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-
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]
Alexander DittrichCurrent Work
My research interests are somewhere between neural networks with Hebbian plasticity, meta-reinforcement learning, and the control of rather unconventional soft robotic platforms like tensegrity robots.
Sahand Jamal RahiExpertise
- Biophysics- Statistical mechanics- Systems biology- Computational biology- Genetics
Enseignement et PhD Doctorant·es actuel·les Alisa Gross, Matthieu Schmidt, Marco Labagnara, Lorenzo Scutteri, Haozong Zeng A dirigé les thèses EPFL de Ahmad Sadeghi, Mahsa Barzegarkeshteli, Vojislav Gligorovski, Roxane Oesterle Cours Biophysics : physics of biological systems PHYS-302 Comprendre et utiliser la génétique des populations, la dynamique des populations, la théorie des réseaux et la
Martin Alois RohrmeierEnseignement et PhD Doctorant·es actuel·les Joris Monnet, Marina Borsodi-Benson, Xinyi Guan, Xiaoxuan Wang, Zeng Ren A dirigé les thèses EPFL de Fabian Claude Moss, Daniel Harasim, Christoph Finkensiep, Johannes Hentschel, Gabriele Cecchetti, Shuxin Meng Cours Digital musicology DH-401 Ce cours a pour but de familiariser les étudiants avec les thèmes principaux en musicologie digitale, ainsi que les approches et méthodes théoriques essentielles. Dans la partie pratique, les étudiants feron
Giancarlo Ferrari TrecateExpertise
Automatic control, Dependable control, Neural-network Control, Machine learning, Microgrids, Hybrid systems
Mission
See the webpage of the DECODE (Dependable Control and Decision) group.
Teaching & PhD PhD Students Laura Meroi, Julien Pallage, Nicolas Léo Pierre Kirsch, Simone Baratto, Daniele Martinelli, Riccardo Cescon, Jakob Nylöf, Sabri El Amrani Past EPFL PhD Students Pulkit Nahata, Mustafa Sahin Turan, Baiwei Guo, Jean-Sébastien Brouillon, Clara Galimberti, Andrea Martin, Muhammad Zakwan,
Guillaume Romain ObozinskiGuillaume Obozinski est Chef Data Scientist Adjoint au Swiss Data Science Center. Il a reçu le diplôme de doctorat en Statistiques de l'Université de Californie à Berkeley en 2009. Post-doc puis chercheur dans les équipes Willow et Sierra à l'INRIA / Ecole Normale Supérieure à Paris jusqu'en 2012, il a été chercheur à l'Ecole des Ponts ParisTech à Paris jusqu'en 2018. Ses domaines d'expertise sont principalement en apprentissage automatique, en statistique et en optimisation. Il a travaillé au fil du temps sur les méthodes d'apprentissage parcimonieux, les techniques d'optimisation pour l'apprentissage, les modèles graphiques probabilistes, l'apprentissage relationnel et les représentations vectorielles sémantiques. Il est intéressé par l'application de ces techniques à tous les domaines des data sciences, depuis la biologie computationnelle à l'analyse automatique d'images.
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
Shravan Tata RamalingasettyShravan Tata Ramalingasetty obtained his Mechatronics Bachelors in Engineering (B.E) degree from Manipal Institute of Technology, Manipal (2013). During his bachelors he worked on the thesis titled "Human Motion Analysis using Inertial Sensors" in collaboration with the Indian Institute of Technology (IISc), Bangalore. Later he continued working in IISc as Research Assistant with Computational Intelligence Laboratory(CInT) Lab on topics related to human bio-mechanics. Later he joined Technical University of Delft, Delft and graduated with Master of Science (M.Sc) degree in Bio-robotics (2016) after his competition of thesis titled "Cerebellum Inspired Computational Models for Robot Control". He then joined BioRob (2016) for his PhD funded by the Human Brain Project (HBP) to study the underlying mechanisms of locomotion in animals and humans.
