Robert Moss is the co-founder and CEO of Valgo, a company focused on building software to validate safety-critical autonomous systems in simulation. Previously, he was a postdoctoral researcher at the Stanford Intelligent Systems Laboratory, conducting research on methods for safe planning under uncertainty and black-box safety validation. Robert received his Ph.D. in computer science from Stanford University advised by Mykel Kochenderfer. He holds an M.S. from Stanford where his research received the best CS master's thesis award and he also received the Centennial TA award for his teaching efforts. Before Stanford, Robert was a research staff member at MIT Lincoln Laboratory and was part of the core team that developed, optimized, and validated the next-generation aircraft collision avoidance system. Robert is an avid Julia user.

Robert Moss is the co-founder and CEO of Valgo, a company focused on building software to validate safety-critical autonomous systems in simulation. He received his Ph.D. in computer science from Stanford University, studying algorithms for safe planning and validation of safety-critical autonomous systems. He holds an M.S. in computer science from Stanford where his research received the best computer science master's thesis award and he also received the Centennial TA award for his teaching efforts. He earned his B.S. in computer science with a minor in physics from the Wentworth Institute of Technology in Boston, MA. Robert was an associate research staff member at MIT Lincoln Laboratory where he was on the team that designed, developed, and validated the next-generation aircraft collision avoidance system for commercial aircraft, unmanned vehicles, and rotorcraft. Robert was also a research engineer at the NASA Ames Research Center, developing decision support tools for the VIPER autonomous Lunar rover mission searching for water deposits on the Moon. Robert is a member of the Stanford Intelligent Systems Laboratory, the Stanford Mineral-X Group, and part of the Stanford Center for AI Safety conducting research on methods for high-dimensional planning under uncertainty using low-dimensional surrogate models, risk assessment of autonomous vehicles, and efficient safety validation.