Anne-Laure Mahul MellierExpertise
Cellular Biology: Cell culture of mammalian cell lines (U2OS, N2a, M17, SH-S5Y5, Cos, HeLa, HEK, MCF7), Astrocytic and neuronal primary cultures (hippocampus, cortex, striatum, midbrain) from P0 mouse or rat pups or from E16-E19 mice embryos, iPSC neuronal cultures (proliferation, passaging, differentiation in iNeurons or iDopaminergic neurons), Cellular transfection (DNA plasmid, siRNA, shRNA), Lentiviruses production and infection of neuronal primary cultures or mammalian cell lines, Samples pre
Romain GuietExpertise
Development of BioImage Analysis workflows and algorithms to extract quantitative data from microscopy images.BioSample Preparation : in vitro cell, organoid, time-lapse, fixation, staining strategies, actin, mitochondria, fluorescent protein expressionBioImage Acquisition : Widefield, Confocal, Whole Slide Imaging, Super-resolution (SIM, STORM, STED), FRET, FRAP, FLIMBioImage Analysis: Colocalisation analysis, Deconvolution, Time-lapse , Whole Slide ImagingTools & Software: ImageJ/Fiji, QuPath, i
Francesco StellacciFrancesco Stellacci graduated in Materials Engineering at the Politecnico di Milano in 1998 with a thesis on photochromic polymers with Prof. Giuseppe Zerbi and Mariacarla Gallazzi. In 1999 he moved to the Chemistry Department of the University of Arizona for as a post-doc in the group of Joe Perry in close collaboration with the group of Seth Marder. In 2002 he moved to the Department of Materials Science and Engineering at the Massachusetts Institute of Technology as an assistant professor. He was then promoted to associate without (2006) and with tenure (2009). In 2010 he moved to the Institute of Materials at EPFL as a full Professor. He holds the Alcan EP Chair. Francesco was one of the recipients of the Technology Review TR35 "35 Innovator under 35" award in 2005, and the Popular Science Magazine "Brilliant 10" award in 2007. He has been a Packard Fellow starting 2005.
Quentin BarraudExpertise
Translational neuroscience · Neuromodulation · Spinal cord injury & Parkinson’s disease · Multi-omics (single-cell, spatial transcriptomics, 3D cleared-tissue imaging) · Preclinical platform management
Mission
To develop, coordinate, and supervise the preclinical activities of .NeuroRestore at EPFL, integrating innovative neuromodulation, gene therapy, and multi-omic strategies. To ensure regulatory compliance of all animal work, support scientific teams in experimental design, and build bridges b
Bruno Emanuel Ferreira De Sousa CorreiaThroughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.
Stéphanie LacourStéphanie P. Lacour holds the Bertarelli Foundation Chair in Neuroprosthetic Technology in the School of Engineering at EPFL and leads the Laboratory for Soft Bioelectronic Interfaces. She received her PhD in Electrical Engineering from INSA de Lyon, France, and completed postdoctoral research at Princeton University and the University of Cambridge. She is the recipient of the 2006 MIT TR35, a University Research Fellowship of the Royal Society, European Research Council ERC Starting and POC Grants, and a SNSF-ERC Consolidator Grant. She was elected a 2015 Young Global Leader by the World Economic Forum.
Berend SmitBerend Smit received an MSc in Chemical Engineering in 1987 and an MSc in Physics both from the Technical University in Delft (the Netherlands). He received in 1990 cum laude PhD in Chemistry from Utrecht University (the Netherlands). He was a (senior) Research Physicists at Shell Research from 1988-1997, Professor of Computational Chemistry at the University of Amsterdam (the Netherlands) 1997-2007.
In 2004 Berend Smit was elected Director of the European Center of Atomic and Molecular Computations (CECAM) Lyon France. Since 2007 he is Professor of Chemical Engineering and Chemistry at U.C. Berkeley and Faculty Chemist at Materials Sciences Division, Lawrence Berkeley National Laboratory. Since 2014 he has been director of the Energy Center at EPFL.
