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Gregoire Mariethoz research group

Remote Sensing, Geostatistics, Hydrology

 

University of Lausanne (UNIL)

UNSW Australia

 

Current group members:

Gregoire Mariethoz (Prof. Assistant, UNIL)

Lionel Benoit (PhD Candidate, UNIL)

Mathieu Gravey (PhD Candidate, UNIL)

Luiz Gustavo Rasera (PhD Candidate, UNIL)

Inigo Irarrazaval  (PhD Candidate, UNIL)

Xue Li (PhD Candidate, UNIL / University of Science and Technology of China)

Ehsan Baninajar (PhD Candidate, UNIL / Sahand University of Technology)

Juan Carlos Castilla (PhD Candidate, UNSW)

 

E-mail

 

The main research interests of the research group reside in the development of stochastic methods that characterize the spatial and temporal variability inherent to hydrological systems. We develop numerical techniques using high-order, nonparametric statistics. These allow us to analyze complex datasets such as remote sensing data or the outputs of complex models (climate models or flow/transport models). The work pursued is at the frontier between Earth modeling and computer science, with a strong emphasis on stochastic models, training images and example-based modeling.

 

One contribution has been the development of numerical methods that offer improved possibilities to integrate different kinds of data, especially those using the semi-qualitative concept of a training image. These include algorithms to perform reconstructions and stochastic simulations, broadly known as MPS. Please check out the book on this topic. In 2013 G. Mariethoz was awarded the Vistelius Award by the International Association for Mathematical Geosciences. This prize is given every 2 years to the most promising researcher under 35 in the field of mathematical geosciences (details).

 

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If you are interested in doing research in an area related to the topics described above, do not hesitate to take contact. We regularly welcome external researchers who come to Lausanne to join our group for periods ranging from months to years. Switzerland offers a range of scholarship opportunities to support top-ranking students.