavassilopoulos
University of Southern California United States of America
optimization algorithms
genetic algorithms
parallel algorithms
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Aaron Bernstein
New York University Tandon School of Engineering United States of America
approximation algorithms
dynamic algorithms
sublinear algorithms
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Nima Anari
Stanford University United States of America
algorithms
sampling algorithms
parallel algorithms
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Suchuan Dong
Purdue University United States of America
high-order numerical methods
high performance computing
algorithms for dynamic simulations
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Debdeep Pati
University of Wisconsin–Madison United States of America
high-dimensional applications
real-time tracking algorithms
high dimensional network analysis
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Souvik Dhara
Georgia Institute of Technology United States of America
large-scale networks
high-dimensional probability statistics
inference algorithms
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Sham Kakade
Harvard University United States of America
scalable optimization algorithms
large-scale learning systems
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Xiucai Ding
University of California, Davis United States of America
scalable computation
high-dimensional statistics
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
stochastic algorithms
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Christopher Musco
New York University Tandon School of Engineering United States of America
scalable machine learning
randomized algorithms
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Moses Charikar
Stanford University United States of America
efficient algorithmic techniques for processing high-dimensional data sets
efficient algorithms for computational problems in high-dimensional statistics
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Bernd Dammann
Technical University of Denmark Denmark
large scale computations
high-performance computing
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
stochastic algorithms
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