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.
Amaury Pierre Jiezhi WeiExpertise
Deep Learning, Computer Vision, Physics Informed Machine Learning, Graph Neural Networks
Amaury a obtenu son Master en Robotique de l'Ecole Polytechnique Federale de Lausanne (EPFL) en 2021. Avant de rejoindre IMOS, il a travaillé pendant plusieurs années en tant que Software Engineer chez Logitech Europe S.A. dans le domaine de la Réalité Virtuelle et Augmentée. Il a développé des algorithmes de 6DoF tracking pour appareils portables, développé le firmware et conçu la stratégie de testing industr
Johanni Michael BreaEnseignement et PhD Doctorant·es actuel·les Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Cours Biological data science II : machine learning BIO-322 Les étudiants comprennent les concepts et méthodes de base d'apprentissage automatique. Ils savent les décrire en termes mathématiques et ils savent les appliquer aux données en utilisant un langage de haut niveau (julia/python/R). Intelligence artificielle et société HUM-286 Ce cours intègre les SHS avec les sciences de l'
Isabella Di LenardoPh.D. in Theories and Art History. Isabella di Lenardo is senior scientist in Digital Humanities and Urban History. Her research activity is focused on digital tools and methods applied to Urban History. She is an expert in ancient cartography, city representations, cadastral sources interpreted through digital modeling, extraction and analysis systems.She's also interested in network analysis questioning the production and circulation of artistic and architectural knowledge in Europe XVIth – XVIIIth centuries in particular on North-South relationships and influences. The development of collaboration projects with European institutions and the activity carried out on various initiatives supported by the European Commission have allowed her to acquire specialism in the field of science applied to heritage, developing in particular specific skills for the enhancement of Cultural Heritage through digital tools. She leads projects in collaboration with Bibliothèque national de France (Paris), Institut National d’Histoire de l’Art (Paris), Ecole nationale des chartes (Paris), Université Paris I Panthéon-Sorbonne, Centre Allemand d’Histoire de l’Art (Paris), Musée du Louvre, Archives Nationales de Paris, Bibliothèque Historique de la Ville de Paris, Réunion des Musées Nationaux. She supervised all the urban modeling simulations for the Venice Time Machine project and acted as content curator for all the exhibitions (Venice Biennale, Grand Palais-Paris, Datasquare - ArtLab-Lausanne, Museo Correr-Venice). Head of “Replica” project : digitizing 1 million photos of artworks in the Fondazione Giorgio Cini (Venice) and visual patterns extraction through a search engine for visual similarities. She has a Ph.D in Art History and also studied Archaeology and Urban Studies. She has published essays and articles about Venetian Art and Urban History and participated in many Art exhibitions in European museums. She coordinated summer schools and workshops about Digital Tools for Art History and Urban History. She attended conferences on digital methods for History in universities and patrimonial institutions.
Adam James ScholefieldAdam Scholefield received the MEng in Electric and Electronic Engineering from Imperial College London in 2007.After a brief interuption of studies to compete in the Olympic Games, he received the PhD from the Communications and Signal Processing Group of Imperial College in 2013. His thesis was titled “Quadtree Structured Approximation Algorithms” and focused on image approximation algorithms with applications in image restoration.Since June 2014, he has served as a postdoctoral researcher in the Audiovisual Communications Laboratory (LCAV) at EPFL.
Jan WienoldEnseignement et PhD Doctorant·es actuel·les Hanieh Khodaei Tehrani, Chui Ling Yuen A co-dirigé les thèses EPFL de Mandana Sarey Khanie, Kynthia Chamilothori, Giorgia Chinazzo, Geraldine Cai Ting Quek, Stephen William Wasilewski, Sneha Jain Cours Comfort and architecture: sustainable strategies AR-442 Ce cours offre une vue d'ensemble sur les évaluations de confort dans la conception architecturale et propose des stratégies passives et de basse énergie adaptées à assurer la meilleure qualit
Gabriel AeppliEnseignement et PhD A dirigé les thèses EPFL de Dmitrii Usanov
Babak RahmaniI am a PhD student in Electrical Engineering department of EPFL where I am advised by Christophe Moser. I also work closely with Demetri Psaltis on Machine learning and its applications in inverse problems, information retrieval and control systems. Prior to joining EPFL, I graduated from Sharif University of Technology, Iran with a M.Sc. and Tehran University, Iran with a B.Sc. both in Electrical Engineering. My goal is to build robust and reliable machine learning algorithms for controlling real-world complex systems in various disciplines ranging from communication, imaging systems to neuroscience and robotics.Please visit my Google Scholar (link above) for an updated list of my publications.
Chen LiuI am a PhD candidate at the School of Computer and Communication Sciences (IC), École Polytechnique Fédérale de Lausanne (EPFL), supervised by Prof. Sabine Süsstrunk and co-supervised by Dr. Mathieu Salzmann. Previously, I obtained my Master Degree from École Polytechnique Fédérale de Lausanne (EPFL) in 2017 and Bachelor Degree from Tsinghua University in 2015, both in Computer Science.
