Theory Driven Methodologies Professors in Global

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Bartolomeo Stellato
Princeton University United States of America
data-driven computational tools
machine learning optimization data-driven algorithms
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Ying Sun
University of Copenhagen Denmark
data-driven decision making
methodology development
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Paul Sabourin
University of Montreal Canada
qualitative methodology
methodological approaches in sociology
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Peter Mcdonald
University of Wisconsin–Madison United States of America
queer methodologies
feminist methodologies
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Paul Mclachlan
Technical University of Denmark Denmark
data-driven decision making
statistical methods
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Bart Lameijer
University of Amsterdam Netherlands
data-driven decision making
statistical methods
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Kjeld Schmidt
Copenhagen Business School Denmark
data-driven decision making
management theory
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Rosemary Reilly
Concordia University Canada
arts-based research methodologies
qualitative research methodologies
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Andreas Pfenning
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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John Anderson
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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Maysam Chamanzar
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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Kate Hong
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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Mike Tarr
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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Dave Touretzky
Carnegie Mellon University United States of America
mathematical methods
statistical methods
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Jacinto Ulloa
University of Michigan United States of America
data-driven computing
variational methods
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Maude Plante
Laval University Canada
sociological methodology
management theory
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Nooshin Salari
University of Alberta Canada
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data-driven decision-making
data-driven optimization
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Northwestern University United States of America
interpretive methods
experimental methods
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Stefano Benincasa
University of Vienna Austria
empirical methods
experimental methods
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Ewart Thomas
Stanford University United States of America
theoretical experimental analyses
statistical methods
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Patrik Rydén
Umeå University Sweden
data-driven optimization
statistical methods
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