Multi Modal Machine Learning Professors in Global

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Usman Naseem
Macquarie University Australia
multimodal analysis
multimodal content analysis
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Samuel Ajila
Carleton University Canada
multi-modal learning applications
machine learning
deep learning
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Chen Li
Aalborg University Denmark
multimodal analysis
deep learning
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Raktim Mondol
University of New South Wales Australia
multimodal analysis
deep learning
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Brandon Pitts
Purdue University United States of America
multimodal
multisensory information processing
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Zhanhong Zhan
University of Western Australia Australia
multitask learning
deep learning
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Julia Dakwar
University of Southern Denmark Denmark
multimodal semiotics
multimodal transcription analysis
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Yang Song
University of New South Wales Australia
multimodal human-centred ai
deep learning
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Caren Han
University of Western Australia Australia
visual-linguistic multi-modal learning
deep learning
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Arun Prakash
Purdue University United States of America
multi-physics
multi-scale mechanics
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Yi-shan Tsai
Monash University Australia
multimodal feedback
multimodal literacy
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Lennart Svensson
Chalmers University of Technology Sweden
multi-target tracking
deep learning
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
deep learning
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
deep learning
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Kate Saenko
Boston University United States of America
adaptive machine learning
deep learning
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David Harwath
University of Texas at Austin United States of America
multi-modal machine learning
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Emil Jensen
Technical University of Denmark Denmark
multi-modal machine learning models
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Albert Gatt
Utrecht University Netherlands
multimodal neural models
machine learning
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Saining Xie
New York University United States of America
multimodal intelligence
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Stephan Caspar
Carnegie Mellon University United States of America
multimodal language learning
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Blessing Ogbuokiri
Brock University Canada
multi-modality
machine learning
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