Virginia LangVirginia started in the medical research field as a Coordinator of Research at the Clinical Research Unit Kennedy Institute of Johns Hopkins Medical Center. She was responsible for the initiation, coordination, and management and/or analysis of research projects in the Clinical Research Unit. These projects were funded by various Federal Government Agencies. Subsequent to Johns Hopkins Medical Center, Virginia entered the field of Human Factors through the doctoral program at SUNY Binghamton. Virginia held a fellowship at the Aeromedical Research Laboratory of the United States Air Force at Wright-Patterson AFB, Dayton, Ohio and a fellowship at NASA. Her research dealt with cognitive factors that differentially affect the characteristics of visual displays. Applications of this research are directly related to various medical devices and software applications providing Medical Device Human Factors by HirLan clients with 30 years of Human Factors experience. In addition, Virginia has extensive experience in the areas of product design, Customer Centered Participatory Design processes, and product lifecycle management. She is also known in the Human Computer Interaction and Usability Communities for her innovative techniques for collecting and incorporating user/customer feedback throughout the product lifecycle. In July 2014, Virginia founded and established the HirLan Institute of Human Factors with labs in Carlsbad, California and a Consortium arrangement in London, UK. HirLan supports Top Ten pharma/medical device companies, as well as, start-ups with consulting and testing services. These services are in conjunction with their clients’ FDA 510(k) and CE mark applications. Virginia holds a PhD in Cognitive-Experimental Psychology from SUNY Binghamton, and a Master of Science (ABT) in Applied Technology, Systems Science from SUNY Binghamton.
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
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•
Andrew James SontaExpertise
Human-building interaction, building energy, occupant behavior, sustainable design and planning, walkability, network analysis, machine learning, urban informatics, social systems.
Andrew Sonta is a tenure track assistant professor of sustainable civil engineering at EPFL. He directs the ETHOS Lab: Engineering and Technology for Human Oriented Sustainability. ETHOS is an interdisciplinary research group focused on using data-driven and computational tools to create interventions in the built envir
Stefana ParaschoEnseignement et PhD Doctorant·es actuel·les Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Cours Capitalizing on Uncertainty AR-809 Digital design and making: A critical introduction AR-503 Le cours présente des méthodes de conception et de fabrication numériques en combinant des compétences techniques avec des connaissances théoriques et une réflexion critique. Les sujets incluent: la programmation pour la conception, la fabr
Francisco Xavier Felix Martin Del CampoEnseignement et PhD Cours Material flow analysis and resource management ENV-501 Ce cours permet de maîtriser les bases des processus de production et consommation de matières et d'énergie. Les étudiants développent une analyse de flux de matières, l'appliquent à la gestion des ressources, aux activités économiques ainsi qu'à l'élaboration de politiques publiques.
Martin SchrimpfExpertise
NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]
Mission
Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
Andres Osorio SalazarExpertise
Robotics, advanced actuator design, soft actuators, sensor design, embedded systems, human-machine interface architecture, electronic-less control, mechanism design, additive and traditional manufacturing, industrial automation, process control, and fluid robotics.
Current Work
Smart Footwear for Diabetic Foot Care and Ulcer PreventionEvery 20 seconds, a person with diabetes has to face an amputation somewhere in the world. The main risk factor is high plantar pressure combined with foot nephropat
Antoine BosselutAntoine Bosselut is an assistant professor at EPFL. He leads the EPFL NLP group, which conducts research on natural language processing (NLP) systems that can model, represent, and reason about human and world knowledge.
Prior to joining EPFL, he was a postdoctoral researcher at Stanford University working in the
SNAP
and
NLP
groups and a young investigator on the
Mosaic
project at the
Allen Institute for AI
. He completed his PhD at the University of Washington.
Mats Julius StensrudEnseignement et PhD Doctorant·es actuel·les Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau A dirigé les thèses EPFL de Matias Janvin, Amit Sawant Cours Causal thinking MATH-352 Ce cours donnera une présentation unifiée des méthodes modernes d'inférence causale. Nous nous concentrons sur les concepts, et nous présenterons des exemples et des idées provenant de diverses disciplines scientifiques, notamment la médecine, l'informatique, l'ingénierie,
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
Yujia ZhangEnseignement et PhD Doctorant·es actuel·les Yuyan Su, Shulang Shen, Jiaqi Liu Cours Advanced microfabrication practicals MICRO-373 Ce TP permet une formation approfondie sur les méthodes avancées de micro et nanofabrication dans un environnement de salle blanche pour des applications sélectionnées, d'acquérir des connaissances plus approfondies sur les processus MEMS/NEMS, de travailler dans un petit groupe avec des doctorants/ MOOC: Micro and Nanofabrication (MEMS) - Fall MICRO-
Emmanuelle Brigitte Marie DavidMission
Candidate au Corps Administratif et Technique — Assemblée d'ÉcoleAprès six ans à la tête de l'EPFL Space Center — entre enseignement, associations étudiantes, recherche et innovation — j'ai une compréhension concrète de ce qui rend l'EPFL exceptionnelle, mais aussi de sa complexité et de son positionnement singulier. Je souhaite apporter cette perspective dans la gouvernance institutionnelle.Constructive par nature. Je suis orientée solutions, j'aime travailler avec des parties prenantes nombreuses
Du WenEducation PhD | Doctor of Philosophy, Mechanical Engineering 2020 – 2023 The University of Tokyo MEng | Master of Engineering, Power Engineering and Engineering Thermophysics 2016 – 2019 Xi’an Jiaotong University Bsc | Bachelor of Engineering 2012 – 2016 Xi’an Jiaotong University
Mirko MusaEnseignement et PhD Doctorant·es actuel·les Louise Cayroche, Antonio Magherini Cours Hydraulic engineering and infrastructures CIVIL-312 L'eau est indispensable à la vie, mais c'est aussi une force naturelle puissante. L'ingénierie hydraulique vise une gestion durable de l'eau pour l'approvisionnement, l'énergie et la protection.
Kai RenKai Ren received his Bachelor's degree in Electrical Engineering from the University of Victoria, and his Master's degree in Electrical and Computer Engineering from the University of British Columbia, Canada. His research interest is the safe motion planning of autonomous systems in uncertain and dynamic environments. His master's thesis investigated a safe and risk-aware Model Predictive Control framework under multimodal environmental uncertainties. Education M.ASc | Electrical and Computer Enginee
