Machine Learning In Energy Systems Professors in Global

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Brian Mathiesen
Aalborg University Denmark
energy systems analysis
integrated energy systems
smart energy systems
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Rene Boonen
KU Leuven Belgium
dynamic systems modeling
machine system design
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Iain Staffell
Imperial College London United Kingdom
energy demand modeling
renewable energy systems
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Daniel Kammen
University of California, Berkeley United States of America
energy forecasting
renewable energy systems
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Chima Ezekiel
University of Calgary Canada
sustainable geo-energy systems modeling
geosystems modeling
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Machteld Van Den Broek
Delft University of Technology Netherlands
energy system integration
short-term energy system balancing
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Polyneikis Kanellas
Technical University of Denmark Denmark
energy analytics
renewable energy systems
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Georgios Tsaousoglou
Technical University of Denmark Denmark
smart energy systems
modeling and control of flexible energy systems
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Iva Ridjan Skov
Aalborg University Denmark
energy system analysis
smart energy systems
renewable energy systems
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Subham Sahoo
Aalborg University Denmark
scientific machine learning
probabilistic machine learning
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Yuzhang Lin
New York University Tandon School of Engineering United States of America
machine learning applications
renewable energy systems
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Hao Wang
Monash University Australia
optimization of power and energy systems
applied machine learning
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Sasan Barak
University of Southampton United Kingdom
machine learning applications in finance
financial machine learning
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Michael Howland
Massachusetts Institute of Technology United States of America
climate modeling
renewable energy systems
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Majid Ali
Aalborg University Denmark
energy optimization
renewable energy systems
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Paul Johannesson
Stockholm University Sweden
information systems modeling
process modeling
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Alessandro Maccarini
Aalborg University Denmark
energy optimization
geothermal energy systems
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Amirnaser Yazdani
Toronto Metropolitan University Canada
electrical energy systems
renewable energy systems
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Marzyeh Ghassemi
Massachusetts Institute of Technology United States of America
healthcare machine learning
behavioral machine learning
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Marzyeh Ghassemi
Massachusetts Institute of Technology United States of America
healthcare machine learning
behavioral machine learning
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Yassine Yaakoubi
Concordia University Canada
machine learning-augmented optimization
probabilistic machine learning
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