1Scalable data processing for data science (16 hrs, 4 ECTS)
LECTURER: Paolo MISSIER, Newcastle University, UK
SYLLABUS: The teaching offer is designed to complement teaching on Big Data Analytics, Foundations of Machine Learning, and Computational and Statistical Learning from typical Master Degrees in Computer Science/Informatics and in Maths (Data Science). The offer consists of a series of topical seminars and practical lab sessions, organised into two complementary parts, as follows:
– Part I: Scalable data processing for data science: architectures and programming models
– Part II: Data Engineering and Data Science for Healthcare and medicine applications: challenges and case studies.

In Part I, key notions in distributed data processing, from theory to the Hadoop architecture (Hadoop) are introduced. Two programming models for distributed data processing are presented and compared: Apache Spark and Dask. For both, practical sessions are organised in a lab, where students can experiment with simple exercises, and then tackle the more complex challenges of making their solutions scalable for increasingly large input sizes.
Part II presents elements of the important, complex, and rapidly evolving landscape of Health Data Science and Engineering. Examples of cutting edge results where AI has been successsfully applied to a variety of problems in healthcare will be presented, to illustrate how machine learning and AI are enabling a new generation of data-driven, personalised medicine. Selected papers will be offered to the students for independent reading and then discussion in class. Open challenges will be presented, including those of data curation, learning with “small data”, and explainability of AI models.
Part I: 22, 23, 24 November, 2022
Part II: 9, 16 March, 2023

2Introduction to Big Data Integration (4 hrs, 1 ECTS)
LECTURER: Donatella FIRMANI, Sapienza Università di Roma
SYLLABUS: Data Integration (DI) is the fundamental problem of building a unified view of data residing in different sources. Over the decades, different generations of DI techniques have succeeded. Nowadays, in the Big Data era, the scale at which data are produced and analyzed poses unprecedented challenges. Big Data Integration (BDI) is the set of techniques developed in response to those challenges and is different from traditional DI in 4 fundamental ways, related to the (i) volume, (ii) velocity, (iii) variety and (iv) veracity of the sources. This short course aims at providing an introduction to these methods and related notions.
DATES: 20 February, 2023
Room M0.2 (ground floor, Mathematics Building) 10:00 – 12:00
Room 1.7 (first floor, Mathematics Building) 14:00 – 16:00
3Digital twins in Industry 4.0: from monitoring to automated synthesis (4 hrs, 1 ECTS)
LECTURER: Francesco LEOTTA, Sapienza Università di Roma
SYLLABUS: Digital twins (DTs) are generally meant as digital interfaces to physical entities. This concept naturally applies to smart manufacturing where DTs may provide a powerful tool for tasks ranging from monitoring the status of the manufacturing process to automatically synthesize production plans able to deal with short term changes (e.g., disruptions) and long term changes (e.g., evolution of the market). In this course we will discuss technological tools and state-of-the-art techniques aiming at a fruitful application of the DT paradigm to Industry 4.0.
DATES: 21 February, 2023
Room “Laboratorio Zironi” (first floor, Mathematics Building) 09:00 – 13:00
4Privacy-enhancing technologies (12 hrs, 3 ECTS)
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.
19, 20, 21 September 2023 9:00 – 13:00

For inquiries contact the lecturer, Prof. Luca Ferretti (luca.ferretti@unimore.it)

5Advanced GPU programming – libraries for data science (16 hrs, 4 ECTS)
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. In the second part of the course, widely used CUDA libraries for numerical calculus and data science will be presented through extensive examples, such as cuBLAS, cuSOLVER and cuSPARSE for numerical optimization, cuFFT for signal processing and NPP for image processing.
05 September 2023 – 10:00 – 12:00 – Filippo Muzzini – lab M0.1 MO18 Edificio Matematica
06 September 2023 – 10:00 – 12:00 – Filippo Muzzini – lab M0.1 MO18 Edificio Matematica
07 September 2023 – 10:00 – 12:00 – Filippo Muzzini – lab M0.1 MO18 Edificio Matematica
08 September 2023 – 10:00 – 12:00 – Nicola Capodieci – lab M0.1 MO18 Edificio Matematica
12 September 2023 – 10:00 – 12:00 – Roberto Cavicchioli – lab M0.1 MO18 Edificio Matematica
13 September 2023 – 10:00 – 12:00 – Roberto Cavicchioli – lab M0.1 MO18 Edificio Matematica
14 September 2023 – 10:00 – 12:00 – Roberto Cavicchioli – lab Zironi MO18 Edificio Matematica
15 September 2023 – 10:00 – 12:00 – Roberto Cavicchioli – lab M0.1 MO18 Edificio Matematica

6Internet and Web of Things at the Edge (8hrs, 2 ECTS)
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.
18 April 2023 – 10:00 – 12:00
26 April 2023 – 15:00 – 17:00
2 May 2023 – 10:00 – 12:00
3 May 2023 – 14:00 – 16:00

The lectures will be held in room M2.2, Math building of the Department of Physics, Informatics and Mathematics, via Campi 213/b, Modena.

