ARTIFICIAL INTELLIGENCE, EXPLAINABLE AI & COMPLEX DATA SYSTEMS
The Artificial Intelligence activities at CNR-Nanotec – LiCryL @ Rende focus on the development of advanced machine learning and deep learning methodologies for the analysis of complex data arising from heterogeneous domains, including biomedical imaging, precision agriculture, structural health monitoring, cultural heritage, and smart systems
CONTACT PERSONS
Eugenio Vocaturo
KEYWORDS
Artificial Intelligence; Optimization; Image Analysis; Data Mining; Industrial Application.
Research is centered on:
- Deep Learning and Hybrid AI architectures
- Explainable Artificial Intelligence (XAI)
- Multiple Instance Learning (MIL)
- Computer Vision and Image Analysis
- Data Mining and Predictive Modeling
- AI for Complex and High-Dimensional Systems
A distinctive feature of the Unit is the development of hybrid and interpretable AI models that integrate data-driven approaches with domain knowledge, enhancing reliability, transparency, and practical deployment in real-world scenarios.
Applications span:
- Medical imaging and computer-aided diagnosis
- AI-driven agricultural monitoring and crop disease detection
- Intelligent inspection systems for industrial and logistic applications
- Digital twins and structural monitoring
- AI-based analysis of scientific and experimental data
The laboratory is actively involved in national and international collaborations, contributes to interdisciplinary research infrastructures, and supports technology transfer through software prototyping, advanced analytics services, and intellectual property protection.
The AI activities are coordinated within the Artificial Intelligence Laboratory at CNR-Nanotec, promoting cross-disciplinary integration with materials science, nanotechnology, photonics, and complex systems modeling.