Event Calendar

 
Colloquium

Semester Colloquium WS 25/26

Monday, 16 February 2026, 17:30
InformatiKOM I
Geb. 50.19, Adenauerring 12
76131 Karlsruhe
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.
Organizer
Fakultät für Informatik
Karlsruher Institut für Technologie (KIT)
Am Fasanengarten 5
76131 Karlsruhe
Tel: 0721 / 608-48660
Fax: 0721 / 608-41777
Mail: pr ∂does-not-exist.informatik kit edu
https://www.informatik.kit.edu
Targetgroup
alumni, Alumni und Freunde des KIT, Foreign Students, Research and Partners, Interested / Everyone, Employees, Professors, Students, Scientific Staff, Young Scientists
Online registration
Zur besseren Planung bitten wir um Anmeldung für die Antrittsvorlesungen und den Empfang.

Please register for the Inaugural Lectures and Reception to facilitate planning.
Online Registration
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About KCDS

Concept of the graduate school KCDS
KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in the field of model-driven and data-driven computational science.
In this unique program, doctoral researchers will be able to conduct an interdisciplinary research project that revolves around computational methods such as mathematical models, simulation methods and data science techniques, all the while building bridges between mathematical sciences and an applied SEE discipline (science, economics and engineering).
Addressing global challenges, the school provides a wide variety of topics, from meteorological ensemble forecasting to machine learning in elementary particle physics.
At KCDS, doctoral researchers have one supervisor from the mathematical sciences and one from the applied discipline. They are part of a dynamic community and participate in the school’s interdisciplinary training program, including hands-on training in small groups, summer schools, networking events and hackathons/datathons.
Thinking simulations and data together, we are ready to conquer the data-driven challenges of tomorrow!

Coordination Office

Angela Hühnerfuß, M.A.
Coordination KIT Graduate School Computational and Data Science

+49 721 608-47748angela huehnerfuss ∂does-not-exist.kit eduwww.kcds.kit.edu/