Courses of Academic Year 2022/2023

A preliminar list of the didactic offer of the ICT doctorate follows. The list will be completed and updated during the year.
Seminars on Bibliometrics and research Evaluation will be offered by UNIMORE for all the doctorate courses.

Scalable data processing for data science: architectures and programming models

Lecturer: Prof. Paolo Missier
Prof. Paolo Missier is Professor of Scalable Data Analytics with the School of Computing at Newcastle University, where he leads the School of Computing's post-graduate academic teaching on Data Engineering for AI (aka Big Data Analytics), and a Fellow (2018-2023) of the Alan Turing Institute, UK's National Institute for Data Science and Artificial Intelligence. His current research interests focus on the challenges of Health Data Engineering and Data Science, as well as on the efficient generation of data provenance to make Data Science more explainable and trustworthy.

Schedule:
Tuesday November 22 Room M0.2 11:00 a.m. – 1:00 p.m.
Wednesday November 23 Room M0.1 9:00 a.m. – 11:00 a.m.
Friday November 25 Room M0.2 9:00 a.m. – 11:00 a.m.

Program:
Key notions in distributed data processing, from theory (MapReduce) to the Hadoop architecture (Hadoop) will be introduced. The PySpark implementation of the framework will then be used for practical lab sessions, where students will be able to experiment with simple exercises, and then tackle the more complex challenges of making their solutions scalable for increasingly large input sizes

Exam:
Not yet defined

CFD: 3


Large Scale Geospatial Data Management

Lecturer: Prof. José Ramón Ríos Viqueira
José R.R. Viqueira is Associate Professor at the Department of Electronics and Computer Science of the University of Santiago de Compostela (USC), Spain, a founding member of the COGRADE (Computer Graphics and Data Engineering) research group of the USC and a member of the research staff of the Centro Singular de Investigación en Tecnoloxías Intelixentes (CITIUS). His current research lines are related to the management of very large scientific data sets, with special emphasis on spatio-temporal and sensor data. He is the author of more than 50 international research papers (10 relevant papers in the last 5 years). He has participated in 31 competitive research projects and 40 research and development contracts with companies and public administrations.

Schedule:
5-7 December 2022 (12 hours), meeting room first floor of MO27 building, and streamed on Teams. Monday, Tuesday and Wednesday 9:00 - 10:00 Lesson 10:30 - 13:30 Hands on session

Program:
Most of the entities about which organizations record data are located on the Earth surface. Therefore, in many cases, either the location and/or shape of those entities on geographic space, or the spatial (spatio-temporal) variation of some of their properties might have to be collected, recorded, and analyzed. The course will describe two main types of geospatial datasets: geospatial Features (entities with geometric properties that define their location and shape on geographic space) and geospatial coverages (collections of properties that change over space and possibly also over time). New solutions in the scope of Big Data technologies that enable the management of geospatial data at large scale will also be presented.

Exam:
Exercises related to each hands on session

CFD: 5


IP4ENGINEERS

Lecturer: Prof. Avv. Isabella Ferrari

Schedule:
14, 17, 21, 24, 28, 31 Marz 2023
Tue 8.30-11 a.m.; Fri 8.30-10 a.m.
Classroom schedule will be published here: https://www.ip4engineers.unimore.it

Program:

https://www.ip4engineers.unimore.it

 

The project IP4ENGINEERS, co-funded by the EU Commission under the Erasmus+ Programme and by the University of Modena and Reggio Emilia, introduces a new teaching module on intellectual property protection within the engineering degree courses of the said University of Modena and Reggio Emilia, in Italy.

The module touches in depth on European IP laws, through a comparative and interdisciplinary approach, to provide engineering students with knowledge on a topic central to their future careers.

 

The overall goal is to train competent professionals, who can actively contribute to strategic and business decisions, collaborating on industrial and economic policies from small to large scale: i.e, from local, regional, and national level to the European one.

 

To encourage technological and industrial development, it is necessary to ensure effective protection to intellectual properties, strengthening economic incentives for new inventions, as well as preventing illegal copying.

In this context, it is useful to equip engineers with the technical and legal tools to navigate the system. In fact, while it is advisable to seek professional guidance from consultants specialized in trademarks, patents, trade secrets, etc., it is also necessary for the engineers themselves to be familiar with IP procedures, standards, national and international bodies, so that they can design and market their products wisely and profitably.

 

These competencies are fundamental to boost research, development, and innovative production in Europe, for greater global competitiveness of the manufacturing sector.

Exam:
Not yet defined

CFD: 4


Data Profiling

Program:
Data profiling is the process of examining the data available in an existing data source and collecting statistics and information about that data. It encompasses a vast array of methods to examine data sets and produce metadata. Among the simpler results are statistics, such as the number of null values and distinct values in a column, its data type, or the most frequent patterns of its data values. Metadata that are more difficult to compute involve multiple columns, such as inclusion dependencies or functional dependencies. Data profiling is relevant as a preparatory step to many use cases, such as query optimization, data mining, data integration, and data cleansing. Topics of the lecture include the deficient detection of unique column combinations, functional dependencies, inclusion dependencies, order dependencies, and denial constraints, and the semantic interpretation of profiling results.

