Lia Morra

Lia Morra is a fixed-term Researcher at the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where she is also a member of the SmartData@PoliTO – Big Data and Data Science Laboratory. She is actively involved in research, teaching, and editorial roles, focusing on artificial intelligence and its applications in vision and data science. She teaches in the College of Computer, Film and Mechatronics Engineering and the College of Management and Production Engineering.

Research Interests: Her work centers on artificial intelligence, deep learning, image analysis, and neural-symbolic integration. She applies these techniques to medical imaging, satellite data, autonomous systems, and human-computer interaction. Her research bridges symbolic reasoning with neural networks, emphasizing explainability, robustness, and real-world deployment.

Publication Trends: Her recent publications (2023–2025) show a strong focus on neuro-symbolic AI, explainable models, medical imaging, and efficient deep learning. She frequently publishes in top-tier journals and conferences such as Medical Image Analysis, IEEE ACCESS, and IJCNN, with applications in healthcare, autonomous driving, and privacy-preserving AI.

Scientific Awards and Recognition:

• Open badge RIMINI SCHOOL 2025 “SUCCESSFULLY PARTICIPATE IN CALLS FOR RESEARCH FUNDING”
• Learning to Teach (L2T)

Advising and Grants: She supervises multiple PhD students in Computer and Systems Engineering, including Pietro Basci, Rosario Milazzo, Alessandro Sebastian Russo, and Luca Piano. She is the Scientific Responsible for several research projects, including EU-funded CAMOUFLAGE and multiple commercial contracts on AI for medical imaging, satellite data, and digital transformation. She also serves on editorial boards for Frontiers in Medical Engineering and IEEE Consumer Electronics Magazine.

Labs and Teams: She is a core member of the GRAINS (GRAphics and INtelligent Systems) research group at DAUIN, focusing on intelligent systems, computer vision, and data science.