CS-448: Sublinear algorithms for big data analysisIn this course we will define rigorous mathematical models for computing on large datasets, cover main algorithmic techniques that have been developed for sublinear (e.g. faster than linear time) data
EE-567: Semiconductor devices IIStudents will learn about understanding the fundamentals and applications of emerging nanoscale devices, materials
and concepts. Remark: at least 5 students should be enrolled for the course to be giv
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
ME-427: Networked control systemsThis course offers an introduction to control systems using communication networks for interfacing sensors, actuators, controllers, and processes. Challenges due to network non-idealities and opportun
MSE-421: Statistical mechanicsThis course presents an introduction to statistical mechanics geared towards materials scientists. The concepts of macroscopic thermodynamics will be related to a microscopic picture and a statistical
CS-119(c): Information, Computation, CommunicationL'objectif de ce cours est d'introduire les étudiants à la pensée algorithmique, de les familiariser avec les fondamentaux de l'Informatique et de développer une première compétence en programmation (
PHYS-758: Advanced Course on Quantum CommunicationThe aim of this doctoral course by Nicolas Sangouard is to lay the theoretical groundwork that is needed for students to understand how to take advantage of quantum effects for communication technolog
