Pasquale ScarlinoI obtained my master's degree in Physics at the University of Salento, Lecce (Italy) in February 2011. During 2006-2011, I have also been a student of Scuola Superiore ISUFI (SSI). SSI is one of six schools of excellence established in Italy to develop the intellectual capital in technological and social sciences. I conducted an external Master thesis project during an 8 months internship in the Quantum Transport Group at TU Delft, under the supervision of Prof. L.M.K. Vandersypen. There, I implemented the Quantum Point Contact Radio-Frequency Reflectometry technique, which allows increasing the single-shot electron spin readout bandwidth and is currently routinely used in the group.I obtained my Ph.D. degree in February 2016, in the Spin Qubits group of Prof. L.M.K. Vandersypen at the Kavli Institute of Nanoscience-Qutech (TU Delft). During my Ph.D. I have been leading the Si/SiGe spin qubits project, collaborating with the M. Eriksson Group at Wisconsin University. In parallel, I have been working on other different projects, in particular with GaAs depletion quantum dots, high impedance superconducting resonators, and surface acoustic wave resonators. I have been working as a Postdoc fellow in the group of Prof. A. Wallraff (Quantum Device Lab) at ETH Zurich. My main project, in collaboration with the group of Prof. K. Ensslin and Prof. T. Ihn, consisted in integrating semiconductor and superconductor technologies. Realizing a well-controlled interface between the semiconductor and superconductor-based quantum information technologies may allow harnessing the best of both device architectures, for example by providing an interface between strongly coupled charge state and high coherence spin states. Furthermore, it enables the possibility to explore light/matter hybridization in a class of solid-state systems and regimes that are new in the context of quantum optics.From June 2019 till September 2020, I have been a Senior Researcher at Microsoft Station Q Copenhagen and at the Center for Quantum Devices in Copenhagen, focusing on developing semiconductor-superconducting hybrid hardware for topologically protected quantum computation.Since October 2020, I am a tenure track Assistant Professor of Physics in the School of Basic Sciences at the EPFL where I founded the Hybrid Quantum Circuit (HQC) laboratory.
Yves PerriardYves Perriard was born in Lausanne in 1965. He received the M. Sc. in Microengineering from the Swiss Federal Institute of Technology - Lausanne (EPFL) in 1989 and the Ph D. degree in 1992. Co-founder of Micro-Beam SA, he was CEO of this company involved in high precision electric drive. Senior lecturer from 1998 and professor since 2003, he is currently director of Laboratory of Integrated Actuators. His research interests are in the field of new actuator design and associated electronic devices. In 2009, he is appointed Vice-Director of the Microengineering Institute in Neuchâtel until 2011. In 2013 the Federal Council has named him the the CTI commission in Bern. In 2014 he is appointed guest professor at Zhejiang University in China. In 2017, the lab is granted by the Werner Siemens Foundation of an amount of 12 millions CHF in order to set up a new Center for Artificial Muscules. Since 2018, he is Expert with Innosuisse, the new Swiss Innovation Agency. http://scholar.google.com/citations?hl=fr&user=V2onuO8AAAAJ https://actu.epfl.ch/news/a-12-million-franc-donation-to-create-a-center-for/ Yoan René Cyrille CivetEnseignement et PhD Doctorant·es actuel·les Simon Holzer A co-dirigé les thèses EPFL de Dan Shi, Jasha Poliakine, Jonathan Chavanne, Quentin Philippe Mario De Menech Cours Electrotechnique I MICRO-100 Le cours aborde les bases des circuits électriques composés d'éléments linéaires, en régime continu. Une série de méthodes de transformations sera traitée.Le régime alternatif est traité en fin de semestre (calcul complexe).De nombreux exemples ainsi que des démonstrations illustrent le cours
Pierre-Emmanuel DessemontetExpertise
- Géographie urbaine et suburbaine, géographie économique et économie spatiale- Méthodes statistiques spatiales appliquées à la géographie humaine, y-compris méthodes spatiales explicites (autocorrélation, etc...)- Connaissances encyclopédiques des méthodes et relevés statistiques et recensements en Suisse et en Europe, depuis 1940.
