Max Robotics — Global Service Robot Directory + US Certification

About

Federico Cunico is at the forefront of research at the intersection of Tiny Machine Learning (TinyML), human-robot collaboration, and Industry 4.0. His most impactful work, a 2024 survey on TinyML with 117 citations, has helped define the emerging field of deploying machine learning on resource-constrained IoT devices, revolutionizing how we design efficient, learning-based hardware-software systems. In industrial robotics, Cunico introduced the Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting in human-robot collaboration, a novel architecture that efficiently models spatial, temporal, and channel-wise interactions. His contributions extend to safety and privacy in smart manufacturing, as demonstrated in the ICE Laboratory case study, and to personalized customer experiences through the I-MALL framework. Most recently, he released the HARPER dataset, capturing 3D human pose data from the perspective of a Boston Dynamics Spot robot, enabling new research in robot-centric perception and interaction. With a growing citation record and pioneering work in both algorithmic innovation and dataset creation, Cunico is shaping the future of intelligent, collaborative, and privacy-aware autonomous systems.