Advancing Machine Learning for Signal Processing
Prof. Klaus-Robert Müller speaks about machine learning applications in physics, chemistry, and medicine
The 33rd annual "IEEE International Workshop on Machine Learning for Signal Processing" (MLSP) in Rome (September 17th - 20th, 2023) brought together experts and researchers to discuss the latest advancements in machine learning for signal processing. The conference highlighted current research trends. In his keynote “Machine Learning for the Sciences – toward understanding” BIFOLD Director Prof. Klaus-Robert Müller shared his expertise in machine learning applications in physics, chemistry, and medicine. He specifically discussed the potential for extracting information from nonlinear machine learning models to further our understanding. He also touched on perspectives and limitations in the field. Other keynote speakers included Prof. José C. Príncipe (University of Florida, USA), Prof. Mihaela van der Schaar (University of Cambridge, UK), and Prof. Stefanos Zafeiriou (Imperial College London, UK).
In addition Klaus-RobertMüller participated in a panel discussion on "Explainable and Reliable Machine Learning in Signal & Data Science" alongside Prof. Tülay Adali (University of Maryland Baltimore County, USA), Prof. David Miller (Pennsylvania State University, USA), and Prof. Sijia Liu (Michigan State University, USA).
This year's conference was organized by Symposia Srl, with support from the Electronics and Telecommunications Engineering department at Sapienza University of Rome, the Department of Information Engineering and Mathematics at the University of Siena, the IEEE Signal Processing Society Italian Chapter, Convention Bureau Italia, ICCA, MPI Italia chapter, Federcongressi & Eventi, and Convention Bureau Roma & Lazio.
The MLSP program in detail: https://2023.ieeemlsp.org/wp-content/uploads/2023/09/IEEE-MLSP-2023-Technical-Program-2.pdf
