Monica Nicoli

Papers

Total Citations

190

H-Index

About

Monica Nicoli is a leading researcher at the intersection of wireless communications, machine learning, and industrial automation. Her work primarily focuses on enabling next-generation autonomous systems through ultra-reliable, low-latency communications (URLLC) and distributed intelligence. She is best known for pioneering the application of Federated Learning in connected, cooperative, and automated industrial systems—a contribution that has garnered 186 citations and is shaping how robots, vehicles, and drones learn collaboratively while preserving data privacy. Nicoli has also made significant advances in industrial indoor positioning, developing novel filtering techniques like the Switching Model Stein Variational Sampling Filter to maintain accuracy in mixed line-of-sight/non-line-of-sight environments, critical for autonomous robotics and augmented reality. Additionally, her research on wireless sensing for device-free human motion recognition has opened new possibilities for contactless interaction using radio signals. Through these contributions, Nicoli is driving the convergence of communication, computation, and sensing in industrial IoT, with her work cited extensively by researchers advancing 5G-advanced and beyond.