Laura Leal-Taixé

Prof. Laura Leal-Taixé is a Professor at the Technical University of Munich (TUM) in the Department of Informatics, leading the Dynamic Vision and Learning group. She holds the Rudolf Mößbauer Tenure Track Assistant Professorship, promoted to W3 Associate Professorship in 2022. Her research focuses on computer vision and machine learning, particularly video analysis, multi-object tracking, and autonomous driving applications.

Education:

• B.Sc./M.Sc. in Telecommunications Engineering (Technical University of Catalonia, UPC)
• Ph.D. in Information Processing (Leibniz University of Hannover, Germany)
• Postdoctoral Research at ETH Zürich (Switzerland) and TUM

Research Interests: Laura’s work addresses challenges in video analysis, including motion analysis, semantic segmentation, and integrating social dynamics into urban traffic modeling. Her project socialMaps, funded by the Sofja Kovalevskaja Award, explores decoupling vehicle and pedestrian traffic using dynamic maps. Her research combines optimization techniques, deep learning, and sensor data for real-world applications like autonomous systems.

Recent Trends: Her publications highlight advancements in multi-object tracking, 3D LiDAR segmentation, and trajectory forecasting, emphasizing neural networks and geometric approaches. Collaborations with industry and academia underscore her work’s practical impact.

Awards:

• 2017 Sofja Kovalevskaja Award (€1.65M, Humboldt Foundation)
• 2017 DAAD Australia-German Joint Research Grant
• Travel grants from Women in CV, CVPR Doctoral Consortium, and Vodafone Foundation

Labs & Projects: Leads the Dynamic Vision and Learning group at TUM, focusing on vision-based AI for autonomous systems and environmental monitoring. Active in developing datasets like DynamicEarthNet for semantic change analysis.