Suliana ManleyFrom 2016 Associate professor, EPFL, Lausanne, Switzerland
2009-2016 Tenure-track assistant professor, EPFL, Lausanne, Switzerland
2006-2009 Post-Doctoral fellow, National Institutes of Health, Bethesda, MD, USA
2004-2006 Post-Doctoral fellow, Massachusetts Institute of Technology, Cambridge, MA, USA
1999-2004 PhD (Physics) Awarded 06/2004, Harvard University, Cambridge, MA, USA
1993-1997 Bachelors (Cum Laude) Physics & Mathematics, Rice University, Houston, TX, USA
Christophe MoserDr. Christophe Moser is
Associate Professor of Microengineering and Industrial Relations
at the Swiss Federal Institute of Technology in Lausanne. He was the co-founder and CEO of
Ondax,Inc
for ten years prior to joining EPFL. During this decade, he raised $15 million from corporate and venture capital sources to fund volume production of thick holographic components in glass and develop devices enabled by these components such as tunable add-drop multiplexers for telecommunications, ultra-narrowband notch filters for low frequency Raman systems, high power semi-conductor frequency-narrowed pumps for fiber lasers, single frequency fixed and tunable lasers for sensing and femtosecond pulse compressors for micro-machining applications. Dr. Moser has a Ph.D. in Electrical Engineering from the California Institute of Technology, a minor in finance and a bachelor degree in Physics from EPFL.
He is the co-inventor of 24 patents, 14 peer reviewed scientific publications, 9 IEEE proceedings and a book chapter.
Private interests include tennis, running, ski, basketball and family excursions.
2010: Associate Professor, EPFL, faculty
Science Technique Ingenieur.
2000-2010: co-founder, CEO Ondax, Inc.
1995-2000: Graduate Research Assistant,
California Institute of Technology.
1993-1995: Engineering Project manager ,
TESA.
1988-1993: Bachelor candidate in Physics, EPFL.
MAIN PUBLICATIONS:
Moser C., Havermeyer F,.Ultra-narrowband tunable laserline notch filter, Appl. Phys. B, 95 (3), pp 597-601, 2009.
Moser C. ,Ho L., Havermeyer F,. Self-aligned Non-dispersive External Cavity Tunable Laser, 16 (21), 16691-16696 Optics Express, 2008.
Steckman, GJ , Moser C. et al. Volume holographic grating wavelength stabilized laser diodes, IEEE J. Of Selected Topics in Quantum Electronics, (13), 672-678, 2007.
Buse K, Havermeyer F, Liu W., Moser C, Psaltis D. Holographic Filters , Book Chapter Photorefractive Materials and their Applications, 2005.
Havermeyer, F; Liu, WH; Moser, C, et al. Volume holographic grating-based continuously tunable optical filter , Opt. Eng. 43 (9), 2017-2021, 2004.
Moser C., Maravic I., Schupp B., Adibi A, Psaltis D, Diffraction efficiency of localized holograms in doubly doped LiNbO3 crystals, Opt. Lett. 25: (17),1243-1245, 2000. Luciano Andres AbriataExpertise
Protein NMRNMR of paramagnetic systemsMetalloproteinsBiomolecular SpectroscopyStructural BiologyStructural BioinformaticsMolecular Modeling
ResearchPapers Link to Google Scholar
Teaching & PhD Courses Basic and advanced NMR - Level 1 A (EPFL) CH-601(x) Basic theoretical and experimental aspects of NMR will be taught. Students will be familarized with modern NMR spectrometers. Basic and advanced NMR - Level 2 (EPFL) CH-703 The goal is to give a sound theoretical an
Marion LeleuExpertise
Bioinformatics, Genomics, High-Throughput Sequencing, Data Mining
Mission
Provide advanced and personalised support and consulting in bioinformatics and biostatistics for the scientific community of EPFL, UNIL, and other Institutes.Her main areas of interest and expertise include but are not limited to, genomics, transcriptomics and epigenetics, with a strong interest in integrating multiple modalities, and choosing the appropriate statistical models, to gain a comprehensive understanding of compl
Fosco Bernasconi2014-Present:
post-doc at the EPFL, Laboratory of Congitive Neuroscience.
2012-2014:
Postdoctoral Research Associate, Charité University Medicine, Berlin, Germany.
2012:
Postdoctoral Research Associate,Psychiatric University Hospital (PUK), Zurich, Switzerland.
2008-2011:
PhD in Neurosciences,Lemanic Neurosciences Doctoral School, Faculty of Biology and Medicine, Lausanne University, Switzerland.
2007-2008:
Master in Medical Biology,Faculty of Biology & Medicine, Lausanne University,Switzerland.
Johanni Michael BreaTeaching & PhD PhD Students Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Courses Artificial intelligence and society HUM-286 This course integrates social sciences and humanities with engineering sciences, and introduces students to the social, technical and political issues surrounding artificial intelligence. Biological data science II : machine learning BIO-322 Students understand basic concepts and methods of machine learning. They can describe them in mathematical
