High Dimensional Omics Data Professors in Global

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Yue Cao
University of Sydney Australia
high-dimensional omics data
single-cell multi-omics data
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Benoit Liquet-weiland
Macquarie University Australia
high dimensional data analysis
omics data
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Christophe Giraud
Cornell Bowers University United States of America
omics data
high-dimensional statistics
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Zihuai He
Stanford University United States of America
high-dimensional data analysis
integrative analysis of omics data
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Zihuai University
Stanford University United States of America
high dimensional data analysis
integrative analysis of omics data
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Kathryn Roeder
Carnegie Mellon University United States of America
high dimensional statistics
multi-omic data
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Bareng Nonyane
Johns Hopkins University United States of America
high dimensional data
multilevel data
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Professorship Biometry Molecular Medicine
Ludwig Maximilian University of Munich Germany
high-dimensional data
high-throughput molecular data
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James Nichols
Australian National University Australia
high dimensional statistics
high dimensional approximation theory
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Lu Xia
Michigan State University United States of America
high-dimensional statistics
multi-omics data analysis
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Dan Nicolae
University of Chicago United States of America
integration of omics data
high-dimensional statistical inference
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Lingzhou Xue
Pennsylvania State University United States of America
high-dimensional data
large-scale optimization
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Pingzhao Hu
University of Manitoba Canada
visual analytics algorithms for omics data
integrative analysis frameworks for omics data
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Danna Zhang
University of California, San Diego United States of America
high-dimensional time series
high-order statistics
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Debdeep Pati
University of Wisconsin–Madison United States of America
high dimensional network analysis
high-dimensional applications
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Xuewen Lu
University of Calgary Canada
high-dimensional data analysis
big data analysis
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Dachuan Chen
Singapore Management University Singapore
high dimensional statistics
high frequency econometrics
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Tatjana Pavlenko
Uppsala University Sweden
high-dimensional problems
large-scale biomedical data
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Kaixin Liu
London School of Economics and Political Science United Kingdom
high-dimensional time series
high-frequency time series
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Guang Cheng
Purdue University United States of America
high dimensional statistical inferences
big data
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Yingli Qin
University of Waterloo Canada
high-dimensional data applications
large dimensional covariance matrices
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