Polytech Nantes (2022-2023)

• Machine Learning for Computer Vision (Visual Computing Master) Machine learning basics; neural network; MLP; gradient methods; backpropagation; deep learning; CNN; RNN; applications in computer vision.
  Slides, Lab 1 material, Lab 2 material

• Perceptual Computing (Visual Computing Master)
  Human visual system; physiology of vision; perceptual principles; experimental methodology; visual attention; models of visual attention; image quality assessement.
  Slides, Lab 1, Lab 2, Lab 3, Project

• Data 2 (Master Cultures Numériques)
  Introduction to machine learning; supervised vs non-supervised learning; regression vs classification problems; clustering algorithms; decision trees; SVM; complex data handling; introduction to neural nets.
  Clustering; Lab 1; Classification; Lab 2; Lab 3

ESIR (2018-2020)

• Artificial Intelligence
  Machine learning strategy; introduction to neural nets; introduction to deep learning; word embeddings; RNN; CNN; Markov decision processes; reinforcement learning.
• Databases
  Relational model; relational calculus; conception (normalisation and modeling); ER model; complex queries.

ISTIC (2018-2020)

• Introduction to programming and Python

Student Supervision

Master students

• Badr Tahri-Joutei, “Explicabilité de prédiction automatique d’actions humaines sur graphe de scène” (March-Aug. 2023)
• Yuan Feng, “Who looks at what ? Distinguishing and predicting personnal gaze behavior”, Polytech Nantes (Feb.-July 2023)
• Jun Zhang, “Data augmentation for deep visual saliency models”, Polytech Nantes (Feb.-July 2022)
• Supervisor of several Master students on their research projects