Menu Chiudi

Topics of the School

Covered areas include (but are not limited to):

  • Design and development of biophotonic devices;
  • Biophotonic imaging;
  • Complexity in biophotonic systems;
  • Complexity in new materials, devices and emerging components such as micro-resonators and plasmonic nanostructures;
  • Artificial Intelligence (AI):
    • Statistics for Machine Learning;
    • Introduction to programming languages in the field of AI (Python, R) of interest in Biophotonics, and the best known libraries (scikit learn, Keras, Tensorflow, etc.);
    • machine learning;
    • Deep learning:
      • Convolutional Neural Networks (CNN);
      • Neural networks for temporal signals (RNN, LSTM, Transformers);
      • Auto encoders;
      • GAN;
      • Graph Neural Networks;
      • Reinforcement Learning;
      • Transfer Learning, Data augmentation, etc.;
  • Applications of AI for the design of biophotonic sensors;
  • Applications of AI for the analysis of biophotonic data;
  • Introduction to Explainability, Interpretability, Trustworthy.