Joma Aldrini

University of Luxembourg, Luxembourg School of Business

Papers

Total Citations

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About

Joma Aldrini is a researcher at the forefront of intelligent automation and sustainable robotics, with a primary focus on fault detection and diagnosis in complex electromechanical systems. Their work bridges the gap between traditional control theory and modern data-driven artificial intelligence, particularly in the context of multi-input multi-output (MIMO) systems. Aldrini’s most cited paper, “Intermittent fault detection for MIMO systems: a case study on SCARA robot” (2023, 6 citations), establishes a foundational comparative framework for estimating actuator torques using data-driven approaches, directly enhancing the safety and operational efficiency of industrial robots. Building on this, their more recent work, “Towards Responsible AI: Evaluating Intelligent Models for Sensor Fault Detection Through the Lens of Sustainability and Performance Optimization” (2025, 3 citations), introduces a novel methodological framework that evaluates fault detection models not only on accuracy but also on sustainability metrics like model complexity and hyperparameter optimization. This dual focus on performance and environmental impact positions Aldrini as a key voice in the emerging field of green AI for automation. Their research is particularly valuable for students and engineers seeking to develop robust, efficient, and ethically responsible diagnostic systems for next-generation smart manufacturing.