Florian Pfaff's research group focuses on advancing the fields of machine learning and tracking. He is specializing in extended object tracking, learning and estimation on manifolds, and the integration of machine learning techniques with traditional estimation and tracking disciplines. This entails the development and refinement of algorithms capable of accurately tracking the position and orientation of objects that cannot be represented as mere points in space, such as vehicles in driving scenarios. By employing machine learning strategies, his group aims to enhance model accuracy and adaptability, enabling the tracking systems to learn from data.
New research group on cognitive sensor technology for the mobility of the future
- News
Safety is a top priority in road traffic. Therefore, future autonomous mobility solutions must accurately predict the movements of other vehicles, cyclists, and pedestrians. This is the focus of the tracking procedures and machine learning methods that Junior Professor Dr. Florian Pfaff aims to further develop with the new research group at the ICM.
Crucial role for mobility systems of the future
This approach facilitates the creation of sophisticated models that can predict and follow the movements of extended objects with high precision, essential for various applications, including autonomous driving. Furthermore, his research group delves into the specific challenges of estimation and learning on manifolds, with a keen interest in human pose estimation, which can be applied to predicting the behavior of humans in traffic settings.
The research group led by Florian Pfaff seamlessly integrates into the InnovationCampus Future Mobility (ICM) by contributing cutting-edge advancements in the field of mobility technologies, specifically through the work on extended object tracking and the synergistic blend of machine learning with classical estimation and tracking methodologies. The group's focus on developing sophisticated algorithms for tracking the dynamics of vehicles and pedestrians plays a crucial role in the design of sustainable mobility systems, aligning perfectly with the ICM's mission to revolutionize transport systems and production techniques for a sustainable and efficient future.
About the person
Florian Pfaff's journey in academia began with exceptional academic achievements, including completing his Ph.D. in Computer Science at the Karlsruhe Institute of Technology with the highest distinction, summa cum laude. His professional experience is marked by a series of notable positions and research endeavors, including postdoctoral research and leadership roles at the Karlsruhe Institute of Technology, where he led projects in the context of optical belt sorting. His expertise and contributions were further recognized during a guest researcher stint at University College London (UCL), where he collaborated on cutting-edge research in his field.
Florian Pfaff's work has garnered widespread recognition, earning him several prestigious awards and honors. Among these are the ISIF Young Investigator Award, the SICK Science Award for the best Ph.D. thesis, and inclusion in the "Ausgezeichnete Informatikdissertation" collection, highlighting the best Ph.D. theses in the German-speaking world. His research has also led to notable best paper awards.
Further information
The unique combination and networking of expertise between the university and research locations of Stuttgart and Karlsruhe will strengthen scientific excellence and the training of young scientists in Baden-Württemberg. The Innovation Campus Mobility of the Future (ICM) is establishing several junior research groups and junior professorships at both universities for this purpose.
More about the junior professorships and junior research groups of the ICM