Prasad Shingne

I am an autonomous driving and ADAS engineer with nearly two decades of experience across academic research and industry, from graduate work at the University of Michigan through roles at Ford, Byton, Audi, Applied Intuition, and Lucid Motors. My work has centered on simulation, validation, and vehicle systems development, with increasing focus on building the infrastructure and methodology that lets ADAS teams move faster and rely less on physical testing. At Lucid Motors I lead ADAS simulation execution and am building the company's simulate-before-physical-test capability from the ground up. At Applied Intuition I was one of the earliest members of the systems engineering team, working with customers in off-road autonomy to develop and validate their systems in simulation. Earlier I helped develop SAE Level 2 and Level 3 systems at Audi, and worked on modeling and testing at Byton and Ford. I hold a PhD in Mechanical Engineering from the University of Michigan and am currently enrolled in a graduate program at Stanford University. Outside of work I build perception and localization systems on embedded hardware and write about technology and history at @ididacalculation.