Alexis Berne

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Associate Professor

alexis.berne@epfl.ch +41 21 693 80 51 http://lte.epfl.ch

EPFL ENAC IIE LTE
GR C2 564 (Bâtiment GR)
Station 2
1015 Lausanne

+41 21 693 80 51
Office:  GR C2 564
EPFL > ENAC > IIE > LTE

Web site:  Web site:  https://lte.epfl.ch

+41 21 693 80 51
EPFL > ENAC > ENAC-SSIE > SSIE-ENS

EPFL > VPA-AVP-E > AVP-E > AVP-E-CDS

Web site:  Web site:  https://dms.epfl.ch/DOCS/E/CDS

EPFL ENAC SSIE-GE
GR A2 392 (Bâtiment GR)
Station 2
1015 Lausanne

+41 21 693 80 51
Office:  GR A2 392
EPFL > ENAC > ENAC-SSIE > SSIE-GE

Web site:  Web site:  https://ssie.epfl.ch/

EPFL VPA-CR
BI A2 435 (Bâtiment BI)
Station 7
1015 Lausanne

+41 21 693 80 51
Office:  BI A2 435
EPFL > VPA > VPA-FAC > CPR

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Administrative data

Fields of expertise

Radar meteorology 
Precipitation microphysics 
Polar precipitation
Geostatistics

Professional course

Associate Professor

LTE

EPFL

2013 -

Assistant Professor

LTE

EPFL

2006 - 2013

Post-doctoral researcher

LTHE

INPG, Grenoble, France

03/2006 - 09/2006

Post-doctoral researcher

HWQ

Wageningen University, The Netherlands

2003 - 2006

Teaching & PhD

Teaching

Environmental Sciences and Engineering

PhD Students

Corden Heather Anne, Erb Sophie Catherine, Ghiggi Gionata, Liernur Adrien Francis Olivier,

Past EPFL PhD Students

Bianchi Blandine , Billault--Roux Anne-Claire Marie , Feldmann Monika , Ferrone Alfonso , Gehring Josué Etienne , Grazioli Jacopo , Jaffrain Joël , Raupach Timothy Hugh , Schleiss Marc , Schwärzel Marc Damien , Van den Heuvel Floortje Elisabeth Maria , Wolfensberger Daniel ,

Courses

Remote sensing

This course aims at exposing the students to the main concepts, instruments and techniques of environmental remote sensing. The interactions between waves and matter, different types of sensors and image-processing techniques are presented.

Atmospheric processes: from cloud to global scales

The main objective is to present important atmospheric processes from the local to global scales. The course will start with cloud processes, continue to synoptic phenomena like extratropical cyclones and fronts, to finally cover numerical modeling at the regional and global scales.

Sensing and spatial modeling for earth observation

Students get acquainted with the process of mapping from images (orthophoto and DEM), as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotemporal variability of processes.