Anna Krause

Dr.-Ing. Anna Krause is a researcher at the Chair of Data Science (Informatik X) within the Faculty of Mathematics and Computer Science at the University of Würzburg. She leads the Deep Learning for Dynamical Systems Group and has been actively involved in teaching at the university since 2019, including courses on Machine Learning for Time Series Analysis and Data Mining.

• Doctoral degree in Electrical Engineering (2019), University of Hannover
• Diploma in Electrical Engineering (2009), Technical University Dresden

Her research focuses on Environmental Sensing and Time Series Analysis, particularly on enhancing physics-based models using machine learning techniques for meteorological applications and sparse sensor networks. She has made significant contributions to explainable AI, climate modeling, and fraud detection systems.

Anna's recent publications demonstrate expertise in climate modeling (ConvMOS, ICLR 2024-2025), physics-informed neural networks (TaylorPDENet, ECMLPKDD 2023), and fraud detection (MIDAS workshops, ECMLPKDD 2020-2023). She actively contributes to conferences as organizer and PC member, including ECMLPKDD and ICLR workshops.

Scientific Awards

• Best ML Innovation Award (2020) for Deep Learning in Climate Modeling
• Best Student Paper Award (2020) for Multi-Task Land Use Regression
• Best Paper Award (2020) for Financial Fraud Detection with INALU

The DynaBench dataset introduced in 2023 provides benchmark tools for learning dynamical systems from low-resolution data. Her work combines theoretical advancements with practical implementations, including edge computing applications for beekeeping monitoring systems.