Brian Geisel builds software for machines that have to work the first time. For decades, he has led engineering teams developing software for NASA missions, the world’s largest autonomous mobile robot fleet, and defense systems where reliability is non-negotiable. He is the founder and CEO of Geisel Software and CEO of Symage, a company advancing synthetic data for computer vision and Physical AI. Drawing on firsthand experience deploying autonomy outside the lab, Brian helps audiences separate AI hype from engineering reality, explaining what it actually takes to build systems that perceive, decide, and act reliably in the real world.
A model that performs well in simulation is an important milestone. But it is not proof that a robot is ready for the real world.
The hardest challenges in Physical AI emerge when learned behaviors encounter changing environments, imperfect sensors, limited compute, and unexpected edge cases. This panel will explore what it takes to bridge the gap between training and deployment, including the engineering disciplines required to build reliable robotic systems.
Experts will discuss how teams are addressing challenges across perception, decision-making, and manipulation to create robots that can operate safely and predictably outside the lab.
