Bio: Andrea Vedaldi is Professor of Computer Vision and Machine Learning and a co-lead of the VGG group at the Engineering Science department of the University of Oxford. He researches computer vision and machine learning methods to understand the content of images and videos automatically, with little to no manual supervision, in terms of semantics and 3D geometry.
Bio: Kate Saenko is an AI Research Scientist at FAIR, Meta and a Full Professor of Computer Science at Boston University where she leads the Computer Vision and Learning Group. Kate received a PhD in EECS from MIT and did postdoctoral training at UC Berkeley and Harvard. Her research interests are in Artificial Intelligence with a focus on out-of-distribution learning, dataset bias, domain adaptation, vision and language understanding, and other topics in deep learning.
Bio: Vishal M. Patel is an Associate Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University. His research focuses on computer vision, machine learning, image processing, medical image analysis, and biometrics. He has received a number of awards including the 2021 IEEE Signal Processing Society (SPS) Pierre-Simon Laplace Early Career Technical Achievement Award, the 2021 NSF CAREER Award, the 2021 IAPR Young Biometrics Investigator Award (YBIA), the 2016 ONR Young Investigator Award, and the 2016 Jimmy Lin Award for Invention.
Bio: Bernt Schiele has been Max Planck Director at MPI for Informatics and Professor at Saarland University since 2010. His research interests emphasize that understanding sensor information is a fundamental problem, spanning the pipeline from single-sensor processing to spatial and temporal fusion of multiple modalities and, ultimately, large-scale multimodal sensor streams. His group focuses on computer vision and multimodal sensor processing.