Prof. Dr. Thomas Bartz-Beielstein from TH Köln (THK-AI Research Cluster) is deeply honored to have been invited to participate in … Mehr
Kategorie: Forschung
THK-AI Research Cluster featured in CAIRNE October 2025 Newsletter
The THK-AI Research Cluster at TH Köln is featured in the CAIRNE October 2025 Newsletter. Recognized by the TH Köln … Mehr
Impressions from the Dagstuhl Research Meeting „Better Benchmarking Setups for Optimisation“
The Dagstuhl research meeting „Better Benchmarking Setups for Optimisation: Design, Curation and Long-Term Evolution“ concluded successfully, fostering productive exchanges and … Mehr
Invitation to the Dagstuhl research meeting „Better Benchmarking Setups for Optimisation“
Prof. Dr. Thomas Bartz-Beielstein is very pleased to be invited to the Dagstuhl research meeting „Better Benchmarking Setups for Optimisation: … Mehr
Erfolgreiches 7. Konsortialtreffen IMProvT II
Das 7. Konsortialtreffen des Forschungsprojektes IMProvT II fand am 18. September an der HTWG Konstanz statt.
TH Köln stärkt KI-Forschung mit dem „THK-AI Forschungscluster“
Der THK-AI Forschungscluster wurde als zentrale Drehscheibe für interdisziplinäre Projekte im Bereich der Künstlichen Intelligenz gegründet. Er wird von Prof. Dr. Bartz-Beielstein und Prof. Dr. Richert geleitet und vernetzt Forschende, Studierende sowie Industriepartner.
Groundbreaking Research on Robust AI in Autonomous Systems Accepted at NeurIPS 2025
A collaborative research paper by scientists from THK-AI Research Cluster, Toyota Research Institute, and Toyota Gazoo Racing Europe has been accepted at the prestigious NeurIPS 2025 conference. The paper, titled „From Faults to Features: Pretraining to Learn Robust Representations against Sensor Failures,“ introduces a novel pretraining approach to enhance the reliability of AI models in safety-critical applications like autonomous driving.
Keine Science-Fiction mehr: Roboter in der Pflege
Der Podcast der TH Köln – Staffel 3 Episode 6: Keine Science-Fiction mehr: Roboter in der Pflege – Prof. Dr. … Mehr
Papers „Physics-Informed Neural Networks for State Estimation Problems“ and „Tuning for Explainability“ accepted at the 35th CI-Workshop in Berlin 2025
Two papers from THK-AI members were accepted for presentation at the 35th Workshop on Computational Intelligence in Berlin, November 2025, and will be published as open access in the KIT Verlag proceedings. The first paper, by Aleksandr Subbotin and Thomas Bartz-Beielstein, explores combining machine learning with classical filtering methods. The second paper, a collaboration with Everllence SE, introduces new measures to enhance explainability in artificial intelligence.
Automated Prediction of Compressor Performance Maps: Surrogate-Based Optimization with RNNs for Enhanced Extrapolation and Interpolation
Richard Schulz presented his talk today at the ACM GECCO 2025 in Malaga. Here are some impressions from his talk.
