Pain Related Learning Professors in Global

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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
perceptual learning
cognitive learning
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Sascha Schneider
University of Zurich Switzerland
emotional learning
cognitive learning
social learning
motivational learning
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Lester Jones
Singapore Institute of Technology Singapore
pain literacy
student learning
reflective learning
self regulated learning
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Pascal Poupart
University of Waterloo Canada
causal learning
reinforcement learning
shot learning
self-supervised learning
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David Kennedy
University of Victoria Canada
learning and pain responses
cognitive factors in pain
pain perception
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Ludwig Maximilian University of Munich Germany
experimental pain research
pain therapy
clinical pain research
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Pierre Rainville
University of Montreal Canada
pain modulation
neuropsychology of pain
emotional influences on pain
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Annette Grunwald
Aalborg University Denmark
learning
problem based learning
active learning
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Benedek Kurdi
University of Illinois United States of America
learning
causal learning
reinforcement learning
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Nader Ghasemlou
Queen's University Canada
translational pain research
pain physiology
understanding of pain outcomes
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Kristian Petersen
Aalborg University Denmark
pain measurement
pain science
pain mechanisms
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Tamara Van Gog
Utrecht University Netherlands
learning
multimedia learning
example-based learning
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Sophia Bello
University of Toronto Canada
experiential learning
language learning
active learning
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Shengping Zou
New York University United States of America
pain management
interventional pain management
multimodal pain management
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Lone Hersted
Aalborg University Denmark
learning processes
action learning
organizational learning
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Fernando Olivera
Western University Canada
learning processes
group learning
individual learning
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Peter Meyerhoff
Northwestern University United States of America
learning interaction
hands-on learning
mathematics learning
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Nikolaj Stegeager
Aalborg University Denmark
problem-based learning
collaborative learning
active learning
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Rudolf Lioutikov
University of Texas at Austin United States of America
reinforcement learning
structure learning
imitation learning
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Nicholas Rhinehart
University of Toronto Canada
reinforcement learning
robot learning
imitation learning
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Yinbei Li
Singapore Institute of Technology Singapore
reinforcement learning
robot learning
imitation learning
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