Shubham is a passionate and innovative leader in the field of machine learning and computer vision, with a focus on 3D perception and autonomous vehicles. He holds a graduate degree in Computer Science from Stanford University, where he specialized in Artificial Intelligence and learned from the world's top experts.
As the Head of Machine Learning at Kodiak, he is building the world's safest driver, using his extensive experience and skills in developing and deploying vision-centric 3D perception solutions. He has led a team of talented researchers at Ford Autonomy, where he created an end-to-end 3D Perception stack for Ford L2+ vehicles, and a scalable cloud-based ML framework for all ML tasks within Ford. He has also authored multiple patents and publications, demonstrating his contributions to the industry and his commitment to driving change.
Case Study
Tuesday, July 01
09:25 am - 09:50 am
Live in San Francisco
Less Details
The deployment of self-driving trucks represents a monumental leap forward in the evolution of transportation, promising unparalleled efficiency, safety, and sustainability in the freight industry. However, the journey towards widespread adoption of autonomous trucking is fraught with multifaceted challenges that demand meticulous navigation and strategic solutions. Kodiak aims to delve into the complexities surrounding the deployment of self-driving trucks, examining the various technological, regulatory, and societal hurdles that must be addressed to realize the full potential of autonomous freight transportation.