7Crowdsensing Systems (12hrs, 3 ECTS)
SYLLABUS: Crowdsensing systems represent an efficient way to collect data and analyze the dynamics about a specific environment. In this course, we will present the different characteristics of Participatory and Opportunistic Crowdsensing systems, and analyze the key challenges which such systems face. Specifically the course will analyze the problem of rewarding users in crowdsensing systems, privacy issues which may arise when dealing with crowdsensed data, and communication efficiently for the devices themselves. The course will be concluded by discussing future research directions.
DATES: March – June, 2023

8Efficient DL/ML models for embedded systems (12hrs, 3 ECTS)
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: 26, 27, 31 January, 2023

9Complexity Theory, On-Line and Approximation Algorithms (12 hrs, 3 ECTS)
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.
12 April, 2023 – h 11:00 – 13:00 – Room M2.3
19 April, 2023 – h 11:00 – 13:00 – Room M2.4
27 April, 2023 – h 11:00 – 13:00 – Room M2.4
3 May, 2023 – h 11:00 – 13:00 – Room M2.4
4 May, 2023 – h 11:00 – 13:00 – Room M2.4
10 May, 2023 – h 11:00 – 13:00 – Room M2.4

Rooms M2.3 and M2.4 are in the Math building of the Department of Physics, Informatics and Mathematics, via Campi 213/b, Modena.

10Energy efficiency for Real-time systems under sequential and parallel programming (12 hrs, 3 ECTS)
LECTURER: Houssam-Eddine ZAHAF, Audrey QUEUDET, Université de Nantes, France
SYLLABUS: This course will present  real-time systems programming  from energy efficiency and availability perspectives. Firstly,  theoretical fundamentals about  single-  and multi-processor real-time scheduling will be presented. Partitioned and global real-time multiprocessor scheduling will be deeply addressed. Secondly,  parallelization techniques for real-time systems, and their schedulability analysis will be presented. We will have a special focus of how parallelization can help to achieve timeliness, while reducing energy consumption as much as possible. Finally,  energy harvesting systems will be addressed. These systems are usually powered by intermittent energy sources, and must ensure timeliness even in the presence of  energy-sources fluctuation. For the second and third part, we present the current state of literature and open-issues related to these systems.
DATES: 24, 25, 26 May, 2023 – 9:00 – 13:00

Detailed schedule:
First Lecture 4h : (Houssam-Eddine ZAHAF) Introduction to real-time systems, and their programming, 9am-13am, 24/05.
Second Lecture 4h, (Houssam-Eddine ZAHAF) Minimizing energy consumptions, for multicore real-time systems, 9am-13am, 25/05.
Third Lecture 4h: (Audrey QUEUDET) Challenges in the design of energy-harvesting real-time systems, 9am-13am, 26/05.

The class will take place as a live streaming event.
Please use the following link to connect


For further information or questions you can write en email to the lecturers
Houssam-Eddine ZAHAF – Houssameddine.Zahaf@univ-nantes.fr
Audrey QUEUDET – Audrey.Queudet@univ-nantes.fr
11Introduction to complex systems (8hrs, 2 ECTS)
SYLLABUS: Many systems in nature, society and technology are composed of numerous parts that interact in non-linear ways. In these systems the emergence of intermediate structures is frequently observed. Paradigmatic examples are present in biology, but similar organizational aspects can be found in different kinds of systems. In social systems we can observe several intermediate bodies between the state and individuals: parties, associations, movements, trade unions, etc. At a bigger scale, alliances, federations and leagues of nations are present, intermediate organizations between the states and the whole of mankind. Likewise, we can observe the emergence of technological organizations based on the interaction between computers in artificial systems, or the presence of dynamic structures composed by computers, (semi)automatic systems and human beings in socio-technological systems. Intermediate-level structures, once formed, deeply affect the system as a whole, and therefore play a key role in understanding its behavior. The course aims to introduce the main issues of complex systems, and to present some of the approaches used in their study.
DATES: January – February, 2023

12Arm Architectures for High-Performance Real-Time (4 hrs, 1 ECTS)
LECTURER: Matteo Andreozzi, ARM Ltd – UK
SYLLABUS: The evolution of computer systems is bringing them constantly closer to the physical world by making machines interact with their surrounding reality. Industrial automation, robotics, aerospace and automotive industries drive increasing demands on both deterministic capabilities and compute performance into the Arm computer systems architecture.
This course will introduce elements of the Arm systems architecture and current and future solutions Arm is adopting, together with its partners, to enable the next generation of high-performance real-time computing.
The audience will be introduced to the Arm real-time compute activities, and how those activities will significantly impact all market segments where both performance and determinism are requirements.
15, 22 September, 2023 – 10:00 – 12:00
Videolecture (live streaming).


