Raquel Urtasun
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Raquel Urtasun (born January 30, 1976) is a Spanish-Canadian computer scientist and entrepreneur known for her research in machine learning, computer vision, and autonomous driving. She is the founder and chief executive officer of Waabi, a Toronto-based autonomous trucking and self-driving technology company she launched in 2021, and a full professor in the Department of Computer Science at the University of Toronto. Before founding Waabi she served from 2017 to 2021 as chief scientist of Uber's Advanced Technologies Group, the unit known as Uber ATG, and she is a co-founder of the Vector Institute for Artificial Intelligence.[1][2]
Over an academic career spanning the Toyota Technological Institute at Chicago and the University of Toronto, Urtasun published more than 200 research papers and was named on more than 100 patents in autonomous driving. She has become one of the most prominent women leading an autonomous-vehicle company and one of the most decorated AI researchers in Canada, recognized with the Order of Ontario, fellowship of the Royal Society of Canada, a place on TIME's list of the 100 Most Influential People in AI, and, in 2026, fellowship of the Royal Society in the United Kingdom.[1][3]
Urtasun was born on January 30, 1976, in Pamplona, the capital of the Navarre region of northern Spain.[1] She earned a degree in telecommunications engineering from the Public University of Navarre (Universidad Publica de Navarra) in 2000 before moving to Switzerland for graduate study. She completed a PhD in computer science at the Ecole Polytechnique Federale de Lausanne (EPFL) in 2006, supervised by Pascal Fua, with a dissertation on motion models for robust three-dimensional human body tracking.[1]
She then pursued postdoctoral research in the United States, first as a postdoctoral associate at the Massachusetts Institute of Technology from 2006 to 2008, and afterward in the group of Trevor Darrell at the University of California, Berkeley from 2008 to 2009.[1]
In 2009 Urtasun joined the Toyota Technological Institute at Chicago, a computer science research institute affiliated with the University of Chicago, as an assistant professor, a position she held until 2014. She was also a visiting professor at ETH Zurich in 2010.[1]
In 2014 she moved to the University of Toronto as a professor in the Department of Computer Science. Her research there spanned computer vision, machine learning, robotics, and remote sensing, increasingly focused on the perception and prediction problems that underlie autonomous vehicles.[1][3] She became a recognized authority on three-dimensional scene understanding, object detection, and motion forecasting from camera and lidar data.
In 2017 Urtasun was among the co-founders of the Vector Institute for Artificial Intelligence, a Toronto research organization established alongside Geoffrey Hinton and others to anchor Canada's deep-learning community.[2] She is a Canada CIFAR AI Chair and a fellow of the CIFAR Learning in Machines and Brains program, and she received the Natural Sciences and Engineering Research Council's E.W.R. Steacie Memorial Fellowship. She served as a program chair of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in 2018 and as an editor of the International Journal of Computer Vision.[1][2]
In May 2017 Urtasun joined Uber as chief scientist of its Advanced Technologies Group, the division building self-driving cars, where she also led research and development and built up the company's Toronto-based research lab.[1][5] She continued to hold her University of Toronto professorship throughout this period.
