Team
Prof. Dr. David Ruegamer
Associate professor
Associate Professor and Group Leader at LMU since summer 2023. Before David was Interim Professor at LMU Munich, RWTH Aachen, and TU Dortmund. He earned his PhD in Statistics in 2018 (supervisor Sonja Greven).
Marcel Arpogaus
PhD Student (co-supervised)
Marcel is PhD Student at University of Goettingen (supervisor Thomas Kneib) and works on multivariate transformation models.
Daniel Dold
PhD Student (co-supervised)
Daniel is PhD Student in the muniq.ai lab (co-supervisor Oliver Duerr) and works on uncertainty quantification in Bayesian neural networks.
Maarten Jung
PhD Student (co-supervised)
Maarten is a PhD student in the muniq.ai lab (co-supervisor Sonja Greven) and works on semi-structured extensions of conditional density regression models.
Chris Kolb
PhD Student (co-supervised)
Chris is PhD Student in the Statistical Learning and Data Science Group (supervisor Bernd Bischl) and works on sparsity in neural networks.
Yawei Li
PhD Student (collaborating)
Yawei is a PhD student in Statistical Learning and Data Science Group (supervisor Bernd Bischl) and works on uncertainty quantification and explainability of large language models.
Richard Paul
PhD Student (co-supervised)
Richard is a PhD Student at Forschungszentrum Jülich (supervisors Hanno Scharr and Katharina Nöh) and works on probabilistic live-cell imaging & analysis.
Tobias Pielok
PhD Student (co-supervised)
Tobias is a PhD Student in the Statistical Learning and Data Science Group (supervisor Bernd Bischl) and works on Bayesian deep learning and model-based optimization.
Lisa Wimmer
PhD Student (co-supervised)
Lisa is a PhD Student in the Statistical Learning and Data Science Group (supervisor Bernd Bischl) and works on uncertainty quantification in deep learning.
Qiwen Xu
PhD Student (co-supervised)
Qiwen is a PhD Student in the muniq.ai lab, the Machine Learning Consulting Unit (supervised by Dr. Andreas Bender) and the Mannheim Medical Faculty (supervised by Mate Maros). Currently, Qiwen's research focuses on generative models in the field of medical imaging, exploring deep learning approaches for data synthesis and enhancement.
