Blended Learning Professors in Global

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Yuhong Guo
Carleton University Canada
federated learning
reinforcement learning
self-supervised learning
active learning
representation learning
semi-supervised learning
continual learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
cognitive learning
depth learning
perceptual learning
transfer learning
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Christian Stöhr
Chalmers University of Technology Sweden
hybrid learning
digital learning
technology-enhanced learning
online learning
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Yichen Zhang
Purdue University United States of America
distributed learning
multi-task learning
reinforcement learning
transfer learning
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Arthur Galamba
King's College London United Kingdom
hybrid learning
collaborative learning
online learning
stem learning
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Antoine Van Den Beemt
Eindhoven University of Technology Belgium
networked learning
transdisciplinary learning
technology enhanced learning
challenge-based learning
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Tamara Van Gog
Utrecht University Netherlands
learning
multimedia learning
example-based learning
self-regulated learning
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Samory Kpotufe
Columbia University United States of America
multi-task learning
adaptive learning
active learning
transfer learning
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Pieter Abbeel
University of California, Berkeley United States of America
reinforcement learning
deep learning
imitation learning
transfer learning
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Natalie Bennett
Monash University Australia
blended learning
collaborative learning
active learning
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Sharon Flecknoe
Monash University Australia
blended learning
collaborative learning
active learning
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Marie-soleil Beaudoin
Dalhousie University Canada
blended learning
online learning
self-regulated learning
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Stefan Stenbom
KTH Royal Institute of Technology Sweden
blended learning
digital learning
learning engineering
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Claire Bossavit
Simon Fraser University Canada
blended learning
mastery learning
project-based learning
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Yaoliang Yu
University of Waterloo Canada
distributed learning
federated learning
representation learning
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Il-min Kim
Queen's University Canada
distributed learning
federated learning
continual learning
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Yue Tan
University of New South Wales Australia
federated learning
multimodal learning
representation learning
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Fei Wang
Cornell University Netherlands
federated learning
multi-modal learning
transfer learning
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Junfeng Wen
Carleton University Canada
federated learning
reinforcement learning
transfer learning
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Ali Beikmohammadi
Stockholm University Sweden
federated learning
reinforcement learning
deep learning
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Mohsen Amiri
Stockholm University Sweden
federated learning
reinforcement learning
deep learning
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