Large Random Matrices Professors in Global

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Lei Ying
University of Michigan United States of America
large-scale graph mining
large-scale computing systems
large-scale communication systems
big data
stochastic networks
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Ivan Kryven
Utrecht University Netherlands
random matrices
randomized algorithms
random approximation algorithms
random graph representation
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Souvik Dhara
Georgia Institute of Technology United States of America
large-scale networks
matrices
random graphs
high-dimensional probability statistics
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Xiucai Ding
University of California, Davis United States of America
applied random matrix theory
large foundation models
randomized numerical linear algebra
high-dimensional statistics
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Antti Knowles
University of Geneva Switzerland
random matrices
random graphs
high-dimensional statistics
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Sepehr Assadi
University of Waterloo Canada
massive datasets
massively parallel computation
big data analysis
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Nicholas Cook
Duke University Singapore
large deviations theory
random hypergraphs
exponential random graph models
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Kavita Ramanan
Brown University United States of America
large deviations
high-dimensional probability
stochastic networks
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Elizaveta Rebrova
Princeton University United States of America
randomized algorithms
high-dimensional probability
non-asymptotic random matrix theory
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Jan Ambjørn
University of Copenhagen Denmark
matrix models
random surfaces
random paths
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Gunnar Martinsson
University of Texas at Austin United States of America
efficient algorithms for large data sets
randomized methods
structured matrix computations
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Steven Evans
University of California, Berkeley United States of America
random matrices
large random combinatorial structures
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Gérard Ben Arous
New York University United States of America
random matrices
large deviations
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Yingli Qin
University of Waterloo Canada
large dimensional covariance matrices
random matrix theory
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Marcus Michelen
Northwestern University United States of America
random matrices
random polynomials
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John Wheater
University of Oxford United Kingdom
random matrix models
large graph systems
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Mihai Nica
University of Guelph Canada
random matrices
deep neural networks
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Kurt Johansson
KTH Royal Institute of Technology Sweden
random matrices
stochastic models
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Babak Hassibi
California Institute of Technology United States of America
random matrices
high-dimensional statistics
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Yanrong Yang
Australian National University Australia
large dimensional random matrix theory
large panel data analysis
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Frederi Viens
Michigan State University United States of America
random matrices
random fields
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