Hannah Marienwald

Hannah Marienwald is a doctoral researcher at the Technical University of Berlin (TU Berlin), affiliated with the Machine Learning group and BIFOLD – Berlin Institute for the Foundations of Learning and Data. She previously worked as a research associate at the Institute of Mathematics, Mathematical Statistics and Machine Learning at the University of Potsdam, collaborating with BZML and the Data Engineering Systems group at the Hasso-Plattner Institute.

She holds a B.Sc. (2016) and M.Sc. (2019) in Computer Science from TU Berlin, with a focus on Machine Learning, statistics, probability theory, and econometrics. Her research interests include Kernel Methods, High-Dimensional Statistics, and Expectation Estimation, particularly in the context of Kernel Mean Embeddings.

Her work on high-dimensional statistical methods and kernel techniques has led to contributions such as the publication at AISTATS 2021, advancing methodologies for multi-task learning and kernel-based estimation.