Uber ATG never reached commercial deployment, and in late 2020 Uber agreed to sell the unit to the self-driving startup Aurora Innovation, a transaction that closed in January 2021.[1] Rather than join Aurora, Urtasun left to start her own company. She had concluded that the industry's heavy reliance on millions of miles of real-world road testing was too slow, too expensive, and too hard to scale safely, and she set out to build autonomy around AI and simulation instead.[5][6]
Urtasun founded Waabi in 2021 and serves as its chief executive officer. The company is headquartered in Toronto, with teams in cities including San Francisco, Dallas, Phoenix, and Pittsburgh, and develops what it calls "physical AI" for autonomous vehicles, starting with long-haul trucking.[5][7]
Waabi emerged from stealth in June 2021 with an oversubscribed US$83.5 million Series A round led by Khosla Ventures, with participation from Uber, Aurora Innovation, and others. It was among the largest first financing rounds ever raised by a Canadian startup at the time.[4] In June 2024 the company raised a US$200 million Series B led by Uber and Khosla Ventures, adding Nvidia as a new investor along with Volvo Group Venture Capital, Porsche Automobil Holding SE, Scania Invest, and Ingka Investments, which lifted total funding to roughly US$280 million.[8][9]
In January 2026 Waabi announced an oversubscribed US$750 million Series C co-led by Khosla Ventures and G2 Venture Partners, with participation from Nvidia's NVentures arm, Volvo Group Venture Capital, Porsche SE, and others. The round valued the company at about US$3 billion and ranked among the largest single financings ever raised by a Canadian technology company.[10][11][12] Separately, Uber committed up to US$250 million in milestone-based investment and agreed to deploy at least 25,000 Waabi-powered robotaxis exclusively on its platform, marking the company's expansion from trucking into ride-hailing.[10][11]
The Waabi Driver, the company's autonomous driving system, has run commercial trucking operations with Uber Freight on the roughly 385-kilometre (240-mile) corridor between Dallas and Houston, Texas, hauling freight since 2023 with safety drivers monitoring the vehicles.[5][13] In 2025 Waabi partnered with the truck maker Volvo to integrate the Waabi Driver with Volvo's purpose-built VNL Autonomous tractor, intended for production at scale.[14] The company had aimed to put trucks on public highways with no human in the cab by the end of 2025; as of early 2026 it had pushed that fully driverless launch back by a few quarters, with remote human operators set to monitor, but not steer, the trucks.[10][13] In August 2025 Waabi hired Lior Ron, the former head of Uber Freight and a co-founder of the self-driving startup Otto, as its chief operating officer.[7]
Urtasun's central thesis is that autonomous driving should be built around a single, end-to-end AI system rather than the long pipelines of separately engineered modules used by many earlier self-driving programs, and that most validation should happen in simulation rather than through endless physical road testing.[6][15] Waabi describes its software as a form of generative AI, closer to a foundation model for driving, that perceives its surroundings, reasons about them, and plans actions within one learned system whose decisions can be interrogated and verified.[6]
The cornerstone of this method is Waabi World, a high-fidelity, closed-loop simulator that recreates the sensor inputs a truck would experience and automatically generates the wide range of situations, including rare and dangerous ones, that a vehicle might face on the road. Because the simulator reproduces real conditions with what Waabi calls a near-zero "domain gap," the same Waabi Driver software can be trained and stress-tested almost entirely in simulation before deployment.[6][7] The company argues that this makes development roughly 10 to 20 times faster and more capital-efficient than approaches that depend mainly on accumulating real-world miles, and that it exposes the system to safety-critical scenarios that would be impractical or unsafe to stage in reality.[6][15]
Urtasun has positioned this AI-first, simulation-centric strategy as the key to deploying self-driving technology safely and at scale. She frequently argues that long-haul trucking is the application where autonomy will become a commercial reality first, citing its highway-dominated routes, predictable operating conditions, and the trucking industry's persistent driver shortage.[5][15]
Urtasun has been widely recognized for both her research and her entrepreneurship. In 2023 she was named to TIME's list of the 100 Most Influential People in AI.[1] In 2024 she was elected a Fellow of the Royal Society of Canada, appointed to the Order of Ontario (the province's highest civilian honour), and named a CNBC Changemaker.[16][17] In May 2026 she was elected a Fellow of the Royal Society, the United Kingdom's national academy of sciences, as part of a cohort of more than 90 researchers announced that month.[3]
| Year | Honor |
|---|---|
| 2018 | Program Chair, CVPR; Chatelaine Woman of the Year |
| 2023 | TIME 100 Most Influential People in AI |
| 2024 | Fellow, Royal Society of Canada |
| 2024 | Order of Ontario |
| 2024 | CNBC Changemaker |
| 2026 | Fellow of the Royal Society (FRS) |
Earlier in her career she received the NSERC E.W.R. Steacie Memorial Fellowship, an NVIDIA Pioneers of AI award, three Google Faculty Research Awards, and an Amazon Faculty Research Award.[1]