Algorithmic Fairness Professors in Global

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Avrim Blum
Toyota Technological Institute Chicago United States of America
algorithmic fairness
algorithmic game theory
online algorithms
machine learning
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Gjergji Kasneci
Technical University of Munich Germany
fairness in machine learning
algorithm transparency
algorithm robustness
machine learning
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Arvind Narayanan
Princeton University United States of America
fairness in machine learning
algorithmic amplification
artificial intelligence
machine learning
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Alan Said
University of Gothenburg Sweden
fairness in ai
artificial intelligence
machine learning
transparency in ai
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Hong Shen
Carnegie Mellon University United States of America
bias and fairness
algorithmic systems
artificial intelligence
machine learning
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Kevin Leyton-brown
University of British Columbia Canada
algorithmic game theory
algorithms
artificial intelligence
machine learning
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Michael Kearns
University of Pennsylvania United States of America
algorithmic game theory
algorithmic trading
artificial intelligence
machine learning
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Michael Kearns
University of Pennsylvania United States of America
algorithmic game theory
algorithmic trading
artificial intelligence
machine learning
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Mohammad Salavatipour
University of Alberta Canada
algorithmics
approximation algorithms
algorithmic graph theory
probabilistic randomized algorithms
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Marc Renault
University of Wisconsin United States of America
search algorithms
approximation algorithms
analysis of algorithms
online algorithms
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Susanne Albers
Technical University of Munich Germany
algorithmic game theory
algorithm engineering
efficient algorithms
online approximation algorithms
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University of Sherbrooke Canada
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algorithms
artificial intelligence
machine learning
deep learning
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Pascal Vincent
University of Montreal Canada
algorithmics
artificial intelligence
machine learning
deep learning
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Satish Thittamaranahalli
University of Southern California United States of America
algorithmic techniques
artificial intelligence
machine learning
approximation randomization
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John Doe
New York University United States of America
algorithm optimization
artificial intelligence
machine learning
deep learning
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Holger Hoos
RWTH Aachen University Germany
artificial intelligence
machine learning
automated machine learning
automated reasoning
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Nicole Wein
University of Michigan United States of America
online algorithms
distributed algorithms
dynamic algorithms
parameterized algorithms
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Thomas Schön
Uppsala University Sweden
decision-making algorithms
artificial intelligence
machine learning
deep learning
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Naveed Akhtar
University of Western Australia Australia
artificial intelligence
machine learning
deep learning
adversarial machine learning
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Aaron Roth
University of Pennsylvania United States of America
algorithmic fairness
fairness in machine learning
ethical algorithms
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Alan Tsang
Carleton University Canada
algorithmic fairness
fair allocation
artificial intelligence
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