Anna Fontcuberta i Morral2014 Associate Professor at the Institut des Matériaux, EPFL
2008 Assistant Professor Tenure Track at the Institut des Matériaux, EPFL
2009 Habilitation in Physics, Technische Universität München
2005-2010 Marie Curie Excellence Grant Team Leader at Walter Schottky Institut, Technische Universität München, on leave from Centre National de la Recherche Scientifique (CNRS, France)
2004-2005 Visiting Scientist at the California Institute of Technology, on leave from CNRS; Senior Scientist and co-founder of Aonex Technologies (a startup company for large area layer transfer of InP and Ge on foreign substrates for the main application of multi-junction solar cells)
2003 Permanent Research Fellow at CNRS, Ecole Polytechnique, France
2001-2002 Postdoctoral Scholar at the California Institute of Technology
Study of wafer bonding and hydrogen-induced exfoliation processes for integration of mismatched materials in views of photovoltaic applications
Sponsor: Professor Harry A. Atwater
1998-2001 PhD in Materials Science, Ecole Polytechnique
Study of polymorphous silicon: growth mechanisms, optical and structural properties. Application to Solar Cells and Thin Film Transistors
Advisor: Pere Roca i Cabarrocas
1997-1998 Diplôme dEtudes Approfondis (D.E.A.) in Materials Science at Université Paris XI, France .
1993-1997 BA in Physics at Universitat de Barcelona
Rahul Kumar GuptaRahul Gupta completed his B.Tech in electrical engineering at NIT Rourkela, India in 2014. From 2015 to 2016, he worked as research assistant on micro-energy harvesting at NUS Singapore. In 2018, he received his M.Sc degree in electrical engineering with orientation in smart grids technology at EPFL Lausanne, Switzerland. He received Zanelli: technologie et développement durable prize 2018 for his master project in the field of sustainable development. Currently, he is pursuing his Ph.D. degree at the Distributed Electrical Systems Laboratory, EPFL. His research interests include model predictive control, distributed optimization and data-driven control of the active distribution networks in the presence of uncertainties.
