| 1 | Quantum Computing for Machine Learning, Optimisation, and Energy Systems (8 hrs, 2 ECTS) |
| LECTURER: Stefano LODI, University of Bologna, Italy SYLLABUS: This intensive PhD-level course introduces the principles and applications of quantum computing, with a focus on machine learning, optimisation, and energy sustainability. The course begins with the foundations of the quantum computational model, covering qubits, quantum gates, circuits, and key phenomena such as superposition and entanglement. It then presents core quantum algorithms, including Grover’s search and the Quantum Fourier Transform, highlighting their implications for computational complexity and modern cryptography. Building on this, the course explores hybrid quantum-classical methods for machine learning and optimisation, such as variational quantum circuits, quantum kernels, and the Quantum Approximate Optimisation Algorithm (QAOA). The final part addresses emerging applications, including optimisation in energy systems, smart grids, and quantum simulation for materials and sustainability. Emphasis is placed on critical assessment of current capabilities and limitations of noisy intermediate-scale quantum (NISQ) devices, and on identifying realistic research opportunities. DATES: TBD | |
| 2 | Introduction to Formal Verification: From Foundations to AI and Multi-Agent Systems (16 hrs, 4 ECTS) |
| LECTURER: Angelo FERRANDO, UNIMORE – FIM SYLLABUS: The course introduces PhD students to the fundamental concepts and methodologies in formal verification, focusing both on static approaches such as Model Checking and dynamic techniques like Runtime Verification. Besides exploring theoretical foundations, the course emphasizes practical knowledge through the use of established verification tools in laboratory sessions. A particular focus will be given to formal verification techniques applied to complex AI-driven and Multi-Agent Systems (MAS). Students will gain practical insights into verifying software components and tackling verification challenges arising in distributed and autonomous systems. At the course’s conclusion, recent research advancements and open challenges in runtime verification and verification of multi-agent systems will be discussed, providing students with a comprehensive understanding of current research directions. DATES: TBD | |
| 3 | Privacy-enhancing technologies (12 hrs, 3 ECTS) |
| LECTURER: Luca FERRETTI, UNIMORE – FIM SYLLABUS: The course offers an introduction to privacy-enhancing technologies (PET), which are security solutions that aim at minimizing information disclosure during data processing. The course outlines the most important system models and security guarantees related to PETs, including information sharing, collaborative and outsourced computation, transparency architectures, and discusses the most popular techniques based on applied cryptography and hardware-related technologies. The course especially focuses on practical solutions and include hands-on sessions based on existing software frameworks. DATES: TBD | |
| 4 | Advanced GPU programming – RAPIDS for data science (16 hrs, 4 ECTS) |
| LECTURER: Nicola CAPODIECI, Filippo MUZZINI, Roberto CAVICCHIOLI, UNIMORE – FIM/DCE SYLLABUS: This course will dive deep into advanced concepts of GPU Programming and architectures. In the first part, advanced CUDA programming concepts will be presented, focussing on the latest evolution of the CUDA programming model and architectural features such as scheduling, programming best practices and CPU – GPU interaction optimizations along with comparison discussions with other GPGPU APIs.The second part introduces NVIDIA’s RAPIDS Suite, an ecosystem of GPU-accelerated libraries for data science and machine learning. It covers the key components: cuDF for GPU-based dataframe manipulation (Pandas equivalent), cuML for accelerated machine learning algorithms, cuGraph for graph analysis, and cuxFilter for interactive visualization. The course presents numerous practical examples of CUDA and RAPIDS integration for end-to-end data science workflows. DATES: TBD | |
| 5 | Internet and Web of Things at the Edge (8hrs, 2 ECTS) |
| LECTURER: Luca BEDOGNI, UNIMORE – FIM SYLLABUS: The class will focus on modern smart IoT systems, which are found in many different scenarios. The course will present at first the Internet of Things and Web of Things scenario, and will then move to practical problems in such environments. The class is focused on the key challenges that low power devices have when processing information. This can be done directly on the device itself, if possible, or can be offloaded to close edge servers. Two reference scenarios pertaining e-Health and Industry 4.0 will be discussed and analyzed in detail, highlighting the key differences and practical issues which can be found. The class will conclude by discussing future research directions. DATES: TBD | |
