Ivana Guarneri

Papers

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About

Ivana Guarneri is a researcher at the forefront of integrating deep learning into embedded and robotic systems. Her work primarily focuses on advancing localization and human-robot interaction through efficient neural network architectures. In her highly cited 2021 paper, "Deep Learning Localization with 2D Range Scanner," she pioneered the use of deep learning for accurate pose estimation from low-cost 2D laser scanners, a critical contribution for industrial vehicles and autonomous robots. This work has garnered 10 citations for its practical impact on cost-effective navigation. Guarneri also made significant strides in edge AI with her paper "A Deep Learning Short Commands Recognition for MCU in Robotics Applications," which demonstrated how neural networks can run directly on microcontroller units (MCUs) for real-time voice command recognition. By enabling deep learning on resource-constrained devices and transmitting commands via Bluetooth Low Energy, she has opened new possibilities for accessible, low-power robotics. Her research bridges the gap between advanced AI algorithms and real-world hardware constraints, making her a key figure in the development of intelligent, autonomous systems for industrial and consumer applications.