Olivier Lévêque
Senior Scientist
olivier.leveque@epfl.ch +41 21 693 81 12 http://ipgold.epfl.ch/~leveque/index.html
Citizenship: CH
EPFL IC IINFCOM LTHI
INR 132 (Bâtiment INR)
Station 14
1015 Lausanne
Web site: Web site: https://ipg.epfl.ch
Web site: Web site: https://ssc.epfl.ch
Web site: Web site: https://sin.epfl.ch
Fields of expertise
Information theory
Random matrices
Stochastic calculus
Random matrices
Stochastic calculus
Biography
Olivier Lévêque was born in Switzerland in 1971. He received the physics diploma from EPFL in 1995 and completed his PhD in mathematics at EPFL in 2001. Since then, he has been with the Laboratory of Information Theory at EPFL. He spent the academical year 2005-2006 at the Electrical Engineering Department of Stanford University, where he was appointed as lecturer. His research interests include stochastic analysis, random matrices, wireless communications and information theory.Publications
Infoscience publications
Infoscience
Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
IEEE Transactions on Information Theory. 2007. DOI : 10.1109/TIT.2007.905002.Scaling Laws for One and Two-Dimensional Random Wireless Networks in the Low Attenuation Regime
IEEE Transactions on Information Theory. 2007. DOI : 10.1109/TIT.2007.904979.Second-order hyperbolic S.P.D.E.'s driven by homogeneous Gaussian noise on a hyperplane
Transactions of the American Mathematical Society. 2006. DOI : 10.1090/S0002-9947-05-03740-2.Information-Theoretic Upper Bounds on the Capacity of Large Extended Ad Hoc Wireless Networks
IEEE Transactions on Information Theory. 2005. DOI : 10.1109/TIT.2004.842576.Second-order linear hyperbolic SPDEs driven by isotropic Gaussian noise on a sphere
Annals of Applied Probability. 2004. DOI : 10.1214/aop/1079021472.Teaching & PhD
Teaching
Communication Systems
Computer Science
Courses
Information, Computation, Communication
On one side, this course covers the concepts of algorithms, the representation of information, signal sampling and compression, and an overview of systems (CPU, memory, etc.). On the other side, an introduction to programming is given.
Information, Computation, Communication
The course objectives are to introduce the students to algorithmic thinking, to get them familiar with the foundations of communication and computer sciences and to develop a first set of skills in programming with the Python language.
Introduction to quantum computation
The course introduces the paradigm of quantum computation in an axiomatic way. We introduce the notion of quantum bit, gates, circuits and we treat the most important quantum algorithms. We also touch upon error correcting codes. This course is independent of COM-309.