Deep Learning Professors in Global

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John Doe
University of Wisconsin–Madison United States of America
deep learning
machine learning
artificial intelligence
data analysis
predictive modeling
computer vision
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Yuhong Guo
Carleton University Canada
machine learning
artificial intelligence
reinforcement learning
computer vision
self-supervised learning
representation learning
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Yuhong Guo
Carleton University Canada
machine learning
artificial intelligence
reinforcement learning
computer vision
self-supervised learning
representation learning
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Mahdi Khodayar
The University of Tulsa Iran
No active positions
deep neural networks
machine learning
artificial intelligence
computer vision
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Apurva Narayan
University of British Columbia Canada
machine learning
quantum machine learning
artificial intelligence
data mining
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Geoff Pleiss
University of British Columbia Canada
machine learning
reliable deep learning
artificial intelligence
probabilistic machine learning
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Yiyu Yao
University of Regina Canada
machine learning
artificial intelligence
data mining
data analysis
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John Doe
University of Wisconsin–Madison United States of America
machine learning
artificial intelligence
data mining
statistical learning
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John Doe
University of Groningen Netherlands
machine learning
artificial intelligence
data mining
computer vision
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John Doe
Aarhus University Denmark
machine learning
artificial intelligence
data mining
computer vision
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John Doe
University of Wisconsin–Madison United States of America
deep learning
machine learning
artificial intelligence
data mining
computer vision
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Sayed Reza
Penn State Harrisburg United States of America
machine learning
artificial intelligence
data mining
computer vision
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Vinay Gogineni
University of Southern Denmark Denmark
machine learning
quantum machine learning
meta learning
self-supervised learning
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Adyya Gupta
University of Melbourne Australia
machine learning
artificial intelligence
data analysis
predictive modeling
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Kevin Van Den Eynde
KU Leuven Belgium
machine learning
artificial intelligence
data analysis
predictive modeling
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Andreas Møgelmose
Aalborg University Denmark
machine learning
artificial intelligence
blended learning
computer vision
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Stuart Russell
University of California, Berkeley United States of America
machine learning
artificial intelligence
real-time decision making
computer vision
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Joris Mooij
University of Amsterdam Netherlands
machine learning
artificial intelligence
statistical learning
computational models
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Tahereh Koohi
University of New South Wales Australia
deep learning
machine learning
neural networks
artificial intelligence
evolutionary algorithms
computer vision
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Titouan Muzellec
University of Vienna Austria
machine learning
artificial intelligence
statistical learning
predictive modeling
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Guang Lin
Purdue University United States of America
machine learning
artificial intelligence
big data analysis
statistical learning
predictive modeling
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