Data Driven Methods Engineering Professors in Global

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Sunmee Kim
University of Manitoba Canada
data-driven analytics
longitudinal data methods
statistical methods
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Kate Hong
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
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John Anderson
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
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Dave Touretzky
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
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Paul Mclachlan
Technical University of Denmark Denmark
data-driven decision making
modeling techniques
statistical methods
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Maysam Chamanzar
Carnegie Mellon University United States of America
computational methods
mathematical methods
statistical methods
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Dejiu Chen
KTH Royal Institute of Technology Sweden
data-driven engineering
model-driven engineering
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Shiva Tavallaey
KTH Royal Institute of Technology Sweden
data-driven methods
model-based methods
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Mark Goudswaard
University of Bristol United Kingdom
digital data-driven engineering
data-driven product development
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Amin Jalali
Stockholm University Sweden
data-driven techniques
model-based techniques
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Brock Tibert
Boston University United States of America
data engineering
data-driven product development
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Mikael Hedlind
KTH Royal Institute of Technology Sweden
model driven engineering
data models
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Ling Liu
Macquarie University Australia
data engineering
data management
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Sebastian Schelter
Technical University of Berlin Germany
data engineering
data management
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Robert Gracie
University of Waterloo Canada
data driven models
numerical methods
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Yuehaw Khoo
University of Chicago United States of America
computational data-driven techniques
neural-network methods
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Miroslaw Staron
Chalmers University of Technology Sweden
model driven software development
empirical methods in software engineering
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Yuehaw Khoo
University of Chicago United States of America
computational data-driven techniques
neural-network methods
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Kamran Paynabar
Georgia Institute of Technology United States of America
engineering-driven statistical modeling
statistical learning methods
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Miguel Paredes Maldonado
Edinburgh College of Art United Kingdom
data-driven mapping
design methods
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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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