Manuele Di Maio

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About

Manuele Di Maio is a robotics and autonomous systems researcher whose work bridges advanced manufacturing and intelligent vehicle perception. His key research areas include robotic manipulation, additive manufacturing, and computer vision for autonomous driving. Di Maio’s most notable contribution is the conceptual design, control, and simulation of a 5-DoF robotic manipulator for direct additive manufacturing on the internal surfaces of radome systems—a specialized application that demonstrates his expertise in integrating robotics with precision manufacturing processes. This work, which has garnered 4 citations, showcases his ability to solve complex, real-world engineering challenges. In parallel, Di Maio has made significant strides in autonomous vehicle perception through his work on action detection from a robot-car perspective. He co-presented the Road Event and Activity Detection (READ) dataset, a pioneering resource designed specifically for action detection in autonomous driving contexts. This dataset, cited 3 times, provides scholars in computer vision, smart cars, and machine learning with a valuable tool for advancing perception systems. Di Maio’s dual focus on robotic manufacturing and autonomous perception positions him as a versatile researcher contributing to both the hardware and software dimensions of intelligent systems.