Invited Speakers

Tri Dao is an Assistant Professor at Princeton University and chief scientist of Together AI. He completed his PhD in Computer Science at Stanford. He works at the intersection of machine learning and systems, and his research interests include sequence models with long-range memory and structured matrices for compact deep learning models. His notable work includes FlashAttention and Mamba. His work has received the COLM 2024 Outstanding paper award and ICML 2022 Outstanding paper runner-up award.

Webpage: https://tridao.me/

Andrea Vedaldi is Professor of Computer Vision and Machine Learning at the University of Oxford, where he co-leads the Visual Geometry Group since 2012. He is also a senior research scientist and technical lead at Meta. He researches generative AI in 3D computer vision, applied to the generation of 3D content from text and images and to image understanding. He is the author of more than 200 peer-reviewed publications in computer vision and machine learning. He is the recipient of the IEEE Thomas Huang Memorial Prize, the IEEE Mark Everingham Prize, and the Test of Time Award by the ACM, and the best paper award from the Conference on Computer Vision and Pattern Recognition.

Webpage: https://www.robots.ox.ac.uk/~vedaldi/

Ishan Misra is a Research Scientist in Meta's GenAI org. He leads the research efforts at Meta in video generation and was the tech lead for Meta's MovieGen and Emu Video foundational video models. In the past, he worked on self-supervised learning methods such as BarlowTwins, DINO. Ishan was featured in MIT Tech Review's 35 innovators under 35 and is the recipient of Carnegie Mellon's Recent Alumni Achievement Award. You can hear him on Lex Fridman's podcast for an overview of his work.

Webpage: https://imisra.github.io/

Chen Change Loy is a President's Chair Professor with the College of Computing and Data Science, Nanyang Technological University, Singapore. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Prior to joining NTU, he served as a Research Assistant Professor at the MMLab of the Chinese University of Hong Kong, from 2013 to 2018. His research interests include computer vision and deep learning with a focus on image/video restoration and enhancement, generative tasks, and representation learning. He served/serves as an Associate Editor of the Computer Vision and Image Understanding (CVIU), International Journal of Computer Vision (IJCV) and IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). He also serves/served as the Area Chair of top conferences such as ICCV, CVPR, ECCV, ICLR and NeurIPS. He will serve as the Program Co-Chair of CVPR 2026.

Webpage: https://www.mmlab-ntu.com/person/ccloy/

Xinlong Wang is a Technical Lead at Beijing Academy of Artificial Intelligence (BAAI), leading the vision and multimodal team (BAAI Vision). He received the PhD degree in Computer Science from The University of Adelaide. Before that he obtained the Bachelor's degree from Tongji University. His research interests lie in the area of computer vision and foundation models. He works on visual perception (SOLO series), visual representation (EVA-CLIP series),  vision foundation models (SegGPT series), and multimodal foundation models (Emu3 series).

Webpage: https://www.xloong.wang/

Daniel Bolya is a Research Scientist Manager at Meta AI (FAIR). He received the BSc, MSc and PhD degrees (all with distinction) in computer science from TU Graz in 2011, 2013 and 2017, and spent time as a visiting researcher at York University, Toronto as well as the University of Oxford. He is a recipient of the PAMI Young Researcher Award, the DOC Fellowship of the Austrian Academy of Sciences, and the Award of Excellence for outstanding doctoral theses in Austria. His main areas of research include the development of effective representations for image and video understanding.

Webpage: https://dbolya.github.io/