Philipp Krähenbühl is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin. He received his Ph.D. in Computer Science from Stanford University and then spent two years as a Postdoc at UC Berkeley. His research interests lie in Computer Vision, Machine learning and Computer Graphics. He is particularly interested in deep learning, as well as image segmentation and understanding.

Aljosa Osep is currently working as a Postdoctoral Fellow at the Robotics Institute at Carnegie Mellon University in Pittsburgh, prior at the Dynamic Vision and Learning Group at the Technical University in Munich. When he's not out exploring the world, he's busy pioneering the next generation of computer vision methods for dynamic scene understanding and mobile robot perception that continually learn and self-improve from raw, unlabeled streams of sensory data.

Prof. Dr. Laura Leal-Taixé is a Senior Research Manager at NVIDIA and also an Adjunct Professor at the Technical University of Munich (TUM), leading the Dynamic Vision and Learning group. From 2018 until 2022, she was a tenure-track professor at TUM. Before that, she spent two years as a postdoctoral researcher at ETH Zurich, Switzerland, and a year as a senior postdoctoral researcher in the Computer Vision Group at the Technical University in Munich. She obtained her PhD from the Leibniz University of Hannover in Germany, spending a year as a visiting scholar at the University of Michigan, Ann Arbor, USA. She pursued B.Sc. and M.Sc. in Telecommunications Engineering at the Technical University of Catalonia (UPC) in her native city of Barcelona. She went to Boston, USA to do her Masters Thesis at Northeastern University with a fellowship from the Vodafone foundation. She is a recipient of the Sofja Kovalevskaja Award of 1.65 million euros in 2017, the Google Faculty Award in 2021, and the ERC Starting Grant in 2022.

Alex Schwing is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois in Urbana-Champaign and affiliated with the Coordinated Science Laboratory and the Computer Science Department. Prior to that he was a postdoctoral fellow in the Machine Learning Group at University of Toronto collaborating with Raquel Urtasun, Rich Zemel and Ruslan Salakhutdinov. He completed his PhD in computer science in the Computer Vision and Geometry Group at ETH Zurich working with Marc Pollefeys, Tamir Hazan and Raquel Urtasun, and graduated from Technical University of Munich (TUM) with a diploma in Electrical Engineering and Information Technology. Alex's research is centered around machine learning and computer vision. He is particularly interested in algorithms for prediction with and learning of non-linear (deep nets), multivariate and structured distributions, and their application in numerous tasks, e.g., for 3D scene understanding from a single image.

Vittorio Ferrari is a Principal Scientist at Google, where he leads research groups on computer vision. He received his PhD from ETH Zurich in 2004, then was a post-doc at INRIA Grenoble (2006-2007) and at the University of Oxford (2007-2008). Between 2008 and 2012 he was an Assistant Professor at ETH Zurich, funded by a Swiss National Science Foundation Professorship grant. In 2012-2018 he was faculty at the University of Edinburgh, where he became a Full Professor in 2016 (now a Honorary Professor). His work on large-scale segmentation won the best paper award at the European Conference in Computer Vision 2012. He received the prestigious ERC Starting Grant, also in 2012. He is the author of over 150 technical papers. He was a Program Chair for ECCV 2018 and a General Chair for ECCV 2020. He is an Associate Editor of the International Journal of Computer Vision, and formerly of IEEE Pattern Analysis and Machine Intelligence. His current research interests are in 3D Deep Learning, transfer learning, and human-machine collaboration for annotation.

Shalini De Mello is a Distinguished Research Scientist and Research Lead in the Learning and Perception Research group at NVIDIA, which she joined in 2013. Her research interests are in human-centric vision (face and gaze analysis) and in data-efficient (synth2real, low-shot, self-supervised and multimodal) machine learning. She has co-authored 48 peer-reviewed publications and holds 38 patents. Her inventions have contributed to several NVIDIA products, including DriveIX and Maxine. Previously, she has worked at Texas Instruments and AT&T Laboratories. She received her Doctoral degree in Electrical and Computer Engineering from the University of Texas at Austin.