Research | Computer Science

The research group includes researchers in the computer science area (G.S.D. INFO/01). The group's research interests mainly focus on the study of theoretical and practical aspects related to the extraction, diffusion and processing of information and knowledge. More in detail, the group is interested in themes such as:

• Design and analysis of efficient algorithms for information processing,
• Analysis of information diffusion dynamics and design of techniques for contrasting opinions’ manipulation,
• Design and analysis of multi-agent systems,
• Machine learning,
• Design of techniques and methods for information security,
• Definition of theories, techniques, and methodologies for the extraction and processing of knowledge from non-structured, heterogeneous, and multi-dimensional data,
• Data-driven modelling and analysis of complex systems and networks.
• Methods for knowledge representation, automation of conceptual relationship extraction, and improvement of knowledge graph quality
• Integration of symbolic and neural approaches to improve reasoning and understanding, development of neuro-symbolic frameworks for knowledge representation.

These goals are pursued using the theoretical and practical, expertise of the group members, which spans a large body of knowledge going from computational intelligence to semantics, from artificial intelligence and machine learning to mathematical and algorithmic optimization, from game theory to network science, from the theory of computation and the computational complexity to the information theory and cryptography.

The activities of the research group have several applications of high practical relevance, such as:

• Design and analysis of algorithms for advertising and marketing on the web and/or on other social and information networks,
• Analysis of social networks (e.g., Twitter, Reddit) and characterization of their dynamics, contrast to the diffusion of fake news and to the manipulation of opinions,
• AI for the social good and public health,
• security and applications of the Blockchain technology,
• cybersecurity,
• Big Data analysis for searching and extracting patterns in raw data.
• Integration and Semantic Representation of Heterogeneous Data
• Applications Based on Retrieval Augmented Generation (RAG)

Most of the research results obtained by the members of the group are published in journals and proceedings of conferences that are internationally recognized as of high level according to the most prestigious national and international rankings (csranking.org, CORE, SJR).

Research directions

Among the research themes of interest for the members of research group there are:

• Artificial Intelligence
• Blockchain and Distributed Ledger Technologies
• Complex Systems Analysis
• Cybersecurity
• Computational Game Theory and Mechanism Design
• Data Mining and Text Mining
• Fuzzy Logic
• Logic Programming
• Knowledge Graph and Knowledge Extraction
• Multi-Agent Systems
• Natural Language Processing
• Network Science
• Neuro-Symbolic AI
• Retrieval Augmented Generation
• Semantic Technologies
• Situation Awareness and Context awareness

Teaching

The members of the research group are involved in teaching activities related to the degrees in Computer Engineering, both at the bachelor level (L8), Master (LM-32) and PhD (Foundations of Programming, Algorithms and Data Structures, Computer Networks, Web Designing Techniques, Algorithms and Protocols for Security, Optimization Techniques, Mobile and Distributed Programming, Data Management Systems, Semantic Technologies, Social Networks Analysis).