Regulatable Machine Learning Professors in Global

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Yingzhen Li
Imperial College London United Kingdom
explainable machine learning
probabilistic machine learning
machine learning
generative modeling
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Henrik Boström
KTH Royal Institute of Technology Sweden
explainable machine learning
trustworthy machine learning
probabilistic machine learning
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Moez Ali
Queen's University Canada
automated machine learning
automated modeling
machine learning
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Mohamed Abdelfattah
Cornell University Netherlands
automated machine learning
machine learning
reconfigurable computing
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Holger Hoos
RWTH Aachen University Germany
automated machine learning
machine learning
automated reasoning
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Danica Sutherland
University of British Columbia Canada
theoretical machine learning
statistical machine learning
machine learning
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Navid Azizan
Massachusetts Institute of Technology United States of America
trustworthy machine learning
machine learning
scientific machine learning
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Sophia Wilson
University of Copenhagen Denmark
resource efficient machine learning
machine learning
data efficient machine learning
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Hina Shaheen
University of Manitoba Canada
statistical machine learning
machine learning
computational modelling
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Jinfeng Liu
University of Alberta Canada
machine learning
applied machine learning
model predictive control
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Geoff Webb
Monash University Australia
scalable learning
machine learning
interactive machine learning
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Yisong Yue
California Institute of Technology United States of America
structured machine learning
statistical machine learning
machine learning
interactive machine learning
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Klaus-robert Müller
Technical University of Berlin Germany
probabilistic machine learning
machine learning
explainable ai
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Klaus Müller
Technical University of Berlin Germany
probabilistic machine learning
machine learning
explainable ai
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Molei Tao
Georgia Institute of Technology United States of America
probabilistic machine learning
machine learning
generative modeling
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Nathaniel Bastian
Pennsylvania State University United States of America
federated machine learning
machine learning
robust learning
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Aristide Akem
University of Southampton United Kingdom
machine learning
applied machine learning
programmable networking
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Benjamin Joffe
Georgia Institute of Technology United States of America
machine learning
robotic manipulation
robot learning
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Yaoliang Yu
University of Waterloo Canada
machine learning
distributed learning
generative modelling
robust stochastic optimization
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Amir Rahnama
KTH Royal Institute of Technology Sweden
interpretable machine learning
explainable machine learning
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Zihuai University
Stanford University United States of America
interpretable machine learning
explainable machine learning
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