Karl Pertsch is a Member of Technical Staff and researcher with a decade of experience at the intersection of computer vision, robotics, and machine learning, currently splitting time between Physical Intelligence and postdoctoral roles at Stanford and UC Berkeley. He holds a PhD in Computer Science from USC and built a strong foundation in 6D pose estimation, RGB/RGB‑D reconstruction, and reinforcement-learned control through projects at TU Dresden, Penn GRASP, Berkeley RAIL, and industry internships at BMW. Karl’s work spans both academic research and applied systems—designing perception pipelines robust to heavy occlusion and energy-optimized driving strategies—making him adept at moving novel algorithms toward real-world robotics applications. Based in Philadelphia, he combines rigorous engineering (Dipl.-Ing. with a 3.95 GPA) with a track record of cross-institutional collaboration that often bridges simulation, ROS-based deployment, and lab-to-field transition.
10 years of coding experience
6 years of employment as a software developer
PhD, Computer Science, PhD, Computer Science at University of Southern California
Diplom-Ingenieurin (Dipl.Ing.), Electrical and Electronics Engineering, GPA: 3.95, Diplom-Ingenieurin (Dipl.Ing.), Electrical and Electronics Engineering, GPA: 3.95 at Technische Universität Dresden
Computer Science, Computer Science at University of Pennsylvania
Contributions:40 commits, 1 PR, 35 pushes in 8 months
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Karl Pertsch - Member Of Technical Staff at Stanford University