| 6 | Efficient DL/ML models for embedded systems (12hrs, 3 ECTS) |
| LECTURER: Alessandro CAPOTONDI, UNIMORE – FIM SYLLABUS: The execution of sophisticated Artificial Intelligence (AI) workloads is no longer a prerogative of high-end, high-performance computing systems. Energy- and resource-constrained embedded devices, also called edge devices, are increasingly embracing this type of functionality, which is key to enabling the realization of smart, autonomous systems (unmanned aerial and terrestrial vehicles, robotic arms, etc.). This class will present an overview of the state-of-the-art methodologies for effective and efficient deployment of Deep Learning and Machine Learning (DL/ML) models on edge embedded systems. The topics presented include quantization, pruning and network-architecture-search (NAS) strategies targeting practical and realistic challenges of deploying state-of-the-art DL/ML tasks on edge systems (e.g. NVIDIA Tegra, Xilinx MPSoC, MCU-class RISC-V and ARM SoCs). The class will then close by providing insights on near-to-come research directions in the field. DATES: TBD | |
| 7 | Complexity Theory, On-Line and Approximation Algorithms (12 hrs, 3 ECTS) |
| LECTURER: Manuela MONTANGERO, Mauro LEONCINI, UNIMORE – FIM SYLLABUS: The course will introduce students to theory of computational complexity. The first (shorter) part of the course will be dedicated to the introduction of the fundaments of complexity theory and the definition of the most important complexity classes. The second part of the course will be dedicated to the study of approximation and on-line algorithms. The former are used to address difficult problems (NP-complete or NP-hard), the latter for those problems whose input is not completely available at the beginning of the execution of a solving algorithm. To this aim, problems with interesting applications in distributed/parallel system and data science scenarios will be selected. DATES: TBD | |
| 8 | Introduction to complex systems (8hrs, 2 ECTS) |
| LECTURER: Marco VILLANI, UNIMORE – FIM DATES: TBD | |
| 9 | Vulnerability research (12 hrs, 3 ECTS) |
| LECTURER: Mauro ANDREOLINI, UNIMORE – FIM SYLLABUS: This course will introduce students to the methodological and practical aspects of security vulnerability research in software. The involved activities are at the basis of identifying unknown and sophisticated flaws (typically resulting in a chain of more elementary ones) that current software solutions are not able to find automatically. Classes are organized as a series of seminars and practical lab sessions discussing the following topics: – static analysis – dynamic analysis – formal verification methods – semi-automated testing DATES: TBD | |
| 10 | Sociology of innovation: new technologies and organization (12hrs, 3 ECTS) |
| LECTURER: Matteo RINALDINI, UNIMORE – DCE SYLLABUS: The course aims to reflect on the relationship between technological innovation and organisational innovation through the various perspectives that, in the socio-economic field and in the field of innovation studies, have subjected a deterministic interpretation of technology to criticism. Various theoretical perspectives derived from organisational studies and innovation studies (SCOT, ANT, sociomateriality, etc.) will be analysed and compared with each other, and through these perspectives the current techno-organisational developments attributable to the so-called fourth industrial revolution and in general to the processes of digitalisation of work and production activities will be analysed. The various topics will be addressed not only through lectures, but also through the discussion of materials, seminars and workshops that may include the presence of external experts and colleagues. DATES: TBD | |
| 11 | Sociosemiotic analysis and Sociology of Data. (12 hrs, 3 ECTS) |
| LECTURER: Federico MONTANARI, UNIMORE – DCE SYLLABUS: The class examines the effects that data and technology – and, today, AI – have on current social systems. Through studies in the sociology of science and technology, discourse analysis, thematic analysis, and sociosemiotics, the course offers a perspective that helps us balance technical and computational aspects with issues of social responsibility (and the analysis of the social meanings of data, their associated rhetoric, and narratives). The course topics concern the use of data from both technological and social perspectives. In particular, we will focus on several case studies, such as, on the one hand, the topic of data visualization and its related rhetorical and discursive strategies. On the other hand, we will examine examples related to contexts such as the environmental crisis, or climate change, and the associated data and visualizations. Finally, we will address the topic of wars and conflicts. The sociological and socio-semiotic areas of interest are STS (Science and Technology Studies) and ANT (Actor-Network Theory). DATES: TBD | |
