Panel Discussion

Challenges and Opportunities in the dawn of Agentic AI era for Computer Systems and Computer Vision

This joint panel aims to create a structured dialogue between the CompSys and NCCV communities on emerging research paradigms shaped by agentic AI. The session will explore how autonomous, goal-driven (agentic) AI systems are influencing research and educational methodologies, infrastructure, and evaluation practices across both communities, with a focus on identifying shared challenges and opportunities.

The key panelists will be:

• Christoph Lofi (TU Delft) - Christoph is an Associate Professor in the Web Information Systems group at Delft University of Technology and serves as the Director of Studies for the BSc Computer Science and Engineering programme. His long-term research vision is to develop semantic-based data and knowledge engineering methodologies that enable FAIR data management platforms to serve as a foundation for sustainable societal research. His work addresses research challenges related to knowledge extraction from unstructured data, dataset integration and enrichment, semantic query processing, and metadata management as a socio-technical system. Aligned with the university’s vision of “Impact for a Better Society,” Christoph’s research is inherently interdisciplinary, focusing on domains where innovative data engineering can address pressing societal needs. His primary application areas include agricultural and botanical sciences, public health, nutrition, and translational sciences.
• Andre Luckow (BMW Group IT & Ludwig-Maximilians-Universität München) - Andre Luckow is Head of Innovation and Emerging Technologies at BMW Group IT and lecturer at Ludwig-Maximilians-Universität München. He leads BMW Group IT’s global Tech Office Network, with locations in the United States, China, India, and Germany. His research spans high-performance and distributed computing systems, including HPC and cloud middleware for heterogeneous compute infrastructures. More recently, his work has focused on AI/ML systems at scale and quantum-classical hybrid computing, with contributions to quantum middleware and hybrid algorithms for optimization and simulation.
• Estefania Talavera (University of Twente) - Estefania is an Assistant Professor in Multimodal Learning for Human Behaviour Analysis within the Data Management and Biometrics group at the University of Twente. His research interests span computer vision, machine learning, and their intersection for understanding and analysing human behaviour. Prior to joining the University of Twente, he worked as a lecturer and researcher in the Information Systems group at the University of Groningen. He received his PhD in Computer Science in February 2020 from the University of Barcelona and the University of Groningen, under the supervision of Prof. Petia Radeva and Prof. Nicolai Petkov.
• Pascal Mettes (University of Amsterdam) - Pascal is a tenured Assistant Professor at the University of Amsterdam. Together with his research team, he aims to advance the field of hyperbolic deep learning. While contemporary deep learning is largely founded on Euclidean geometry, this framework has inherent limitations that cannot be overcome simply through larger datasets or more complex models. One of the most significant challenges concerns the representation and learning of hierarchical structures, which are fundamentally hyperbolic in nature due to their exponential growth patterns. His research focuses on developing the theoretical foundations and algorithmic methods required to perform deep learning in hyperbolic spaces, enabling more effective modelling of hierarchical data. His key research domains are highlighted below.

The moderator of the panel will be Giacomo D’Amicantonio (TU/e)