Teaching

2016-2017

  • Advanced Machine Learning, Cycle Master et Master Spécialisé Big Data, Télécom ParisTech
    Advanced machine learning methods : metric learning, large-scale kernel methods, graph-based learning. 18 hours of lectures and lab sessions (taught in French).
  • Certificat d’Études Spécialisées Data Scientist, Télécom ParisTech
    Introduction to supervised learning, Support Vector Machines. 14 hours of lectures and lab sessions (taught in French).
  • Lecture on Learning Similarity and Distance Functions, Pre-doc Summer School on Learning Systems
    Introduction to similarity and distance metric learning at a summer school targeting pre-doc students organized at ETH Zurich. 1.5 hours of lectures (taught in English).
  • Lecture on Graph Mining, Allianz France
    Introduction to graph mining and machine learning in graphs targeted to Allianz professionals, as part of a series of 7 lectures on data science. 3 hours of lectures (taught in French).

2015-2016

  • Advanced Machine Learning, Cycle Master et Master Spécialisé Big Data, Télécom ParisTech
    Advanced machine learning methods : distributed optimization, metric learning, large-scale kernel methods, graph-based learning. 21 hours of lectures and lab sessions (taught in French) and organization of a data challenge with the company Morpho on the topic of rank aggregation for facial recognition.
  • Certificat d’Études Spécialisées Data Scientist, Télécom ParisTech
    Introduction to supervised learning, Support Vector Machines. 10 hours of lectures and lab sessions (taught in French).

2014-2015

  • Advanced Machine Learning, Cycle Master et Master Spécialisé Big Data, Télécom ParisTech
    Advanced machine learning methods : stochastic approximation, distributed algorithms, structured prediction, large-scale kernel methods. 15 hours of lab sessions (taught in French) and organization of a data challenge with the company Morpho on the topic of metric learning for facial recognition.
  • Machine Learning and Data Mining, Cycle Master et Master Spécialisé Big Data, Télécom ParisTech
    Introduction to machine learning and data mining : Python programming, k-nearest neighbors, perceptron, classification and regression trees, large margin and kernel methods, ensemble learning and unsupervised learning. 24 hours of lab sessions, taught in French.

2012-2013

  • Design and Analysis of Algorithms, Master Erasmus-Mundus CIMET, University of Saint-Etienne
    Introduction to C programming, divide-and-conquer algorithms, dynamic programming, graph algorithms. 22 hours of lab sessions with student projects, taught in English.

2011-2012

  • Pattern Recognition, Master Erasmus-Mundus CIMET, University of Saint-Etienne
    Introduction to convex optimization, support vector machines (SVM) and their applications. 20 hours of lectures, tutorials and lab sessions, taught in English. In charge of the course unit.
  • Design and Analysis of Algorithms, Master Erasmus-Mundus CIMET, University of Saint-Etienne
    Introduction to C programming, divide-and-conquer algorithms, dynamic programming, graph algorithms. 22 hours of lab sessions with student projects, taught in English.
  • Object-Oriented Programming, Licence professionnelle ATII par alternance, IUT de Saint-Etienne
    Introduction to object-oriented programming and Java. 21 hours of lectures, tutorials and lab sessions taught in French to students in cooperative education (work-based learning). In charge of the course.
  • Introduction to Office Tools, L1 Sciences Technologie Santé, University of Saint-Etienne
    Introduction to information technology : Internet, word processing, HTML, spreadsheet and presentation applications, databases. 12 hours of lab sessions, taught in French.

2010-2011

  • Design and Analysis of Algorithms, Master Erasmus-Mundus CIMET, University of Saint-Etienne
    Introduction to C programming, divide-and-conquer algorithms, dynamic programming, graph algorithms. 22 hours of lab sessions with student projects, taught in English.