| 12 | Introduction to Social Network Analysis (24 hrs, 6 ECTS) |
| LECTURER: Stefano GHINOI, Elvira PELLE, UNIMORE – DCE SYLLABUS: The course aims at introducing Social Network Analysis (SNA) to doctoral students, which is based on the use of quantitative tools for mapping and analyzing qualitative models of relationships that connect individuals, organizations and institutions. The course provides an overview of the main networking approaches and is structured around a series of theoretical sessions and practical (mini) workshops; in these labs students will have the opportunity to use Python to analyze real networks. The main topics covered in this course are the following: 1) History of SNA and theoretical approaches; 2) network structure data; 3) network statistics; 4) clusters and online communities. By the end of the course, students will be able to understand how to collect, analyze and interpret network data to address social and economic challenges. DATES: TBD | |
| 13 | Introduction to the Parametric Comparison Method (24 hrs, 6 ECTS) |
| LECTURER: Cristina GUARDIANO, UNIMORE – DCE SYLLABUS: This course provides an overview of the Parametric Comparison Method (PCM), that investigates historical relationships between languages through the comparison of their deep grammatical structures. Syntactic parameters and the internal structure of parameter systems will be introduced, where each parameter governs clusters of co-varying surface phenomena and interacts with other parameters through networks of crossparametric dependencies. Students will be introduced to the computational tools used in PCM research to extract historical signals from parameter systems, especially in cases where traditional etymological evidence is absent or insufficient. DATES: TBD | |
| 14 | The structure of DPs (24 hrs, 6 ECTS) |
| LECTURER: Paola Crisma(1), Giuseppe Longobardi(2), Cristina GUARDIANO(3), (1) UNITS, (2) University of York, (3) UNIMORE – DCE SYLLABUS: Through the reading, analysis, and discussion of major contributions to the study of the internal structure of the nominal domain, the course introduces some of the main theoretical approaches and reference analyses developed in contemporary syntactic theory. Particular attention is devoted to the formal properties of nominal syntax and to their interpretation from a comparative and cross-linguistic perspective. Participants will engage directly with selected articles, chapters, and case studies, developing the ability to critically analyze theoretical proposals and empirical data. Lectures will therefore be integrated with seminar-style discussions, close reading of texts, and student presentations aimed at encouraging active participation and independent reflection on the topics addressed during the course. DATES: TBD | |
| 15 | Historical linguistics and contemporary science (12 hrs, 3 ECTS) |
| LECTURER: Giuseppe Longobardi, University of York SYLLABUS: The course introduces the foundations of historical research in linguistics and its place within the broader landscape of contemporary historical sciences. The course explores how 19th-century historical linguistics developed a model of scientific inquiry based on the reconstruction of hidden processes of transmission and change, revealing deep connections between languages and human populations. By comparing linguistics with disciplines such as population genetics, the course reflects on the role of abstraction, reconstruction, and long-term historical inference in the study of the human past. Special attention is devoted to the epistemological challenges of investigating remote chronology and to the relationship between observable linguistic data and deeper historical structures. DATES: TBD | |
| 16 | Introduction to formal syntax (12 hrs, 3 ECTS) |
| LECTURER: Monica Alexandrina IRIMIA, UNIMORE – DCE SYLLABUS: This course provides an overview of the main concepts, methods, and theoretical assumptions of contemporary formal syntactic analysis. The course introduces the principles of sentence structure, syntactic representation, and grammatical relations within the generative tradition, with particular attention to cross-linguistic variation and the relationship between form and interpretation. Through the analysis of linguistic data and selected readings, participants will develop the tools required to formulate and evaluate syntactic analyses from a comparative perspective. DATES: TBD | |
