|Assistant HES, PhD student CS UNIGE
Imahn graduated from the University of Hamburg in September 2022. In his MSc thesis, he worked on the use of high-dimensional normalizing flows to emulate high-granularity calorimeter showers. This work has direct relevance for the particle physics community, e.g. at CERN.
Besides the use of machine learning in physics, Imahn is also very interested in pure machine learning, including, but not limited to computer vision and natural language processing.
Imahn is currently working on simulation-based (likelihood-free) inference and deep generative models.