Welcome, Julius
Julius will work on machine-learning-assisted denoising algorithms for low-frequency vibrational spectroscopy, with the aim of reducing acquisition time while preserving analytically useful spectral information.
The project will address cases where faster acquisition can simply make analysis more efficient, as well as measurements where acquisition time is a fundamental limitation. This includes compositional characterization and spectroscopic mapping, where it may not be practical to record a sufficiently high-quality spectrum at every measurement point.
Julius joined the group in August 2026.