Panagiotis Mallioris

Papers

Total Citations

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About

Panagiotis Mallioris is a researcher at the forefront of industrial automation and smart manufacturing, with key contributions in robotics, artificial intelligence, and the Internet of Things (IoT). His work focuses on integrating advanced computational tools into physical production environments to enhance efficiency and decision-making. In his highly cited 2019 paper, "A ROS Tool for Optimal Routing in Intralogistics," Mallioris leveraged the Robot Operating System (ROS) to develop a sophisticated scheduling and planning framework for mobile robots in industrial settings, addressing the complex demands of intralogistics with a practical, software-driven solution. More recently, his 2024 study, "Effective Machine Learning Solution for State Classification and Productivity Identification: Case of Pneumatic Pressing Machine," demonstrates his commitment to Industry 4.0 by applying machine learning to monitor and classify machine states, enabling real-time productivity tracking. With a growing citation record, Mallioris’s work bridges the gap between theoretical AI and tangible industrial applications, offering scalable tools for manufacturers aiming to remain competitive. His achievements highlight a dedication to transforming data into actionable insights, making him a notable voice in the evolution of smart factories.