Paolo PeronaExpertise
River mechanics and morphoydnamics, Erosion processes, Ecohydraulics, Plant roots biomechanics, Watershed and catchment hydrology, Water Resources Management, General hydraulics, Time Series Analysis, Dynamical Systems Theory, Stochastic Processes
Expertise
River mechanics and morphoydnamics, Erosion processes, Ecohydraulics, Plant roots biomechanics, Watershed and catchment hydrology, Water Resources Management, General hydraulics, Time Series Analysis, Dynamical Systems Theory, Stochastic Proces
Volkan CevherVolkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University. His research interests include machine learning, signal processing theory, optimization theory and methods, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.
Roberto CastelloRoberto Castello is a senior scientist and group leader at the EPFL Laboratory of Solar Energy and Building Physics. Physicist by training, he has extensive experience in collecting, classifying and interpreting large datasets using advanced data mining techniques and statistical methods. He received his MSc (2007) in Particle Physics and PhD (2010) in Physics and Astrophysics from the University of Torino. He worked as a postdoctoral researcher at the Belgian National Research Fund (2011-2014) and at the CERN Experimental Physics Department (2015-2017) as a research fellow and data scientist. He is primary author of more than 20 peer-reviewed publications and he presented at major international conferences in the high energy physics domain.
In 2018 he joined the Solar Energy and Building Physics Laboratory (LESO-PB) to work on data mining and Machine Learning techniques for the built environment and renewable energy. His main research interests are: spatio-temporal modeling of renewable energy potential, energy consumption forecasting techniques, anomaly detection, and computer vision techniques for automated classification in the built environment.
He leads the group of Urban Data Mining, Intelligence and Simulation at LESO-PB and he is a member of the NRP75 Big Data project (HyEnergy) of the Swiss National Science Foundation. He is a member of the Swiss Competence Centre for Energy Research (SCCER) and deputy leader of the working group on Leveraging Ubiquitous Energy Data. He has served as a scientific committee member, workshop organizer and speaker at international conferences (ICAE 2020, Applied Machine Learning Days 2019 and 2020, CISBAT 2019 and 2021 and SDS2020).
Since 2017 he is member of the Geneva 2030 Ecosystem network, promoting the United Nations agenda towards the realization of the Sustainable Development Goals (SDGs).
Paolo BenettinI was born in Padova, Italy, in 1986. After high school, I started the Environmental Engineering program at the University of Padova (Bachelor and Master), where I followed the 'soil protection' curriculum. During my Master studies I spent a semester as Erasmus student at Wageningen University (Wageningen, the Netherlands) to follow courses in Hydrology. After graduation, I decided to bring my education further and I started a Ph.D. at the civil and environmental engineering department at the University of Padova. My Ph.D. thesis focused on hydrologic transport and travel time distributions at the catchment scale. My contribution to the subject included both new theoretical formulations and extensive numerical applications to real catchments. During my Ph.D., I also spent 7 months as visiting research fellow at Virginia Tech University (Blacksburg, USA). Since I arrived at EPFL as post-doc in 2015, I started being involved in field and experimental activities, which allowed me to learn about practical experimental problems. In 2017 I had the opportunity to by hired by the ECHO laboratory as a permanent scientist, conducting research in the field of catchment hydrology.
Laurent VillardTeaching & PhD Past EPFL PhD Students Matteo Maccio, Olivier Fischer, Gloria Luisa Falchetto, Paolo Angelino, Sébastien Jolliet, Xavier Lapillonne, Thibaut Vernay, Julien Stanislas Pierre Dominski, Gabriele Merlo, Emmanuel Lanti, Noé Ohana, Moahan Murugappan
Elena RaveraTeaching & PhD Courses Terra Epidermis PENS-211 This transversal project aims to test around a case study chosen, the specifics of " reverse soil ." On a chose site, students will be invited to propose a single technical and architectural gesture, and synthesize their concept graphically.
Kamil SedlákTeaching & PhD PhD Students Daniel Louis Arthur Biek Courses Fusion and industrial plasma technologies PHYS-632 The course provides an overview of the technologies that are essential for fusion developments and for industrial plasmaapplications, highlighting the synergies between the two fields. The aim is to provide a combined theoretical andexperimental background to the various topics.
Martin Alois RohrmeierTeaching & PhD PhD Students Joris Monnet, Marina Borsodi-Benson, Xinyi Guan, Xiaoxuan Wang, Zeng Ren Past EPFL PhD Students Fabian Claude Moss, Daniel Harasim, Christoph Finkensiep, Johannes Hentschel, Gabriele Cecchetti, Shuxin Meng Courses Digital musicology DH-401 This course will introduce students to the central topics in digital musicology and core theoretical approaches and methods. In the practical part, students will carry out a practical project. Musical theory and creativity
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