Large Scale Observational Data Professors in Global

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George Voneiff
Texas A&M University United States of America
large datasets
large-scale production data analysis
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Greg Ganger
Carnegie Mellon University United States of America
large-scale machine learning
big data
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Krishna Narayanan
Texas A&M University United States of America
big data
large language models
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John Paisley
Columbia University United States of America
big data
data analysis
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Neil Davis
Technical University of Denmark Denmark
big data
data analysis
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Bjarne Ersbøll
Technical University of Denmark Denmark
big data
data analysis
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Sieun Lee
University of Nottingham United Kingdom
big data
data analysis
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Mohammad Ghasempour
Umeå University Sweden
big data
statistical models
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Claudia Solis Lemus
University of Wisconsin–Madison United States of America
big data
statistical models
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Pascal Vincent
University of Montreal Canada
big data
statistical models
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Yudong Chen
University of Warwick United Kingdom
large language models
high-dimensional statistics
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Yuki Shiraito
University of Michigan United States of America
large-scale computational algorithms
data analysis
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Guang Cheng
Purdue University United States of America
big data
high dimensional statistical inferences
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Andriy Miranskyy
Toronto Metropolitan University Canada
big data
large software systems
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Andrew Loza
Yale University United States of America
real-world data
statistical deep learning
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Anna Wedenborg
Technical University of Denmark Denmark
high-dimensional datasets
data analysis
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Shmuel Weinberger
University of Chicago United States of America
large scale geometry
large scale metric spaces
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Evangelos Kontopantelis
University of Manchester United Kingdom
observational studies
longitudinal data modelling
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Maria Kateri
RWTH Aachen University Germany
high-dimensional statistics
categorical data
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Clara Sanchez-izquierdo Lozano
University of Edinburgh United Kingdom
qualitative data
quantitative data
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Marc Wouters
University of Amsterdam Netherlands
qualitative data
quantitative data
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