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•
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
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
Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
Allison Marie BurnsEnseignement et PhD Cours Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Due to its success, this course will take place from 1st to 5th September 2025 in room AAC 0 20.It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data. Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b)
Emily Clare GrovesEmily is a digital designer, researcher and educator. She has a BSc in Human Sciences from University College London, an MA in Information Experience Design from the Royal College of Art, and an MAS in Design Research for Digital Innovation from the EPFL ECAL Lab. Her interests lie at the intersection of culture, technology and food.
Andy BushbyEnseignement et PhD Cours CCMX Advanced Course - Instrumented Nanoindentation MSE-656
Nicholas X. RandallEnseignement et PhD Cours CCMX Advanced Course - Instrumented Nanoindentation MSE-656
Edoardo ChiarottiEnseignement et PhD Cours Data Science & Causal Inference for Sustainability MGT-499 Ce cours explore les grands enjeux climatiques à travers les données. Les étudiants apprendront à les traiter, analyser et interpréter avec rigueur, à l'aide de Python, pour tirer des conclusions solides sur la durabilité et éviter les pièges courants.
Mathias Benjamin ThoenigEnseignement et PhD Cours Economics for challenging times MGT-494 Ce cours analyse les grands enjeux socio-économiques -pauvreté, inégalités, changement climatique, mondialisation, migration, IA, etc.- et forme les étudiants aux méthodes quantitatives en économie empirique et à l'élaboration de solutions adaptées aux économies de marché.
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