Dr. Schwalb has received his Ph.D in Artificial Intelligence from University of California Irvine. He has more than 20 years of experience in implementing intelligent systems for a wide range of industries, including defense, consumer electronics, financial, healthcare and engineering. He has authored a technical book, published in major journals, edited technical standards, and credited with more than a dozen patents. At MSC software, he was an architect and member of a product team winning more than a dozen awards in 3 years. Currently he is focused on adoption of machine learning methods for simulation, including tools for training and validating driving agents. His research focus is methods to engineer inherently safe drivers, through quantification and validation of safety.
The development of AI systems for autonomy is very focused on building robust models for neural networks and perhaps less so on how these systems should be made functionally safe for deployment. This presentation will discuss these challenges and propose solutions for successful, safe deployment in tomorrow’s autonomous vehicles.
· Outline the safety challenge faced by AI developers
· Demonstrate an open and safe path to success for autonomous systems