Deep Decarbonization Professors in Global

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Christoph Brune
University of Twente Netherlands
deep gaussian processes
deep learning
geometric deep learning
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Annika Skoglund
University of Bristol United Kingdom
industrial decarbonisation
technological decarbonization
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Yinyan Liu
University of New South Wales Australia
decarbonization
decentralization
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Alice Mah
University of Glasgow United Kingdom
decarbonisation
deindustrialization
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Chaochen Xu
University of Western Australia Australia
decarbonization
co2 reduction
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Edward Sargent
University of Toronto Canada
energy decarbonization
co2 reduction
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Kin-choong Yow
University of Regina Canada
deep learning
deep reinforcement learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
deep learning
deep reinforcement learning
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Nina Taherimakhsousi
University of Victoria Canada
deep learning
deep reinforcement learning
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Jingmin Huang
University of Southampton United Kingdom
deep learning
deep generative models
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Xenia Miscouridou
Imperial College London United Kingdom
deep learning
deep generative models
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Victor Li
University of Michigan United States of America
decarbonization of built environment
carbon sequestration
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Patryk Rygiel
University of Twente Netherlands
deep learning
geometric deep learning
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Anastasios Kratsios
University of Toronto Canada
deep learning
geometric deep learning
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Krishna Swamy
Yale University United States of America
deep learning
geometric deep learning
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Chuan He
Linköping University Sweden
deep learning
decentralized optimization
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Rasmus Paulsen
Technical University of Denmark Denmark
deep reinforcement learning
geometric deep learning
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
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Zhiyong Ren
Princeton University United States of America
water sector decarbonization
desalination
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Aidan Smith
Aarhus University Denmark
hydrothermal carbonization
greenhouse gas emission reduction
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