Information Processing Systems – IINF-05/A
The IINF-05/A sector is engaged in the development and innovation of advanced methodologies, technologies, and architectures for information processing, with a focus on artificial intelligence, big data, information systems, and web technologies. Research activities focus on several key areas, with the aim of addressing emerging challenges related to data analysis, management, and interpretation, as well as the design of intelligent and adaptive systems for industrial, scientific, and social applications.
Main Research Areas
Research activity in the IINF-05/A sector aims to contribute significantly to the advancement of information technology, with a significant impact on various application sectors, from industry to healthcare, from digital services to information management. The main lines of research that SSD researchers intend to develop are listed below:
- Artificial Intelligence and Machine Learning –Machine learning algorithms, deep learning, generative models, and applications of artificial intelligence in industrial, healthcare, and social contexts.
- Smart Manufacturing and Industry 4.0 –Development of intelligent systems for production optimization, process automation, and predictive analytics in industrial contexts.
- Big Data Analysis –Advanced methods for managing, analyzing, and visualizing large volumes of data, with applications in scientific, economic, and social fields.
- Information Systems -Design and development of software architectures for the management, integration, and security of information in corporate and public contexts.
- Personalized access to information and recommendation systems –Models and algorithms for personalizing access to digital content and improving the user experience.
- Information Retrieval –Techniques for indexing, retrieving, and automatically classifying information.
- Web of Things (WoT) - Integration of smart devices with the web, development of distributed and interoperable architectures for IoT applications.
- Semantic Web and Knowledge Graphs –Knowledge representation and automatic reasoning models for the semantic web and knowledge networks.
- Knowledge Representation and Automated Reasoning -Advanced techniques for knowledge representation, automated reasoning, and the use of innovative methods such as non-standard reasoning and opportunistic reasoning.
- Model Checking –Formal methods for the verification and validation of complex systems, with applications in software and hardware.
- Adaptive Architectures -Design of software and hardware systems capable of dynamically adapting to changes in the operating environment.
- Human-Centered Artificial Intelligence (HCAI) - Development of artificial intelligence systems that integrate principles of explainability, interpretability, and ethics, with a focus on human-machine interaction and the design of intuitive interfaces for decision support.
- Brain-Computer Interface (BCI) –Development of deep learning models for decoding brain signals and recognizing emotional states, with applications in advanced interaction with digital systems and creative generation of digital content.
- Artificial Intelligence for Life Science -Design and development of artificial intelligence pipelines to support the diagnosis and prognosis of neurological diseases, with a particular focus on the explainability, reliability, and usability of AI-driven models.
- Cybersecurity - Development of advanced models for the protection of IT systems, networks, and critical infrastructure, with a particular focus on the detection and mitigation of cyber threats, the security of IT/OT architectures, and the integration of machine learning techniques for the identification and attribution of malicious attacks.
Personnel
