Antonia Kiel

Antonia Kiel is a PhD student working on the intersection of seismology and machine learning. Her research focuses on detecting different types of icequakes in Antarctica, using machine learning techniques to link these events to various processes active in the region. The goal is to gain deeper insights into ice dynamics, especially in the context of climate change. During her Master’s, she worked as a student researcher within the CLiCCS project, where she monitored groundwater in urban Hamburg using a combination of seismic interferometry, temperature data, and soil moisture content. Her Master’s thesis, part of the WAVE initiative, involved clustering different seismic noise sources in the urban area using unsupervised learning on DAS data.