Understanding what AI models can – and can't – do
Interview with Dr. Simone Schaub-Meyer, early career researcher in the cluster project “RAI”
2024/12/23
In the “RAI” project, Dr. Simone Schaub-Meyer is working to improve our understanding of widely used artificial intelligence (AI) models and to make them more robust. In this interview, the computer scientist reveals why this is important, who could benefit from it in the future and what drives her personally. Part two of a video series with early career researchers in the planned clusters of excellence involving TU Darmstadt.
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The planned RAI Cluster of Excellence , led by Technical University of Darmstadt, is dedicated to developing a new generation of AI systems based on reasonable use of resources, data protection and continuous improvement. With four research areas, multidisciplinary teams are working to shape the future of AI. Over the past decade, deep learning has enabled significant advances in artificial intelligence. Nevertheless, current AI systems have weaknesses, including a lack of logical reasoning, difficulties in dealing with new situations, and the need for continuous adjustment. Not least, current AI systems require extensive resources. The Cluster of Excellence project therefore aims to develop the next generation of AI, “Reasonable Artificial Intelligence” (RAI).
About Dr. Simone Schaub-Meyer
Dr. Simone Schaub-Meyer is an independent research group leader at the Technical University of Darmstadt and a member of the Hessian Center for Artificial Intelligence (hessian.AI). There she also heads a DEPTH research group funded by the HMWK as part of the cluster project “The Third Wave of Artificial Intelligence” (3AI). Since 2024, Schaub-Meyer has also been leading an Emmy Noether junior research group at TU Darmstadt, which is funded by the German Research Foundation (DFG) for the first three years with around 1.1 million euros.
The focus of her research is on developing efficient, robust and comprehensible methods and algorithms for image and video analysis. Before founding her own group, she worked as a postdoc in Professor Stefan Roth's Visual Inference Lab.
Prior to that, Schaub-Meyer worked as a postdoc in the field of augmented reality at the Media Technology Lab at ETH Zurich. In her dissertation, which was awarded the ETH Medal, she developed novel methods for motion estimation and video image interpolation.
About the excellence strategy of the federal and state governments
To further strengthen the international competitiveness of research at German universities, the federal and state governments have established the Excellence Strategy as a funding programm e. The key objective of the Excellence Strategy is to strengthen top-level research in areas that are internationally competitive, to institutionally strengthen German universities, and to advance the development of the German higher education system.
To this end, the Excellence Strategy comprises two separate but intertwined funding lines. The “Clusters of Excellence” funding line, coordinated by the German Research Foundation (Deutsche Forschungsgemeinschaft – DFG) provides project-based funding for internationally competitive research areas at German universities. The “Universities of Excellence” funding line, coordinated by the German Science and Humanities Council (Wissenschaftsrat – WR), is designed to fund institutional strategies that promise to strengthen universities as a whole and create outstanding framework conditions for excellent research.
