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Raquel Urtasun

From Wikipedia, the free encyclopedia
Raquel Urtasun
Born (1976-01-30) 30 January 1976 (age 48)
Pamplona, Spain
Known forSelf-driving cars, AI
Scientific career
FieldsMachine Learning, Computer Vision, Robotics, AI and Remote Sensing
InstitutionsUniversity of Toronto
ETH Zurich
ThesisMotion Models for Robust 3D Human Body Tracking (2006)
Doctoral advisorPascal Vitali Fua
WebsiteRaquel Urtasun

Raquel Urtasun OOnt (born 30 January 1976[1]) is a professor at the University of Toronto. Urtasun uses artificial intelligence, particularly deep learning, to make vehicles and other machines perceive the world more accurately and efficiently.[2]

Education

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Urtasun received her bachelor's degree in Telecommunication Engineering from the Universidad Publica de Navarra in 2000 and her Ph.D. degree from the Computer Science department at École Polytechnique Fédérale de Lausanne (EPFL) in 2006.[3] Afterward, she was a postdoctoral scholar with Trevor Darrell,[4] initially at MIT (2006–2008) and then, following Darrell's move to the International Computer Science Institute, at UC Berkeley (2008–2009).[5]

Career

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Professor Urtasun's area of research is machine perception for self-driving cars. This work includes machine learning, computer vision, robotics and remote sensing. She was previously an assistant professor at the Toyota Technological Institute at Chicago (TTIC) (2009–2014) and a visiting professor at ETH Zurich (2010).[5]

In May 2017, Uber hired Urtasun to lead a Toronto-based research team on self-driving cars.[6] There, she led a research group in Uber's Advanced Technologies Group. Uber hired dozens of researchers and also made a multi-year, multi-million dollar commitment to Toronto's Vector Institute, which Urtasun co-founded.[7] She worked for the University of Toronto one day per week and for Uber four days per week.[6] She brought eight students with her.[8][9]

In 2021, Urtasun left Uber and launched Waabi Innovation, focused on developing self-driving cars.[10]

Awards and honours

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Among Urtasun's awards are an NSERC E.W.R. Steacie Memorial Fellowship, an NVIDIA Pioneers of AI Award, a Ministry of Education and Innovation Early Researcher Award. She is the recipient of Faculty Research Awards from both Amazon and Google, the latter three times. She served as Program Chair of CVPR 2018, and is an editor of the International Journal in Computer Vision (IJCV). She has also served as Area Chair of several machine learning and vision conferences including NeurIPS, UAI, ICML, ICLR, CVPR, and ECCV. She was selected as one of the Chatelaine Women of the Year 2018.[11] In January 2024, she was appointed to the Order of Ontario.[12]

References

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  1. ^ Urtasun, Raquel. "Curriculum Vitae". University of Toronto. Archived from the original on 5 August 2022. Retrieved 30 September 2024.
  2. ^ "Uber opening Toronto research hub for driverless car technology". Toronto Star. 8 May 2017. Retrieved 2017-08-28.
  3. ^ Aubelle, Arnaud (25 October 2021). ""Self-driving technology needs AI as its focal point"". EPFL News. Retrieved 14 October 2022.
  4. ^ "Berkeley Artificial Intelligence Research Lab". BAIR. Retrieved 31 October 2022.
  5. ^ a b Urtasun, Raquel (8 February 2017). "Curriculum Vitae" (PDF). Raquel Urtasun.
  6. ^ a b "Uber Is Opening Up A Self-Driving Car Center In Canada". BuzzFeed. 8 May 2017. Retrieved 2017-08-28.
  7. ^ Metz, Cade. "Uber Hires an AI Superstar in the Quest to Rehab Its Future". Wired. Wired Magazine. Retrieved 2017-08-28.
  8. ^ Perkel, Colin (8 May 2017). "Uber setting up AI lab in Toronto". CityNews Toronto. Retrieved 31 October 2022.
  9. ^ "Uber setting up artificial intelligence lab in Toronto". Las Vegas Sun. Associated Press. 8 May 2017. Retrieved 31 October 2022.
  10. ^ "U of T AI research star Raquel Urtasun raises US$83.5-million for self-driving startup four months after leaving Uber". Retrieved 2021-06-15.
  11. ^ Chen, Rachel; et al. (2018). "Meet Our Women Of The Year: 32 Canadians Who Absolutely Rocked 2018".
  12. ^ "2023 Order of Ontario Appointees". Ontario Newsroom. 1 January 2024.
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