Invited speakers
Jan-Christoph Kalo
University of Amsterdam
Kubilay Atasu
Delft University of Technology
Christopher Morris
RWTH Aachen University
Many real-world phenomena can be naturally represented as graphs, including social networks, biological systems, transaction networks, and knowledge bases. Learning and reasoning over graphs have enabled advances in applications such as drug discovery, fraud detection, recommender systems, and scientific discovery.
This workshop brings together researchers and practitioners working on graph-based AI across foundations and applications. The 3-hour session features invited talks and an interactive poster session with extended abstracts, with the goal of fostering discussion and collaboration between research and applications of these topics in the Benelux region and beyond.
University of Amsterdam
Delft University of Technology
RWTH Aachen University
The workshop will have a duration of 3 hours. Times are indicative and will be confirmed with the BNAIC/BeNeLearn 2026 program.
Welcome and introduction by the organizers
30-minute talk + 10 minutes of questions and discussion
30-minute talk + 10 minutes of questions and discussion
80 minutes of networking and detailed scientific exchange around extended abstracts
30-minute talk + 10 minutes of questions and discussion
We invite extended abstracts on learning and reasoning with graphs, spanning foundational methods and real-world applications, to be presented during the poster session.
Authors are invited to submit an extended abstract of up to 2 pages (excluding references) using the Springer Lecture Notes in Computer Science (LNCS) template. The template is available on Overleaf.
Submissions will be lightly reviewed for relevance to the workshop, and they may describe previously published work, work in progress, or ongoing research.
Attendance requires registration for BNAIC/BeNeLearn 2026.
