Si propone una lista di possibili argomenti per la tesi di laurea magistrale, suddivisi per docente proponente, il quale assumerà il ruolo di relatore.

Professor: F. BELLAVIA

1. Computer Vision
2. Three-dimensional reconstruction from images and videos
3. Autonomous navigation through computer vision
4. Color correction methods for images and videos
5. Image mosaicing and stitching

Professor: G. CASTIGLIONE

1. Infinite-word languages
2. Advanced closure properties of regular languages
3. Star-free languages
4. Recognizability of two-dimensional languages
5. Two-way finite automaton
6. Applications of formal language theory to the study of natural languages
7. Context-sensitive languages

Professor: C. EPIFANIO

1. Data structures for text indexing
2. Data compression algorithms
3. Sturmian graphs

Professor: G. FALCONE

1. Addition algorithms on hyperelliptic curves in asymmetric cryptography
2. Decoding algorithms for Goppa and Reed–Muller codes

Professor: G. FICI

1. Implementation in C or Java of advanced string algorithms and experimentation on real-world data
2. Theoretical development of combinatorial notions on strings (introduction to research)

Professor: D. GARLISI

1. DevOps Pipelines for Cyber-Physical Systems: CI/CD for edge computing and IoT applications.
2. Containerization and Kubernetes orchestration for large-scale cyber-physical systems.
3. Infrastructure-as-Code (Terraform, Ansible) for scalable IoT environments.
4. Automated testing of firmware and cloud services for IoT sensor networks.
5. IoT sensor systems for water network monitoring and leak detection.
6. LLM-based operational assistants for managing energy or water infrastructures.
7. LLMs as orchestrators of ML models for prediction, diagnostics, and technical reporting.
8. RAG-based optimization for accessing technical manuals and intervention protocols.
9. Reinforcement Learning for network distributed node selection
10. Anomaly detection in streaming of dataset (malfunctions, outliers).
11. Federated learning for consumption forecasting with privacy preservation.
    
12. ML-Enhanced Key Agreement Protocols for 5G Security
13. Document Intelligence: entity extraction and information retrieval from documents.
14. Semantic indexing and natural-language querying of technical manuals, reports, and regulations.
15. Automated SCAS Testing via RAG on 3GPP Documentation

Professor: R. GIANCARLO

1. String algorithms for large data collections
2. Graph algorithms
3. Data structures for indexing and search
4. Data compression based on reordering

In collaboration with the CNR:

1. Adaptive workflow systems
2. Multi-agent simulation systems
3. Software design tools

Professor: G. LO BOSCO

1. Machine Learning
2. Deep Learning
3. Bioinformatics
4. Medical imaging
5. Augmented reality (in collaboration with the ITD-CNR institute)
6. Natural Language Processing (in collaboration with the ICAR-CNR institute)
7. Mobile application development (in collaboration with the ITD-CNR institute)

Professor: F. REALE

1. Numerical analysis applied to Astrophysics
2. High-performance computing applied to Astrophysics

Professor: S. ROMBO

1. Pattern discovery and Artificial Intelligence for oral cancer prevention
2. Selection of optimal cohorts of individuals in various contexts (advertising, clinical trials, finance, etc.)
3. Big Data Analytics and Artificial Intelligence for decision support in different application contexts with distributed tools (Spark, MongoDB, ElasticSearch, etc.)
4. Distributed frameworks and methodologies (MapReduce, RDD, etc.)
5. Knowledge Graphs
6. Natural Language Processing (NLP) and text-to-speech
7. Applications for Precision and Regenerative Medicine - also in collaboration with industries
8. Link prediction for social and/or biological networks
9. Software security and cybersecurity (Blockchain, Smart Contracts, etc.) - also in collaboration with other universities
10. Digital signage and personalized advertising
11. Data Warehousing and Business Intelligence
12. IT approaches and methodologies for sustainability - in collaboration with the University's Center for Sustainability and Ecological Transition

Professor: G. SANFILIPPO

1. Exchangeable events and draws from urns of unknown composition
2. Entropy and extropy of information
3. Bregman divergence and measures of dissimilarity

Professor: M. SCIORTINO

1. Construction of compact graphs for text indexing
2. Combinatorial tools for text classification
3. Construction of self-adjusting automata for process management (in collaboration with the CNR)
4. External-memory algorithms and data structures for processing massive datasets
5. Construction of index structures for text collections
6. Measures for text comparison
7. Measures for comparing tree structures

Professor: C. VALENTI

Data analysis, parallel and evolutionary algorithms for:

1. Tomography
2. Forensic computing
3. Diagnostics
4. Interpretation
5. Compression