Courses - Cycle 40

For the cycle 40, the PhD Programme in Computer Science offers a comprehensive educational plan covering a broad range of fundamental and advanced topics in computer science and its applications. The proposed courses are designed to provide doctoral candidates with high-level theoretical and methodological competencies, addressing scientific and technological challenges through innovative approaches.

The educational programme includes essential introductory courses such as Introduction to PhD Studies, which supports new doctoral candidates in navigating their research path, and Introduction to Computational Complexity Theory, which provides a solid foundation in computational complexity. In the area of security and information management, the Reading Group: Cryptography explores the main cryptographic methods, while the Reading Group: Large Language Models and Knowledge Graphs examines the interaction between language models and knowledge graphs. Artificial intelligence is further addressed in the courses MCMC for Machine Learning, AutoML, Metaheuristics and LLMs as a New Solving Approach, and Perceptive Deep Learning and Generative AI for Industrial and Legal Applications, which focus on advanced algorithms for machine learning and automated optimization. The field of data analysis and statistical methods is well represented by courses such as Clustering Approaches and Mixture Models, which explores statistical clustering models, and Efficient Heuristics for Optimization, devoted to heuristic methodologies for optimization problems. The course Causal Inference on Bayesian Network provides tools for causal modelling based on Bayesian networks. The growing impact of computer science in the medical domain is highlighted by the courses In Silico Medicine: State of the Art and Perspectives and In Silico Trials and Digital Twins in Healthcare, which address the use of computational simulations in medicine and clinical trials. The integration of complex systems is the focus of Integration Systems, while Mathematical Background for Signal Processing and Related Applications provides essential mathematical tools for signal processing. The area of computer vision and image recognition is explored in Advanced Computer Vision and Applications, structured into two distinct modules, and in the Reading Group: Perception, Learning and Visual Intelligence, which investigates the frontiers of visual intelligence. The course Analysis of Social Media Contents and Natural Language Processing addresses techniques for analysing social media content through NLP. Finally, the PhD programme offers courses on emerging topics such as Quantum Computing: from Mathematical and Physical Basis to Coding, which introduces the theoretical and practical foundations of quantum computing, and Knowledge Representation and Reasoning in the Semantic Web, which focuses on knowledge representation and automated reasoning in the Semantic Web. All courses will be activated with a minimum enrolment of two doctoral candidates, ensuring a focused and interactive learning experience aimed at developing interdisciplinary competencies essential for advanced research in Computer Science.

Ph.D. Days 2025 Seminar Series

The Ph.D. Days seminar series, now in its eighth edition, was established to enhance the training of our doctoral candidates by providing them with the skills required to undertake highly qualified research activities both within and outside the University. This year’s theme is “Placement for Ph.D.: Doctoral Education and Career Opportunities”. The programme will address key cross-cutting topics for all doctoral candidates, including postdoctoral career paths, scientific communication, and intellectual property protection of research outcomes. The potential of doctoral candidates in terms of start-up creation and technology transfer will also be explored. Click here for information about the seminars and dates.

Summer Schools 2025

ICVSS - International Computer Vision Summer School: Computer Vision for Spatial and Physical Intelligence.

iFOSS - International Forensics Summer School. Forensic Horizons: Investigating Truth in the Digital and AI Era. Challenges and Opportunities in Digital Forensics.