Pr. Vedaldi is a 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. His research mainly covers using 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. He is also the leading author of the VLFeat and MatConvNet computer vision and deep learning libraries.

Vladimir (Vova) Kim is a Senior Research Scientist at Adobe Research, where his work focuses on computer vision, machine learning, and 3D geometry processing. His research spans a wide range of topics, including 3D reconstruction, shape analysis, and generative models for 3D content creation. Vova is well-known for his contributions to developing advanced algorithms that bridge the gap between visual understanding and 3D modeling, helping to shape the future of creative technologies. He holds a Ph.D. from Princeton University, and his work has been widely published in top-tier conferences such as CVPR and SIGGRAPH.

Pr. Birdal is an Assistant Professor (Lecturer) in the Department of Computing of Imperial College London. Previously, he was a senior Postdoctoral Research Fellow at Stanford University within the Geometric Computing Group of Pr. Leonidas Guibas. His current foci of interest involve geometric machine learning and 3D computer vision. More theoretical work is aimed at investigating and interrogating limits in geometric computing and non-Euclidean inference as well as principles of deep learning.

Pr. Su is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego. His research focuses on artificial intelligence, 3D vision, and robotics, with a particular emphasis on deep learning for 3D understanding, 3D reconstruction, and robot learning. He has made significant contributions to the development of neural representations for 3D data, advancing fields such as 3D shape analysis and scene understanding.

Pr. Chang is an Associate Professor in the School of Computing Science at Simon Fraser University. Prior to this, she was a visiting research scientist at Facebook AI Research and a research scientist at Eloquent Labs. Her research focuses on bridging the gap between language and 3D representations of shapes and scenes, grounding language for embodied agents, and synthesizing 3D environments from natural language.

Pr. Fang is an Associate Professor of Electrical and Computer Engineering at the NYU Abu Dhabi and NYU Tandon. He directs the NYU Multimedia and Visual Computing Lab. His research focuses on 3D Computer Vision and Machine Learning with applications to robotics and autonomous driving. He is currently working on the development of 3D deep learning technologies in large-scale visual computing, cross-domain and cross-modality models, and their various industrial applications.