ENG-466: Distributed intelligent systemsThe goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing
and optimizing coordination strategies. The course is a well-balanced mixture of theory and practical activities. ...
PHYS-642: Statistical physics for optimization & learningThis course covers the statistical physics approach to computer science problems, with an emphasis on heuristic & rigorous mathematical technics, ranging from graph theory and constraint satisfaction to inference to machine learning, neural networks and st ...
COM-405: Mobile networksThis course provides a detailed description of the organization and operating principles of mobile and wireless communication networks, as well as the use of wireless signals for sensing and imaging. ...
MICRO-523: Optical detectorsStudents analyse the fundamental characteristics of optical detectors, their architectures, selected applications and case studies. Photoemissive devices, photodiodes, infrared and single-photon detectors are studied. CCD, CMOS and SPAD cameras are analyse ...
ME-422: Multivariable controlThis course covers methods for the analysis and control of systems with multiple inputs and outputs, which are ubiquitous in modern technology and industry. Special emphasis will be placed on discrete-time systems due to their relevance to digital and embe ...
QUANT-410: Microwave engineering in physicsThis course aims at teaching basic notions and tricks of microwave engineering to students with only an elementary knowledge of applied electromagnetism. Emphasis is made on topics that often arise in modern physics experiments, including quantum science a ...
BIO-449: Understanding statistics and experimental designThis course is neither an introduction to the mathematics of statistics nor an introduction to a statistics program such as R. The aim of the course is to understand statistics from its experimental design and to avoid common pitfalls of statistical reason ...
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...
AR-128: Building technology I, IIIntroduction à la technologie du bâti: défis environnementaux et sociétaux, exigences techniques et fonctionnelles du bâtiment dans la durée, équilibre statique des ossatures, matériaux de construction, détails d'assemblage et mise en oeuvre, stratégies de ...
EE-594: Smart sensors for IoTThis lecture provides insights in the design and technologies of Internet-of-Things sensor nodes, with focus on low power technologies. The lectures alternate every two weeks between sensing technologies of various kinds (prof. Ionescu) and their integrate ...
