Mobileye
Tal Babaioff is responsible for mapping and localization at Mobileye. In this critical role, Babaioff’s team (jointly managed with Yoram Gedalyahu) is responsible for creating the high-definition maps that are needed for highly and fully autonomous vehicles. Using Mobileye’s Road Experience Management™ (REM™) technology, Babaioff’s team uses a crowd sourcing approach to collect the data needed for the map creation and compiles that data into useful maps. Babaioff joined Mobileye in 2002 as an algorithm developer.
In his 17-year career, he has worked on Mobileye’s business development team as well as advanced evaluation platforms for key Mobileye customers. His previous VP role was leading Mobileye’s production organization between 2014 - 2017, overseeing all customer-facing execution of OEM integrated safety systems, and allowing Mobileye triple the number of new systems delivered other that time frame. Before that, Babaioff personally led the first production program launches for the first three generations of Mobileye’s System-on-Chip, known as EyeQ®, EyeQ2 and EyeQ3.
Babaioff holds a bachelor of science degree in computer science from the Hebrew University in Jerusalem. Outside of work, he volunteers for his daughter’s school as finance chair and is an avid reader and hiker.
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Mobileye
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Mobileye N.V. is engaged in the development of computer vision and machine learning-based sensing, mapping and driving policy technology for advanced driver assistance systems and autonomous driving technologies. The Company operates through two segments: Original Equipment Manufacturing, which supplies the software algorithms and EyeQ chip, and After Market, which sells a complete system, which includes its software algorithms and EyeQ chip, as well as the camera and other necessary components. Its software algorithms and EyeQ chips perform detailed interpretations of the visual field in order to anticipate possible collisions with other vehicles, pedestrians, cyclists, animals, debris and other obstacles. Its products are able to detect roadway markings; identify and read traffic signs, directional signs and traffic lights; create a Roadbook of localized drivable paths and visual landmarks using its road experience management technology, and provide mapping for autonomous driving.