Jérémy Alain La Scala-JayetJérémy La Scala is a PhD candidate in Learning Sciences at the école Polytechnique Fédérale de Lausanne. He received a Bachelor and a Master of Science in Microengineering from the same institution where he specialised in low-power embedded systems for the Internet of Things. His current research interests lie in digital affordances for supporting design and project-based learning, especially in engineering education. In particular, he investigates how web-based collaborative applications helps in scaffoldi
Livia Eleonora Bove KadoExpertise
Member of the Scientific Council of the Institute de Physique CNRS since 2018Member of the Transition énergétique et changements globaux, Working Group CNRS, CS INP Representative since 2021Member of the Editorial Board Sapienza University Press (Italy), Senior Editor for the Natural Science Division since 2020Member of the European High-Pressure Research Group Committee since 2018Member of the EPS- Liquid Matter Committee since 2018Chair Liquids and Glasses ILL Panel 2016-2020 Co-editor of Fronte
Roland John TormeyI am a sociologist and learning scientist researching and teaching on engineering education. I'm particularly focused on the roles of emotion and self-regulation in engineering teaching and learning. My profile is accessible here.
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.
Cécile HardebolleTravail en cours
Responsible information systems (https://go.epfl.ch/digitalethics), ethical skills Jupyter notebooks for education (https://go.epfl.ch/notebooks), digital skills, computational thinkingTransversal/professional skillsEngineering design skillsFlipped classrooms Project-based learning
Formation Doctorat | Informatique 2006 – 2008 Université Paris-Sud XI, France Dirigée par Prof. Guy Vidal-Naquet Diplôme d'Ingénieur | Génie Electrique, spécialisat Berend SmitEnseignement et PhD Doctorant·es actuel·les Anastasia Blokhina, Raluca-Ana Kessler, Seyed Amirmohammad Elahi, Juliette Veronique Schleicher, Yutao Li, Xin Jin, Sara Bassetta, Beatriz Bueno Mouriño A dirigé les thèses EPFL de Samantha Lynn Anderson, Daniele Ongari, Andrzej Gladysiak, Seyedmohamad Moosavi, Arunraj Chidambaram, Bardiya Valizadeh, Stavroula Kampouri, Fatmah Ebrahim, Fatma Pelin Uran, Andres Adolfo Ortega Guerrero, Kevin Maik Jablonka, Elias Moubarak, Sauradeep Majumdar, Miriam Jasmin Pougin,
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'
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
