ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica
EE-334: Digital systems designStudents will acquire basic knowledge about methodologies and tools for the design, optimization, and verification of custom digital systems/hardware.
They learn how to design synchronous digital cir
ME-436: Micro/Nano roboticsThe objective of this course is to expose students to the fundamentals of robotics at small scale. This includes a focus on physical laws that predominate at the nano and microscale, technologies for
MICRO-515: Evolutionary roboticsThe course gives an introduction to evolutionary computation, its major algorithms, applications to optimization problems (including evolution of neural networks), and application to design and contro
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
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
ME-326: Control systems and discrete-time controlCe cours inclut la modélisation et l'analyse de systèmes dynamiques, l'introduction des principes de base et l'analyse de systèmes en rétroaction, la synthèse de régulateurs dans le domain fréquentiel
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 technolog
