Teaching Activities (Enseignements)

I teach the following courses:

Sûreté de fonctionnement et Retour d'expériences ( Reliability and Feedback Data Collection) ,
4th Year of Engineering in Management opérationnel Maintenance et Maîtrise des risques (M3)

Introduction to Deep Learning and Artificial Intelligence (5th year, Ingénierie de l’Information et des Systèmes (FISE & FISA) :

  • Theory: Basics, ANN, CNNs, RNNs and LSTM.
  • Practicals:  In Jupyter notebook, ANN: classification MNIST data, MNIST fashion data; CNN based:  CIFAR data classification, LSTM based:  prediction of time series
  • Slides available at request.
  • Student Feedback ( in French) 2019-20, 2020-2021,

Introduction to Reinforcement Learning and Deep Reinforcement Learning for Control

  • Theory:  Basics, Markov Decision Processes, Dynammic Programming, Model free control (SARSA and TD control), Function Approximation (Deep Neural netowrks), 
  • Deep reinforcement Leanring ( DQN and DDPG).
  • Environments solved in Tutorials (OpenAI gym based Environments)

Cartpole, Inverted Pendulum and Bipedal Walker

Decision support and Artifical Intelligence for Predictive Maintenance (5th Year, M3)

  • Decision support ( multi-criteria decision making): AHP, TOPISIS
  • Deep Neural networks for decision: ANNS RNNs
  • Deep Learning based Prognostics for Predictive maintenance:  CM1

Digital Signal processing (Traitement du signal numérique),  4th Year, Tutorials and Practicals (TD et TPs) , M3)

Control of Mobile Robots (5A IA2R Parcours SIA)
Lab 1: The QCAR (Autonomous Car),

Lab 2: The QBOT (differential drive robot by Quanser)

Lab3: The 3Pi+ Robot

Lab4: The Zumo robot