Fairness In Data Professors in Global

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Brent Mittelstadt
University of Oxford United Kingdom
fairness
transparency in machine learning
data ethics
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Gjergji Kasneci
Technical University of Munich Germany
fairness in machine learning
algorithm transparency
responsible data science
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Professor
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Arvind Narayanan
Harvard University United States of America
algorithmic fairness
data privacy
web transparency
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Professor
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Melanie Morrison
University of Saskatchewan Canada
inequalities
data mining
big data
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Professor
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Tracey Lauriault
University of Ottawa Canada
data ethics
equity
data society
data literacy
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Professor
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Tracey Lauriault
Carleton University Canada
open data
data governance
big data
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Professor
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Aaron Roth
University of Pennsylvania United States of America
fairness in machine learning
algorithmic fairness
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Professor
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Siavash Arjomand Bigdeli
Technical University of Denmark Denmark
bias fairness
algorithmic fairness
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Professor
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Ricardo Usbeck
Leuphana University Lüneburg Germany
fair data
data extraction
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Alan Tsang
Carleton University Canada
algorithmic fairness
fair allocation
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Nisarg Shah
University of Toronto Canada
algorithmic fairness
fair division
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Katherine Smith
University of Manchester United Kingdom
fairness
equality
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Shaul Shalvi
University of Amsterdam Netherlands
fairness
equality
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Leanne Son Hing
University of Guelph Canada
fairness
inequality
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Professor
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Alan Said
University of Gothenburg Sweden
fairness in ai
transparency in ai
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Olga Russakovsky
Princeton University United States of America
fairness in ai
transparency in ai
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Anh Luong
Warwick Business School United Kingdom
fairness in algorithmic decision-making
data visualization
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Professor
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Jamie Tucker-foltz
Yale University United States of America
fairness
equity
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Laurie Barclay
University of Guelph Canada
fairness
equity
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Li Cheng
Michigan State University United States of America
fairness
equity
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Aleksandra Korolova
Princeton University United States of America
algorithmic fairness
data privacy
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