Jan David Hüwel has successfully completed his PhD at the FernUniversität in Hagen. His dissertation, which forms part of the GAIA (Gaussian Processes for Automatic and Interpretable Anomaly Detection) project, is also part of the DataNinja Research Training Group in North Rhine-Westphalia. It focuses on methods for trustworthy and traceable AI when analysing complex data. Prof. Christian Beecks (FernUniversität in Hagen) supervised the doctoral thesis, and Prof. Markus Lange-Hegermann (inIT) provided co-supervision.
Inter-university doctoral program at the NRW Research Training Group DataNinja
The Research Training Group "DataNinja – Trustworthy AI for Seamless Problem Solving" in the state of North Rhine-Westphalia (NRW) is a doctoral programme in the field of trustworthy AI. The group combines rigorous methodological research with practical applications. A key feature is the inter-university supervision model, which draws on expertise from various research institutions.
Doctoral thesis on Gaussian processes and structured time series analysis
In his dissertation entitled “Adaptive Modeling and Signal Discovery in Time Series Data,” Jan David Hüwel deals with the modeling of complex time series based on Gaussian processes. The focus is on the question of how hidden structures and anomalies in multidimensional data can be identified automatically and at the same time comprehensibly—a topic of high relevance for data-driven research and industrial applications.
Research in the GAIA project: interpretable AI for anomaly detection
This doctoral thesis was written as part of the GAIA research project. The project aims to develop powerful yet interpretable methods for anomaly detection. GAIA therefore addresses a key challenge facing modern AI systems, namely that results must be both correct and comprehensible.
Several young scientists are pursuing their doctorates within the GAIA project. One of them is Andreas Besginow, a research assistant in the inIT Mathematics and Data Science working group, which is headed by Prof. Dr. Markus Lange-Hegermann.
Success through collaboration
Jan David Hüwel's doctoral thesis exemplifies how inter-university supervision and project-based research interact in the DataNinja graduate school.
'We warmly congratulate Jan David Hüwel on successfully completing his doctoral thesis. His work highlights the importance of closely integrating methodological AI research with practical applications. The DataNinja graduate college provides an excellent framework for this.' – Prof. Dr. Markus Lange-Hegermann.