The KIT Department of Informatics cordially invites you to the Semester Colloquium on February 16 2026, 5:30pm, at InformatiKOM 1.

 

As part of the event, the Dean of the Faculty will give a brief semester report, providing an overview of current developments and perspectives. The focus of the colloquium will then be on the inaugural lectures of Professor Nadja Klein and Professor Henning Meyerhenke, both of whom are based at the Scientific Computing Center in addition to the Department.

 

In her inaugural lecture, entitled “Bayesian Statistics and Machine Learning: Leveraging the Best of Both Worlds”, Nadja Klein introduces Bayesian learning as a principled framework for combining prior knowledge with data, quantifying uncertainty, and enhancing the transparency of modern machine-learning systems. By incorporating expert information, structural assumptions, or sparsity‑inducing mechanisms, Bayesian methods can make models more accurate, robust, and data‑efficient, thereby addressing key limitations of black‑box approaches. Nadja Klein's research brings together theoretical analysis, methodological innovation, and real‑world applications. This includes work on spatial statistics, sparse and scalable Bayesian models, Bayesian neural networks, and techniques for interpretability and explainability of complex systems. On the applied side, her group collaborates across disciplines, from analyzing complex biomedical and neuroimaging data, to predicting weather and environmental patterns, to supporting safer autonomous‑driving technologies. This talk will highlight selected recent methodological advances from her group and illustrate their impact through concrete applications, showcasing how Bayesian ideas can strengthen modern machine‑learning pipelines.

 

In the inaugural lecture “Graph Algorithms for Large Complex Systems” Henning Meyerhenke addresses research challenges arising from massive networks in different application areas. The talk focuses on recent algorithmic results that solve problems in algorithmic network analysis, carbon-aware workflow scheduling, and graph robustness optimization.

 

Following the colloquium, you are warmly invited to a small reception, offering the opportunity for discussion and personal exchange.