Expertise
- Géographie urbaine et suburbaine, géographie économique et économie spatiale- Méthodes statistiques spatiales appliquées à la géographie humaine, y-compris
Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
Pierre DillenbourgAncien instituteur primaire, Pierre Dillenbourg obtient un master en Sciences de lEducation (Université de Mons, Belgique). Dans son projet de master en 1986, il est l'un des premiers au monde à appliquer les méthodes de 'machine learning' à l'éducation, afin de développer un 'self-improving teaching system'. Ceci lui permettra de débuter une thèse de doctorat en informatique à l'Université de Lancaster (UK) dans le domaine des applications éducatives de lintelligence artificielle. Il a été Maître dEnseignement et de Recherche à lUniversité de Genève. Il rejoint l'EPFL en 2012, où Il fut le directeur du Centre de Recherche sur l'Apprentissage, la formation et ses technologies(CRAFT), puis académique du Centre pour l'Education à l'Ere Digitale (CEDE) qui met en oeuvre la stratégie MOOC de l'EPFL (plus de 2 millions d'inscriptions). Il est actuellement professeur ordinaire en technologies de formation aux sein de la faculté Informatique et Communications et dirige laboratoire d'ergonomie éducative (CHILI). Depuis 2006, il a aussi été le directeur de DUAL-T, la 'leading house' dédiée aux technologies pour les systèmes de formation professionnelle duale. Il a fondé plusieurs start-ups dans l'éducation et rejoint plusieurs conseils d'administration. En 2017, Il a créé avec des collègues le 'Swiss EdTech Collider', un incubateur qui rassemble 80 start-ups dans le domaine des technologies éducatives. En 2018, ils ont lancé LEARN, le centre EPFL pour les sciences de l'apprentissage, lequel regroupe les initiatives locales en innovation éducative. Pierre est un 'inaugural fellow of the International Society of Learning Sciences'. Il est actuellement le Vice-Président Associé pour l'Education à l'EPFL.
Dario FloreanoProf. Dario Floreano is director of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology Lausanne (EPFL). Since 2010, he is the founding director of the Swiss National Center of Competence in Robotics, a research program that brings together more than 20 labs across Switzerland. Prof. Floreano holds an M.A. in Vision, an M.S. in Neural Computation, and a PhD in Robotics. He has held research positions at Sony Computer Science Laboratory, at Caltech/JPL, and at Harvard University. His main research interests are Robotics and A.I. at the convergence of biology and engineering. Prof. Floreano made pioneering contributions to the fields of evolutionary robotics, aerial robotics, and soft robotics. He served in numerous advisory boards and committees, including the Future and Emerging Technologies division of the European Commission, the World Economic Forum Agenda Council, the International Society of Artificial Life, the International Neural Network Society, and in the editorial committee of several scientific journals. In addition, he helped spinning off two drone companies (senseFly.com and Flyability.com) and a non-for-profit portal on robotics and A.I. (RoboHub.org). Books
Manuale sulle Reti Neurali, il Mulino (in Italian), 1996 (first edition), 2006 (second edition)Evolutionary Robotics, MIT Press, 2000
Bio-Inspired Artificial Intelligence, MIT Press, 2008
Flying Insects and Robots, Springer Verlag, 2010
Tuong-Van NguyenEnseignement et PhD Cours Energy conversion and renewable energy ME-409 Le cours donne un aperçu (i) du système énergétique actuel, (ii) des principes techniques des systèmes de conversion d'énergie (fossiles, nucléaires et renouvelables), et (iii) de leurs aspects économiques et environnementaux. La transition énergétique : défis et opportunités HUM-293 Ce cours porte sur la transition énergétique d'un système fondé sur les énergies fossiles vers un modèle reposant sur des s
Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Mengjie ZhaoMengjie Zhao holds degrees in Computational Mechanics (MSc) with honors track and in Engineering Science (BSc) from the Technical University of Munich (TUM).
From the early years of her studies, Mengjie was fascinated by the modeling of multiphysics and multiscale systems. As a student research assistant at TUM and research intern at International Centre for Numerical Methods in Engineering (CIMNE), she gained a solid understanding of both the theoretical and algorithmic fundamentals as well as a wide range of applications. Through the BGCE project with the Elitenetzwerk Bayern (ENB), which dealt with the mesh sensitivity prediction with a deep neural network, she realized that leveraging data could bring physical modeling far beyond the current computational limits. Later, in her master's thesis in cooperation with Siemens, she turned to the reduced-order modeling with enforced physical invariants, which showed better accuracy and generality.
In her Ph.D., she would like to step towards a further combination of deductive research (modeling and simulation) and inductive (data-driven) research by embedding physics into machine learning.
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