Deutsch Intern
    Faculty of Physics and Astronomy

    Würzburg ToCoTronics Colloquium

    "Application of machine mearning to solid state spectroscopy and astroparticle data analysis"
    Date: 03/16/2023, 4:15 PM - 6:00 PM
    Category: Kolloquium
    Location: Hubland Süd, Geb. P1 (Physik), HS P (Röntgen HS)
    Organizer: SFB 1170 ToCoTronics
    Speaker: Eleonora Barbano - Fakultät für Physik und Astronomie, Universität Würzburg

    Machine Learning (ML) is a field of Artificial Intelligence based on coding predictive models that can find internal patterns and relations in data features. ML algorithms are used today in several fields of physics, engineering, and technology, and have proven to be highly efficient in domains where standard computational approaches hit their limits.

    In this seminar, I will introduce some key concepts of ML (e.g., types of “learning", classification/regression problems, training of models) and give an overview of the main ML algorithms. I will focus on Neural Networks (NNs) that are among the most powerful and most employed methods in supervised learning.

    Finally, I will discuss some pertinent examples of NNs applied to the field of spectroscopy (e.g., denoising of 2D detectors, pattern recognition) and of astroparticle physics (e.g. binary classification of e/cosmic rays, clustering of astroparticle data).

    This talk is also broadcasted via zoom. To enter the meeting, follow the link: