Physics Based Machine Learning Professors in Global

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Tal Kachman
Radboud University Netherlands
machine learning
statistical physics
deep learning
reinforcement learning
financial machine learning
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Somnath Ghosh
Johns Hopkins University United States of America
multi-physics modeling
machine learning
physics
computational mechanics
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Yisong Yue
California Institute of Technology United States of America
statistical machine learning
machine learning
structured machine learning
interactive machine learning
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Federico Bocci
Radboud University Netherlands
machine learning
deep learning
biophysical modeling
mathematical modeling
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Mehrdad Mahdavi
Pennsylvania State University United States of America
large-scale machine learning
computational statistical machine learning
deep learning
computational learning theory
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Molei Tao
Georgia Institute of Technology United States of America
machine learning
probabilistic machine learning
dynamical systems machine learning
deep learning theory
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Mohsen Amiri
Stockholm University Sweden
machine learning
deep learning
reinforcement learning
federated learning
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Yee Teh
University of Oxford United Kingdom
machine learning
large scale machine learning
deep learning
probabilistic learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
deep learning
reinforcement learning
robot learning
deep reinforcement learning
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Clemens Gühmann
Technical University of Berlin Germany
physics-based modelling
machine learning
data-based modelling
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Vinay Gogineni
University of Southern Denmark Denmark
physics-informed neural networks
quantum machine learning
machine learning
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Satyasaran Changdar
University of Copenhagen Denmark
physics-informed neural networks
machine learning
deep learning
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Michiel Van De Panne
University of British Columbia Canada
physics-based simulation
machine learning
reinforcement learning
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Nathaniel Bastian
Pennsylvania State University United States of America
federated machine learning
machine learning
deep learning
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Hamid Alinejad-rokny
University of New South Wales Australia
statistical machine learning
machine learning
biomedical machine learning
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Ambuj Tewari
University of Michigan United States of America
machine learning
theory of machine learning
reinforcement learning
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Hina Shaheen
University of Manitoba Canada
statistical machine learning
machine learning
computational modelling
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning algorithms
machine learning theory
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Rickard Armiento
Linköping University Sweden
machine learning
physical modeling
theoretical physics
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Christopher Atkeson
Carnegie Mellon University United States of America
machine learning
memory-based learning
reinforcement learning
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Sriram Subramanian
Carleton University Canada
machine learning
deep learning
reinforcement learning
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