I am a Machine Learning researcher interested in Data Science and Artificial Intelligence; and an advocate of open science, open source, and open data. I am currently pursuing a PhD at the LTS2 Signal Processing laboratory of EPFL under the supervision of Prof. Pierre Vandergheynst. My current research interest is the automatic modeling, analysis and understanding of irregularly structured data, for example data lying on transportation, energy, social or brain networks. To this end, I am developing Deep Learning for data structured by arbitrary graphs, which are versatile representations of heterogeneous pairwise relationships. Besides research I am teaching practical Data Science, either by preparing and giving exercises for a master course at EPFL or a block course targeted at industrial practitioners. I used to maintain a digital lab notebook with notes as well as relevant tools, datasets, groups, events or courses.
Before starting a PhD in September 2015 I obtained a MSc in Electrical and Electronic Engineering at EPFL with a focus in Information Technologies and a minor in Computational Neurosciences. During that time I was a research assistant at LTS2 as well as a software engineer at Infoteam. Before that I obtained a BSc in Electronic Engineering from the engineering school of Fribourg after a thesis at the Physics Department of the Lawrence Berkeley National Laboratory and an ERASMUS in Munich, Germany. My career started by a vocational training as an electronics specialist working in aerospace at Meggitt. See my academic CV or LinkedIn for more details about my education or professional experience.