13Methods for social and economic science and data (24 hrs, 6 ECTS)
SYLLABUS: The course analyzes how socio-economic disciplines are influenced by data analytics methodologies. The course consists of two parts. The first part presents a historical excursus on traditional socio-economic research methodologies, both those of a qualitative nature and those of a quantitative nature. The second part of the course addresses the new frontier of digital methods for social and economic research. The objective of the second part of the course is not simply to reflect on digital methods as a mere adaptation of traditional methodologies, but rather to seize the new opportunities and new limits that digital environments offer to study social and economic changes. The course will provide a solid foundation for using qualitative and quantitative methods in socio-economic research by making the most of the opportunities of digital data science.

14Analysis and critique of data visualizations, spaces and their representations   (12 hrs, 3 ECTS)
LECTURER: Federico Montanari, UNIMORE – DCE
SYLLABUS: This class offers an in-depth analysis and critique of data visualizations, spaces and their representations, on the basis of research experiences and courses at international level (think of authors such as Manovich, or important research centers such as EHESS Paris, or MIT). The first part of the class deepens the areas of data visualization through maps, graphs, and other tools. The second part of the class  focuses on the technical and social problems of the use of these maps in relation to lived and represented spaces, their cultures and social contexts. The fields are those related to the theme of urban spaces, smart cities, spatial maps, research through the use of geolocations, urban and territorial ethnographies.
DATES: July, 2023

15Unveiling Historical Relations Across Human Languages with Data Science: Computational Phylogenetics in Linguistics (12 hrs, 3 ECTS)
LECTURER: Andrea Ceolin, Cristina Guardiano, UNIMORE – DCE
SYLLABUS: By relying on computational techniques, algorithms and data analysis methods proper of data science, quantitative phylogenetics has developed automatic tools for  to build taxonomies and hierarchical trees of biological entities, to explore their phylogenetic relations, discover common ancestors, date their splits, and reconstruct unattested stages. Over the past 20 years, these methods have been applied to linguistic classifications as well, to automatically compare various types of language data, generate hypotheses of historical relation across languages and language families, aid in automatic cognate identification, explore dynamics of language evolution, reconstruct migration patterns, and compare linguistic, genetic and cultural evolution of human populations. This course discusses the application of such computational phylogenetic tools and taxonomic algorithms to the investigation of historical relations across human languages.

16Quantitative and formal modeling of historical sciences (12 hrs, 3 ECTS)
LECTURERS: Cristina Guardiano, Giuseppe Longobardi, UNIMORE – DCE, University of York
SYLLABUS: The implementation of quantitative models, computational tools and automatic algorithms of data collection and analysis has brought into human sciences models, idealizations, and explanatory standards typical of natural sciences. This course explores how these tools are extended and applied to those human sciences that specifically deal with history and cultural transmission. Focusing on the historical investigation of language diversity, the course will show how the application of computational techniques for data processing and analysis, in combination with the adoption of abstract cognitive language structures as taxonomic characters for phylogenetic reconstruction (Irimia et al. 2022), brings about the possibility to address large-scope genealogical issues, to look for general principles on possible historical evolution which cannot be revealed by archeology or demography alone, and ultimately to contribute some of the required heuristics and tools for a deeper investigation of human history.

17Coding and Comparing Syntactic Data (24 hrs,  6 ECTS)
LECTURERS: Cristina Guardiano, UNIMORE – DCE
SYLLABUS: The implementation of quantitative models, computational tools and automatic algorithms of data collection and analysis has brought into human sciences models, idealizations, and explanatory standards typical of natural sciences.
This course explores how these tools are extended and applied to those human sciences that specifically deal with history and cultural
Major contents:
– introduction to formal models of human language structure and diversity: parameters, parameter systems, parameter setting
– application of computational techniques to code, annotate and parse linguistic data (syntactically annotated corpora)
– application of computational techniques for data processing and analysis to the quantitative assessment of language relatedness and to phylogenetic reconstruction
DATES: 30, 31 March 2023 – 3, 4 April 2023

18Labour market, intelligence and digital organization (12hrs, 3 ECTS)
LECTURER: Matteo Rinaldini, UNIMORE – DCE
SYLLABUS: The course deals with key conceptual, methodological and organizational features in using Big Data both for the so-called labour market intelligence (LMI), and for human resource management. The aim is to explore opportunities and constraints in using refined (granular) Big Data analysis of labour market and occupational structure (for example, mapping skills, identifying discrepancies and obsolescence of skills and carrying out predictive analysis for new jobs in quasi-real time), with particular attention to the main structural changes such as organizational changes in companies, the reproduction of inequalities, the insider-outsider gap, the retraining and disqualification processes and the interaction between internal and external labor markets.
27, 29 June; 6July, 2023 – h 10:00 – 14:00
The lectures will be held in Sala riunioni, 2nd floor, Dipartimento di Comunicazione ed Economia, UNIMORE, Viale Allegri, 9, Reggio Emilia

