- Prior to joining EURECOM, Patrick Loiseau had been teaching in the areas of physics, computer architecture, probability and basic signal processing at Ecole Normale Superieure de Lyon, University of Versailles Saint-Quentin-en-Yvelines and University of California, Santa Cruz.
At EURECOM, he teaches Performance evaluation of computer systems.
G_Theory / Fall 2013 - Applied Game Theory
- This course is an introduction to game theory and its algorithmic aspects. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics and computer science in general.
NetEcon / Fall 2013 - Network Economics
- The course will introduce a number of topics in economic analysis of networks and network-based services.
- The basic method used will be game theory. The basics of game theory will be assumed to be known and the course will focus on applications to network economics.
- The main goal is to show how game-theory is used to analyze economics problems in networks, with a focus on modern research topics in network economics.
Perf / Spring 2013 - Performance evaluation of computer systems
- The objective of the course is to provide students with simple and efficient methods to analyze the performance of a system.
- Although studied methods rely on mathematical analysis (which will be sketched), the focus will be on the understanding of the methods and the situations in which they can be used (which methods should you use, what to expect, etc.).
- The first part of the course will be dedicated to analysis of performance data (from simulations or experiments); the second part will be dedicated to performance modeling.
- Examples of applications will be given in computer networks, computer systems and in other engineering areas.
Stat / Fall 2013 - Statistical data analysis
- The goal of the course is to provide students with simple and efficient statistical methods to analyze data. Such methods are of crucial importance in many situations as they allow to answer questions such as: 'Is this performance improvement significant?', 'What is the uncertainty on that result?', 'How can I predict a new output of my system based on measurements?', 'Which factors have a significant impact on the performance of my system?', and many more.
- Mathematical analysis underlying the presented methods will be sketched, but the main focus will be on the understanding of the methods and the situations in which they can be used (which method to use, what to expect, etc.).
- The course will present generic methods working for data from any application and not a specific domain of application. Examples will be given in different areas (computer networks, engineering, etc.).
- Best Student Demonstration award at ACM Sigmetrics/Performance 2009, for the demo "Automated traffic measurements and analysis in Grid'5000", with Romaric Guillier, Oana Goga, Matthieu Imbert, Paulo Goncalves and Pascale Vicat-Blanc Primet.