Qamar Un Nisa is a PhD researcher at the Department of Computer Science and Engineering (DISI), University of Bologna, working under the supervision of Prof. Maurizio Gabbrielli. Her research focuses on the development of intelligent and explainable systems for predictive maintenance, fault detection, and real-time monitoring in industrial environments.
Her current research develops modular AI frameworks for processing complex sensor data, with the goal of detecting anomalies at an early stage and enhancing the operational efficiency of cyber-physical systems, contributing directly to the advancement of Industry 4.0.
In collaboration with SACMI, a leading industrial partner, she designs and implements applied AI solutions that integrate human-in-the-loop feedback to support trustworthy and interpretable decision-making across manufacturing processes.
She holds a Master’s degree in Information Technology (Pakistan, 2014) and has professional experience working with public sector data systems. With a strong background in teaching and applied research, Qamar Un Nisa is passionate about bridging the gap between academic innovation and real-world industrial challenges, and is dedicated to contributing impactful solutions in the field of Industrial AI and smart system monitoring.