19Sociology and Sociosemiotics of Data  (12 hrs, 3 ECTS)
LECTURER: Federico Montanari, UNIMORE – DCE
SYLLABUS: The course analyzes the effects that data and technologies have on current social systems. Through studies in the sociology of sciences and technologies, the course provides a point of view that helps to balance technical-computational aspects with issues of social responsibility. The topics of the course concern the use of data from a technological and social point of view. The sociological and sociosemiotic areas of interest are STS (Science and technological studies) and ANT (Theory of actor networks).
4, 11, 18 July, 2023 – h 14:00 – 18:00
The lectures will be held in Sala riunioni, 2nd floor, Dipartimento di Comunicazione ed Economia, UNIMORE, Viale Allegri, 9, Reggio Emilia

20Business Model Innovation (12 hrs, 3 CFU)
SYLLABUS: The course aims to evaluate how data-driven management, digitalization of internal and external processes and Artificial Intelligence (AI) applications in market relationships could impact on firms’ economic performance and innovation rates of business models, a new and relevant unit for analyzing strategic and organizational growth paths of firms. The course will introduce the main research streams and the most promising research avenues in the current debate, specifically focusing on relationships among  sustainability and circular economy, on one side, and digitalization, applied data science and AI, on the other side.
20, 21, 26 April, 2023 – h 9:00 – 13:00

The lectures will be held in room “Sala Riunioni”, Palazzo Dossetti, Viale Antonio Allegri, 9, Reggio Emilia

21Corsi Di Formazione Complementare Per Dottorandi E Assegnisti Ediz. 2022/2023 (24 hrs, 6 CFU)
LECTURER: Barbara Rebecchi, Ferdinando Di Maggio, Federica Manzoli, Nadja Seding, Giulia Catellani, Valeria Bergonzini, Valeria Goldoni, Ufficio Ricerca Internazionale UNIMORE
SYLLABUS: Il corso si compone di 4 sessioni modulari:
a.    Politiche della ricerca e innovazione: In questa sessione viene spiegato ai dottorandi da dove vengono i soldi per la ricerca. Vengono introdotte le opportunità e i percorsi per la ricerca e l’innovazione nazionali e internazionali.
b.    Progettare la ricerca: In questa sessione vengono illustrate le varie fasi della progettazione della ricerca, dalle politiche ai bandi di finanziamento europei; il ciclo del progetto, la struttura del piano delle azioni e dei costi, gli attori; la negoziazione e la gestione dei progetti europei;
c.    La valorizzazione dei risultati di ricerca:
d.    La proprietà intellettuale: I diritti di proprietà intellettuale, i metodi di tutela, i brevetti; Come scrivere le rivendicazioni; Gestire e sfruttare la PI; Banche dati brevettuali

Il corso consiste in una parte di lezioni asincrone (video), già raggiungibili al link sottostante e per cui al termine è prevista la compilazione di un questionario, più una parte di lezioni sincrone in streaming (o dal vivo), prevista per le date indicate sotto.
DATES: lezioni sincrone (live workshops) – 21, 22 March, 2023

martedì 21 ore 9.30 – 10.45 – Bibliographic databases and their advanced tools: Scopus, Web of Science and Iris Unimore –  Andrea Solieri e Simona Assirelli  – Ufficio Bibliometrico UNIMORE;
martedì 21 ore 11.00 – 13.00 –  European research programs; international opportunities for young researchers – Ferdinando Di Maggio e Irene Chini -Ufficio Ricerca Internazionale DRTTTM UNIMORE;
mercoledì 22 ore 9.30 – 11.00 – Terza Missione e Public Engagement –Valentina Lomi – Ufficio Terza Missione DRTTTM UNIMORE
mercoledì 22 ore 11.00 – 13.00 – Technology transfer: methods and examples – Giulia Catellani, Valeria Bergonzini, Filippo Zagni – Industrial Laison office -DRTTTM UNIMORE  
mercoledì 22 ore 14.30 – 16.30 – From Research to innovation – Prof. Bernardo Balboni – Dipartimento di Economia “Marco Biagi”

The workshops will be held in the room “Aula Convegni”, first floor of the building Giurisprudenza, Via S. Geminiano, 3, Modena
Link to the course webpage

22Bibliographic research, scientific writing and dissemination: tools, techniques and strategies (12 hrs, 3 CFU)
LECTURER: Simona Assirelli, Michele Pola, Ufficio Bibliometrico – SBA – UNIMORE
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.
DATES: 2, 3, 8, 9 February, 2023
Link to the course webpage