Skip Robotics was started in 2017 to develop building blocks for robotics and automation. We develop core perception algorithms from the ground up and advise companies on strategies for building state-of-the-art autonomous systems while managing the risks associated with new technologies.

photo of Alex Segal

Alex Segal

Over the past 17 years, Alex has followed his passion for all things robotics and automation while working on autonomous vehicles, orbital photogrammetry, computer vision, numerical optimization, and data association techniques.

He earned his B.A. in Mathematics and M.S. in Computer Science (Artificial Intelligence) from Stanford University and a PhD from the Active Vision Group at Oxford University. During his time at Stanford, Alex worked with Sebastian Thrun's mobile robotics lab and developed the widely used Generalized-ICP algorithm for processing LIDAR data. His doctoral research at Oxford focused on combined estimation and data association algorithms for robotics.

Alex was an early perception hire and eventual sensor fusion lead at Zoox, where he helped build core perception algorithms for an ambitious autonomous vehicle taxi service. He started Skip Robotics to create technological building blocks for the industry after seeing first-hand the challenges companies face bringing robotics and automation technology to market.