Bias In Machine Learning Professors in Global

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Maximilian Kasy
University of Oxford United Kingdom
machine learning
publication bias
algorithmic decision making
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Peter Grunewald
Heidelberg University Germany
predictive modelling
bayesian inference
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Vanessa Mcnealis
University of Glasgow United Kingdom
bayesian inference
hierarchical modelling
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Hina Shaheen
University of Manitoba Canada
machine learning
statistical machine learning
bayesian inference
computational modelling
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Xinran Li
University of Chicago United States of America
bayesian inference
randomization-based inference
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Laura Schulz
Massachusetts Institute of Technology United States of America
inductive biases
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Eva Vanmassenhove
Tilburg University Netherlands
algorithmic bias
gender bias
machine translation
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Noel Ragsdale
University of Southern California United States of America
gender bias
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Rekha Krishnan
Simon Fraser University Canada
gender bias
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Kristyn Scott
Toronto Metropolitan University Canada
gender bias
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Amber Stephenson
Penn State Harrisburg United States of America
gender bias
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Anikó Hannák
University of Zurich Switzerland
social biases
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Tal Simons
Erasmus University Rotterdam Netherlands
media bias
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Samuel Stäbler
Tilburg University Netherlands
media bias
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Pinar Yildirim
University of Pennsylvania United States of America
media bias
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Ursula Kessels
Freie Universität Berlin Germany
feedback bias in education
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Ilias Chalkidis
University of Copenhagen Denmark
bias and debiasing
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Benjamin Eidelson
Harvard University United States of America
algorithmic discrimination
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Aleksandra Korolova
Princeton University United States of America
algorithmic discrimination
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Eric Rosen
University of Michigan United States of America
learning algorithms
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Anne-michelle Tessier
University of British Columbia Canada
learning algorithms
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