Francesco Locatello is an assistant professor at ISTA, working on Causal Learning and Artificial Intelligence. Before, he was a Senior Applied Scientist at Amazon Web Services (AWS). He led the Causal Representation Learning research team, where he pursued fundamental research in machine learning, artificial intelligence, and causality. He received his Ph.D. in Computer Science from ETH Zurich (2020), supervised by Gunnar Rätsch (ETH Zurich) and Bernhard Schölkopf (Max Planck Institute for Intelligent Systems), where he was awarded the ETH medal for outstanding doctoral dissertation. During his Ph.D., he was supported by a Google Fellowship and was a Fellow at the Max Planck ETH Center for Learning Systems and ELLIS. During that time, he spent one year at the Max Planck Institute for Intelligent Systems and two years at Google Brain across Zurich (1.5 years as a part-time Research

Consultant) and Amsterdam (6 months internship). He holds a Computer Science M.Sc. degree from ETH Zurich and a B.Sc. engineering degree (cum laude) in Information Technologies from the University of Padua (Italy). His research on machine learning and artificial intelligence has received awards at several premier conferences and workshops, most notably the best paper award at the International Conference on Machine Learning. Francesco Locatello is heavily involved in the research community, co-organizing the first international conference on Causal Learning and Reasoning (CLeaR), ICLR and UAI workshops, and a NeurIPS competition.

Vittorio Ferrari is the Director of Science at Synthesia, where he leads R&D groups developing cutting-edge generative AI technology. Previously he built and led multiple research groups on computer vision and machine learning at Google (Principal Scientist), the University of Edinburgh (Full Professor), and ETH Zurich (Assistant Professor). He has co-authored over 160 scientific papers and won the best paper award at the European Conference in Computer Vision in 2012 for his work on large-scale segmentation. He received the prestigious ERC Starting Grant, also in 2012.  He led the creation of Open Images, one of the most widely adopted computer vision datasets worldwide. While at Google his groups contributed technology to several major products (with launches e.g. on the Pixel phone, Google Photos, Google Lens). He was a Program Chair for ECCV 2018 and a General Chair for ECCV 2020. He is an Associate Editor of IEEE Pattern Analysis and Machine Intelligence, and formerly of the International Journal of Computer Vision. His recent research interests are in 3D Deep Learning and Vision+Language models.

Stefan Roth received the Diplom degree in Computer Science and Engineering from the University of Mannheim, Germany in 2001. In 2003 he received the ScM degree in Computer Science from Brown University, and in 2007 the PhD degree in Computer Science from the same institution. Since 2007 he is on the faculty of Computer Science at Technische Universität Darmstadt, Germany (Juniorprofessor 2007-2013, Professor since 2013). His research interests include probabilistic and statistical approaches to image modeling, motion estimation and tracking, as well as object recognition and scene understanding. He received several awards, including honorable mentions for the Marr Prize at ICCV 2005 (with M. Black) and ICCV 2013 (with C. Vogel and K. Schindler), the Olympus-Prize 2010 of the German Association for Pattern Recognition (DAGM), and the Heinz Maier-Leibnitz Prize 2012 of the German Research Foundation (DFG). In 2013, he was awarded a starting grant of the European Research Council (ERC). He regularly serves as an area chair for CVPR, ICCV, and ECCV, and is member of the editorial board of the International Journal of Computer Vision (IJCV), the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), and PeerJ Computer Science.