Marion LeleuExpertise
BioinformaticsGenomicsHight-Throughput SequencingData Mining
Jean-Paul Richard KneibEnseignement et PhD Doctorant·es actuel·les Oliver Pineda Suarez, Robert Daniel Kincaid, Ethan Daniel Tregidga, Belén Yu Irureta-Goyena Chang, Elisabeth Andréa Cécile Rachith, Shengyu He, Aurélien Thomas Mathieu Verdier, Timour Jestin A dirigé les thèses EPFL de Markus Rexroth, Luzius Gregor Kronig, Christoph Ernst René Schäfer, Vasileios Angelopoulos, Michaël Juillard, Amélie Tamone, Andrei Variu, Yoan Rappaz, Anne-Marlene Rüede, Jiaxi Yu, Daniel Felipe Forero Sanchez, Beauchesne Benjamin Emmanuel Nicola
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.
Luciano Andres AbriataEnseignement et PhD Cours Basic and advanced NMR - Level 1 A (EPFL) CH-601(x) Basic and advanced NMR - Level 2 (EPFL) CH-703 The goal is to give a sound theoretical and practical foundation in NMR for various applications in research. PhD students and post-docs who have followed the course successfully should be able to perform modern multi-dimensional NMR experiments independently. Integrative structural biology for Life sciences BIO-643 Recombinant protei
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.
Maria BrbicMaria Brbic is an assistant professor in computer science at EPFL. Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec. She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L’Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research.
Elisa OricchioEnseignement et PhD Doctorant·es actuel·les Vamsi Krishna Polavarapu, Asli Ece Kasapoglu, Konstantina Georgakopoulou, Eleni Balli A dirigé les thèses EPFL de Maria Christine Donaldson, Elena Battistello, Daniel Pereira Duarte, Frédérica Schyrr, Ruxandra-Andreea Lambuta, Aaron Simone Petruzzella, Jixing Zhong, Justine Epiney Cours Cancer biology I BIO-471 Le cours couvre les mécanismes moléculaires du développement du cancer: le cycle cellulaire; la stabilité du génome; les oncogènes; les g
David Richard HarveyEnseignement et PhD Doctorant·es actuel·les Ethan Daniel Tregidga, Felix Francisco Vecchi Cours Lecture series on scientific machine learning PHYS-754 Ce cours présente des travaux sur la façon dont les questions scientifiques peuvent être abordées à l'aide de l'apprentissage automatique. L'apprentissage automatique permet d'extraire des connaissances à partir de données de manière automatisée. Nous apprendrons à partir d'exemples concrets.
Christoph KochEnseignement et PhD Doctorant·es actuel·les Léonard Léchot, Zhekai Jiang, Hanbit Lee A dirigé les thèses EPFL de Immanuel Trummer, Aleksandar Vitorovic, Milos Nikolic, Daniel Lupei, Mohammed El Seidy, Ioannis Klonatos, Mohammad Dashti Rahmat Abadi, Amir Shaikhha, Lionel Parreaux, Sachin Basil John, Zilu Tian A co-dirigé les thèses EPFL de David Kozhaya Cours Making intelligent things A CS-358(a) Le cours vise à enseigner le prototypage d'artefacts physiques intelligents et à résoudre des d
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