Posts Tagged: Raquel Urtasun
Raquel Urtasun, Robotics Institute faculty member and founder and CEO of Waabi, appointed one of 25 recipients of the Order of Ontario for 2023—the province's highest civilian honour.
Urtasun is recognized as a leader in autonomous vehicle technology for founding autonomous-trucking start-up Waabi.
Andreas Geiger, professor of computer vision and machine learning at the University of Tübingen, is part of a team of researchers honoured with the prestigious Longuet-Higgins prize at this year’s IEEE Conference on Computer Vision and Pattern Recognition (CVPR). In addition to Geiger, Philip Lenz and Raquel Urtasun received the prestigious award for their joint work on the “KITTI Vision Benchmark,” which they have been running and developing since 2012.
Video and Blog of announcement: Welcome to Waabi World (blog) How Waabi World works (blog) Waabi World video In the news: Canadian AI simulator maker Waabi aims to recharge the quest for […]
Congratulations to UofT Robotics Institute’s Raquel Urtasun, AI & self-driving pioneer, who is No 14 on Toronto Life’s 2021 list of 50 INFLUENTIALS for launching Waabi with $100 million in capital—among the most ever raised by a Canadian tech start-up!
The Everingham prize is awarded to a researcher, or a team of researchers, who have made a selfless contribution of significant benefit to other members of the computer vision community. Raquel Urtasun and her and her colleagues Andreas Geiger, Philip Lenz, Christoph Stiller were awarded the prize thanks to their work on the KITTI Vision Benchmark Suite.
In an interview in Canadian Business magazine, Prof. Raquel Urtasun talks about how she got into autonomous vehicles research, why transparency is important in self-driving technology, and what it’s like […]
Robotics Institute faculty Raquel Urtasun has launched Waabi, a company aiming to bring self-driving tech closer to commercialization than ever before.
Researchers at the University of Toronto’s department of computer science and Uber’s Advanced Technologies Group (ATG) in Toronto have developed an algorithm that jointly reasons about multiple self-driving tasks in as little as 30 milliseconds per frame.
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