Concept

Terrain cartography

Related people (28)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Otto Kölbl

David Andrew Barry

Research InterestsSubsurface hydrology, constructed wetlands, ecological engineering, in particular contaminant transport and remediation of soil and groundwater; more generally, models of hydrological and vadose zone processes; application of mathematical methods to hydrological processes; coastal zone sediment transport, aquifer-coastal ocean interactions; hydrodynamics and modelling of lakes.

Zhaoyang Wang

Franziska Gerber

Fernando Porté Agel

FERNANDO PORTÉ AGEL Professor Director, Wind Engineering and Renewable Energy Laboratory (WIRE) School of Architecture, Civil and Environmental Engineering (ENAC) École Polytechnique Fédérale de Lausanne (EPFL) e-mail: fernando.porte-agel@epfl.ch RESEARCH INTERESTS Environmental fluid mechanics. Computational fluid dynamics. Atmospheric boundary layers. Turbulence. Large-eddy simulation. Wind energy. Wind engineering. Renewable energy. EDUCATION Ph.D. 1999 Johns Hopkins University, Environmental Engineering M.Sc. 1995 Hydrologic Engineering, IHE - Delft, The Netherlands B.S. 1992 Universidad Politécnica de Cataluña, Spain ACADEMIC POSITIONS 2010-present: Full Professor, School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Switzerland 2005-2009: Associate Professor, St. Anthony Falls Laboratory and Department of Civil Engineering, University of Minnesota, Minneapolis, MN, USA 2000-2005: Assistant Professor, St. Anthony Falls Laboratory, Department of Civil Engineering, University of Minnesota, Minneapolis, MN, USA AWARDS AND FELLOWSHIPS McKnight Presidential Fellow (2006-2009), University of Minnesota, USA McKnight Land-Grant Professorship (2003-2005), University of Minnesota, USA NASA Young Investigator Award (2001-2004), USA NSF CAREER Award (2001-2006), (Division of Earth Sciences Hydrological Sciences), USA Outstanding Student Paper Award: Hydrology Section, Fall Meeting of the American Geophysical Union; San Francisco, 1998. Research Award (1995-1997): La Caixa fellowship program; Barcelona, Spain. Research Award (1993-1995): Dutch Ministry of Foreign Affairs fellowship. Research Award (1990-1993): Spanish Civil Engineering Association.

Jean-Philippe Thiran

Jean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam. Dr Thiran's current scientific interests include Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.