Hardware Accelerated Machine Learning Professors in Global

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Sophia Wilson
University of Copenhagen Denmark
machine learning
data efficient machine learning
resource efficient machine learning
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Riyadh Baghdadi
New York University Tandon School of Engineering United States of America
high performance computing
deep learning
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Rick Stevens
University of Chicago United States of America
high performance computing
deep learning
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Brandon Haworth
University of Victoria Canada
augmented intelligence
deep learning
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Robert Nowak
University of Wisconsin–Madison United States of America
data-efficient machine learning
deep learning
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Andreea Bobu
Massachusetts Institute of Technology United States of America
human-aligned representation learning
human-centered robotics
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Varun Kanade
University of Oxford United Kingdom
computational learning
deep learning
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Michael Mack
University of Toronto Canada
human memory learning
computational modelling
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Bin Han
University of Alberta Canada
computer aided geometric design
deep learning
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Oisin Mac Aodha
University of Edinburgh United Kingdom
machine learning
machine teaching
deep learning
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Priya Donti
Massachusetts Institute of Technology United States of America
robust machine learning
physics-informed machine learning
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Tsirigos Tsirigos
New York University United States of America
deep learning
machine learning in healthcare
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Kristen Grauman
University of Texas at Austin United States of America
machine learning
deep learning
interactive machine learning
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Sitan Chen
Harvard University United States of America
algorithmic learning
quantum learning
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Seok-bum Ko
University of Saskatchewan Canada
deep learning
efficient hardware implementation
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Zakia Hammal
Carnegie Mellon University United States of America
deep learning
human-centered robotics
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Houman Homayoun
University of California, Davis United States of America
heterogeneous computing
hardware security
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Madeleine Wyburd
University of Copenhagen Denmark
deep learning
computational modelling
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Kamila Jozwik
University of Cambridge United Kingdom
deep learning
computational modelling
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Honglak Lee
University of Michigan United States of America
machine learning
deep learning
large-scale learning
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Zhiru Zhang
Cornell University Netherlands
machine learning
algorithm-hardware co-design
accelerator architectures
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