Max Robotics — Global Service Robot Directory + US Certification

About

Andreas Ziegler is a researcher at the intersection of robotics, computer vision, and neuromorphic computing. His work focuses on enabling machines to perceive and interact with fast-moving objects in real time, with a particular emphasis on dynamic sports scenarios and event-based vision. Ziegler’s major contributions include the development of SpinDOE, a novel method for estimating ball spin in table tennis using event cameras, which addresses a long-standing challenge in robotic sports perception. He has also pioneered real-time event simulation techniques that make neuromorphic sensor research more accessible, and explored the detection of high-velocity objects using spiking neural networks on neuromorphic hardware. His work on hypo-fractionated SBRT for prostate cancer demonstrates an early interest in precision medical applications. With over 40 citations across his most influential papers, Ziegler is establishing himself as a key figure in the emerging field of neuromorphic robotics. His 2025 paper on neuromorphic hardware for fast-moving object detection signals a promising trajectory toward energy-efficient, real-time perception systems that could transform autonomous robotics and human-machine interaction.