Massimiliano Sampaolo

Papers

Total Citations

H-Index

About

Massimiliano Sampaolo is a pioneering researcher at the intersection of robotics and process mining, with a core focus on enabling data-driven analysis of autonomous robotic systems. His major contributions center on developing methodologies to extract, structure, and mine multimodal data—including sensor streams, video, and action logs—from robotic environments. Sampaolo’s work introduces novel frameworks for transforming raw robotic operational data into event logs suitable for process mining, thereby bridging the gap between physical robot behavior and analytical process models. His 2025 paper "Robotic Datasets for Process Mining" has already garnered 4 citations, highlighting its foundational role in this emerging field. He further advanced the domain with "Enabling Process Mining on Multimodal Robotic Data" (3 citations) and "Multimodal Zero-Shot Activity Recognition for Process Mining of Robotic Systems" (1 citation), which leverages zero-shot learning to recognize robot activities without task-specific training. Sampaolo’s research is notable for its practical implications in manufacturing, logistics, and service robotics, offering a systematic approach to improve robot efficiency, transparency, and adaptability. His work is rapidly gaining traction as a cornerstone for the next generation of intelligent robotic process analysis.