The team


The KATABATA project brings together three researchers from the University of Liège.

KATABATA Team 

Picture : Xavier Fettweis, Michaël Fonder and Damien Ernst

Damien ERNST

Damien ERNST is a computer engineer at the Faculty of Applied Sciences, and a researcher at the Montefiore Institute of Electrical and Engineering and Computer Science Research Unit.

Known for his research in the field of artificial intelligence and the Global Grid, his scientific work has been published in two books, twelve book chapters, more than fifty journal articles, and approximately 150 conference proceedings. In 2018, Damien Ernst received the Blondel Medal, a prestigious award granted by the Société de l'Électricité, de l'Électronique et des Technologies de l'Information et de la Communication (SEE) that recognizes a remarkable research career in the field of electrical engineering sciences.

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Xavier FETTWEIS

Xavier FETTWEIS is a climatologist in the research unit SPHERES (Faculty of Sciences) of the ULiège. He is known for his climate modelling work in the Arctic (notably thanks to the MAR model, developed in his lab).

Xavier Fettweis is continuing his work on the modelling of the Greenland climate in the Climatology Laboratory which he has directed since September 2017. He has been a Research Associate of  the FNRS since October 2013 and now coordinates the development of the regional climate model MAR, used in particular to study the melting of the polar ice caps but also climate change in Belgium. He has also developed a classification of weather types to study recent changes in atmospheric circulation in the Arctic that favour the melting of the Greenland ice cap.

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Michaël FONDER

Michaël FONDER is an electrical engineer, and is a PhD student at the Montefiore Research Unit Institute of Electrical and Engineering and Computer Science.

Michaël Fonder's research focuses on the fields of deep learning and computer vision. Currently, his work is focused on the development of algorithms to assist the piloting of a UAV by exploiting the information provided by onboard cameras. 

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