Fairness And Equity In Machine Learning Professors in Global

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Shai Ben-david
University of Waterloo Canada
fairness in machine learning
reliability in machine learning
machine learning
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Gjergji Kasneci
Technical University of Munich Germany
fairness in machine learning
machine learning
algorithm transparency
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Nisarg Shah
University of Toronto Canada
algorithmic fairness
fair division
machine learning
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Rumi Chunara
New York University United States of America
algorithmic fairness
inequity technology
machine learning
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Samantha Hatzenbeler
University of Washington United States of America
racial equity
gender equity
economic equity
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Aditya Vashistha
Cornell University Netherlands
contextual equity
information equity
representational equity
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Amir Payberah
KTH Royal Institute of Technology Sweden
justice in computing
educational equity
machine learning
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Aaron Roth
University of Pennsylvania United States of America
fairness in machine learning
algorithmic fairness
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Changjian Shui
University of Ottawa Canada
fairness and equity in machine learning
machine learning
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Siavash Arjomand Bigdeli
Technical University of Denmark Denmark
algorithmic fairness
bias fairness
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Elaheh Fata
Queen's University Canada
fairness in machine learning
machine learning
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Aaron Roth
University of Pennsylvania United States of America
fairness in machine learning
machine learning
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Aaron Roth
University of Pennsylvania United States of America
fairness in machine learning
machine learning
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Arvind Narayanan
Princeton University United States of America
fairness in machine learning
machine learning
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Seth Neel
Harvard University United States of America
fairness in machine learning
machine learning
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Richard Zemel
University of Toronto Canada
fairness in machine learning
machine learning
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Alan Tsang
Carleton University Canada
algorithmic fairness
fair allocation
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Nour Ghadban
University of Glasgow United Kingdom
fairness-aware machine learning
ai healthcare equity
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Arvind Narayanan
Princeton University United States of America
algorithms and fairness
machine learning bias
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Swati Kumari
Radboud University Netherlands
fairness algorithms
gender equity
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Brent Mittelstadt
University of Oxford United Kingdom
fairness
transparency in machine learning
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