Inverse Modelling Professors in Global

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Magnus Röding
Chalmers University of Technology Sweden
statistical modeling
physical modeling
stochastic modeling
machine learning
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Katy Tant
University of Glasgow United Kingdom
inverse problems
data-driven inverse problems
mathematical modelling
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Florian Shkurti
University of Toronto Canada
inverse reinforcement learning
imitation learning
machine learning
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Fadil Santosa
Johns Hopkins University United States of America
inverse problems
mathematical modeling
machine learning
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Deeph Chana
Imperial College London United Kingdom
inverse problems
computational modeling
machine learning
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Paul Segall
Stanford University United States of America
geophysical inverse theory
theoretical modeling
data collection and inversion
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Kevin Smith
Royal Institute of Technology Sweden
inverse problems
generative modeling
machine learning
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Mirjam Kretzschmar
UMC Utrecht Netherlands
mathematical modelling
statistical modelling
infectious disease modelling
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Gerard Gorman
Imperial College London United Kingdom
inversion optimization
multi-scale modeling
multi-physics modeling
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Daniel Graham
Imperial College London United Kingdom
mathematical modelling
statistical modelling
economic modelling
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Arson Lab
Cornell University Netherlands
model reduction
multi-scale modeling
numerical modeling
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Jaime Ide
Yale University United States of America
theoretical modeling
predictive modeling
machine learning
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Joakim Munkhammar
Uppsala University Sweden
mathematical modeling
statistical modeling
machine learning
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Kamal Hossain
University of Melbourne Australia
computational modeling
statistical modeling
machine learning
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Samir Maity
Aalborg University Denmark
imprecise modeling
predictive modeling
machine learning
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Fangxin Fang
Imperial College London United Kingdom
model reduction
predictive modeling
machine learning
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Iain Moyles
York University Canada
mathematical modelling
behaviour modelling
disease modelling
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Luke Miller
Radboud University Netherlands
computational modeling
neural network modeling
machine learning
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Till Bretschneider
University of Warwick United Kingdom
image-based modeling
generative modeling
machine learning
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Akke Suiker
Eindhoven University of Technology Belgium
multi-scale modeling
failure modeling
multi-physics modeling
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Yalan Song
Pennsylvania State University United States of America
predictive modeling
differentiable modeling
machine learning
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