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Bringing AI Up to Speed — Autonomous Auto Racing Promises Safer Driverless Cars on the Road
Madhur Behl, associate professor of computer science and systems and information engineering and Cavalier Autonomous Racing team leader, writes about the history and rapid growth of AI racing.
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More Systems NewsTrust is Not the Answer: Rethinking Human-Machine Interaction for Ethical Engineering
Matthew Bolton argues that relying on trust in AI can mislead users, advocating instead for transparency, reliability and ethical design.
Read NowHoo’s a Pinball Wizard? Engineering Student Goes From Winning the Game To Designing the Game
Mean pinballer and second-year systems engineering major Colin Sartori is offering his wizardry to help design a UVA-themed pinball game for Gavin Garner’s mechatronics course project.
Systems and Information Engineering 2.0: The Future of Complex Systems
Opinion: Integrating AI with human insight to revolutionize smart systems for a modern world.
Read NowFor this Founder and Investor, It All Started with Systems Engineering
UVA alumna Dayna Grayson’s first startup experience at UVA’s ERICA project sparked her passion for transformative technology and venture capital.
Read NowUVA Co-Leads $2.9 Million NIH Investigation Into Where Systems May Fail People with Disabilities
Rupa Valdez has combined efforts with a Johns Hopkins University researcher and others to understand how systems affect the care of people with disabilities.
Read NowPodcast: Madhur Behl on CAVCAR’s Record-Breaking Victory and Beyond
Hoos in STEM podcast host Ken Ono asks Cavalier Autonomous Racing’s Madhur Behl and Amar Kulkarni what’s next after becoming the first American team to win the Indy Autonomous Challenge.
Read NowUVA Engineering Seeks Applicants for Talent Pipeline
UVA Engineering is recruiting talent for its Rising Scholars program.
Read NowWatch as UVA Displays Its New High-Speed, Self-Correcting AI Algorithms
What were the keys to UVA's impressive showing at this fall's Indy Autonomous Challenge? A mathematical tweak to the vehicle dynamics and a new car-detection algorithm that learns from its mistakes.
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