| 17 | Linearization and hierarchical structures in human languages: theoretical and experimental approaches (12 hrs, 3 ECTS) |
| LECTURER: Denis DELFITTO(1), Gaetano FIORIN(2), (1) UNIVR, (2) UNITS SYLLABUS: This course investigates the relationship between linear order and hierarchical structure in human language from both theoretical and experimental perspectives. It examines how hierarchical representations are encoded in linear sequences and how speakers acquire, process, and interpret such structures. Drawing on recent developments in formal syntax, cognitive science, and artificial grammar learning, the course explores the cognitive mechanisms underlying grammatical structures building and the extent to which sensitivity to hierarchical organization can be experimentally assessed. Particular attention is devoted to the implications of experimental findings in the Artificial Grammar Learning paradigm for the relashionship between order and hierarchy in language. DATES: TBD | |
| 18 | Seminar series: Modelling cultural diversity in language and cognition (24 hrs, 6 ECTS) |
| LECTURER: Various lecturers SYLLABUS: In addition to regular courses, students will have the opportunity to attend seminars organized within the series “Modelling Cultural Diversity in Language and Cognition”. The seminars will be structured as thematic mini-workshops dedicated to current topics in linguistics, cognition, and cultural evolution. Attendance of 4 hours of seminar activities corresponds to 1 ECTS, up to a maximum of 6 ECTS. A preliminary list of the seminars already approved is provided below: – Disorder and Frustration. A perspective into the complexity of the human brain (A.Treves); – The ‘miracle creed’: outline and possible applications (M.R. Manzini); – Discourse network analysis (S.Ghinoi); Languages, Cultures and Societies in South America (Valdemar João Wesz Junior); – Language acquisition and parameter systems (P.Crisma, Th.Biberauer; 2 seminars); – Syntactic microvariation in Romance (D.Pescarini); – Annotated corpora and syntactic analysis (E. Sanfelici); Dialects and variation in Italy (J. Garzonio). DATES: TBD | |
| 19 | Corsi Di Formazione Complementare Per Dottorandi E Assegnisti Ediz. 2024/2025 (24 hrs, 6 ECTS) |
| LECTURER: Barbara REBECCHI, Ferdinando DI MAGGIO, Federica MANZOLI, Nadja SEDING, Giulia CATELLANI, Valeria BERGONZINI, Valeria GOLDONI, UNIMORE – International Research Office SYLLABUS: The course is composed of 4 modular sessions: a. Policies for research and innovation: this session explains where the fundings for research come from. Opportunities and practices for national and international funding for research and innovation are explained; b. Planning the research: In this session all the various phases of the planning of research are explained: the EU finding policies and calls; the project cycle, the structure of the action and cost plan, the actors involved; the negotiation and the management of the european projects; c. Exploitation of the research results; d. Intellectual property: IP rights, protection methods, patents; management and exploitation of the IP; patent databases. This course is mandatory for all PhD students DATES: TBD | |
| 20 | Bibliographic research, scientific writing and dissemination: tools, techniques and strategies (12 hrs, 3 ECTS) |
| LECTURER: Manuel Ciccarelli, Simone Cocchi, Valentina Davighi, Nicola de Bellis, Andrea Solieri – Ufficio Bibliometrico – Servizio Open Science SYLLABUS: The course aims at teaching the skills and the knowledge for using the specific library services and resources for doctoral students; for being productive in information retrieval, in preparing a bibliography, in writing a scientific article, so to support the Ph.D. students in their path with an outlook at their post-doc career. The course will provide an in-depth introduction to the following aspects: • resources for basic information retrieval like OPACs, UNISTORE and OneClick discovery tool • resources for advanced information retrieval like scientific databases like Scopus and Web of science. • the scientific journal as the main vehicle for STEMM research dissemination. • workflow of a scientific article; (copy)rights and dues of an author, plagiarism, citations and bibliographies. • How to work with a reference manager software. • Improving research impact: from bibliometric analysis to research evaluation; journals evaluation (from authoritative to predatory); differences among ahead of print, post print, editorial version of a publication; • the Open Access initiative and what this means for the authors; what ASN and VQR are with examples and exercises; how the repository IRIS works; checking author profiles on Scopus, Publons and ORCID. This course is mandatory for all PhD students DATES: TBD |