Exam:
Not yet defined

CFD: 5


Optical System Design Course

Lecturer: Prof. Martial Geiser
Prof. Geiser Geiser, physicist, has a broad experience in the field of first-order lens design, ophthalmic instruments, ocular blood flow measurement, bioluminescence, and fluorescence measurement within microfluidic systems for water and food quality assessment, all with an emphasis on systems design.

Schedule:
every Tuesday from 16.00 to 19.00 in room P0.2 and Wednesday from 8.00 to 10.00 in P2.2.

Program:

Parte teorica

- Ottica del primo ordine e invariante lagrangiana

- Principio del diagramma di Delano

- Qualità dell'immagine, aberrazione, ...

- Esempi di sistemi di lenti (telescopio, microscopio, oculari, occhio umano...)

Parte pratica

- Progettazione del layout ottico di diversi sistemi ottici come tomografia ottica, velocimetri, scansione laser, oftalmoscopio, fotocamere fundus, microscopi, ...

More details: http://personale.unimore.it/rubrica/contenutiad/mageiser/2022/73604/N0/N0/9999

Exam:
L’esame è costituito da una prova scritta finale di due ore

CFD: 0


Semiclassical and quantum mechanical foundations of modern nanoscale FET device operation- part II

Lecturer: Prof. Luca Selmi

Schedule:
The schedule of the lecture will e published in early spring 2023. All lectures will be delivered at the DIEF.

Program:
Based on a succinct and highly focused review of a few key concepts of quantum mechanics, the course will introduce the foundations of the semi-classical approach to nanoscale electron device modeling. Elements of classical and quantum mechanics will be merged to yield a state-of-the-art modeling framework suited to describe advanced nanoscale FETs. Conventional, strained and alternative channel materials, quasi-ballistic transport in a 2D or 1D electron gas as achieved in FinFET, double gate FDSOI, nanowire, nanosheet and nanofork gate all around device architectures will be addressed

Exam:
Not yet defined

CFD: 3


Graph Data Analysis & Exploration

Lecturer: prof. Matteo Lissandrini, Aalborg University, Denmark

Schedule:
29-30 May (10-13, 14-17) and 31 May (10-12 -- if needed) in the meeting room at MO27, first floor

Program:
Complex data can be represented by the structure of the relationship between objects within a graph. Graphs are a fundamental tool for modelling social, technological, and biological systems, either as networks (e.g., social networks) or as more expressive semantic graphs (also called Knowledge Graphs). However, the widespread adoption of graph data, especially when to model and integrate different data sources, along with their complex generation processes, have made graphs very complex objects, requiring dedicated methods for their understanding. This course will present fundamental concepts and methods adopted for the analysis and exploration of graph data across different applications and use cases. It will provide different formalisms to model graph data in different domains (networks, KGs, and Property graphs) along with concepts adopted to describe fundamental structural characteristics, in particular approaches used for graph understanding at the node level, link level, and at the graph level, e.g., centrality measures, density, and modularity. It will further cover important analytical tasks, such as subgraph search, frequent graph mining, graph summarization, and example-based search and exploration techniques. The course will be accompanied by hands-on sessions where some of the approaches will be adopted to analyze real-world graph data in a typical data-science environment by adopting python, jupyter notebooks, and interacting with a graph DBMS.

Participants are invited to fill in the anonymous form:
https://forms.gle/v7RVx7hmKZAha5zM6
in order to provide the teacher with useful information to better define the detailed content of the course.

Exam:
oral test

CFD: 5


Academic English Workshop I

Lecturer: Silvia Cavalieri

Schedule:

- 2 Maggio - martedì - 11-14 in aula P0.5

- 4 Maggio - giovedì - 14-17 in aula P0.1 

- 9 Maggio - martedì - 11-14 in aula P0.5

- 11 Maggio - giovedì - 14-17 in aula P0.1

Program:
The workshop aims at giving an overview of the linguistic conventions adhered to by the English-speaking academic community, focussing on aspects such as the structure of research articles, the writing of abstracts and the preparation of conference presentations. More specifically, the workshop will try to raise the participants' awareness of the rhetorical and discourse patterns characteristic of academic English, introducing them to the skills required to produce texts which are accurate both from a grammatical and a stylistic point of view. Ample opportunities will be given for practice, both in the analysis and the production of texts. In particular, special attention will be given to argumentative writing techniques and to special genres such as the abstract and conference presentations.

Exam:
Not yet defined

CFD: 5


Academic English Workshop II

Lecturer: Silvia Cavalieri

Schedule:

- 13 Giugno - martedì - 11-14 in aula P0.5
- 15 Giugno - giovedì - 14-17 in aula P0.1
- 20 Giugno - martedì - 11-14 in aula P0.5
- 22 Giugno - giovedì - 14-17 in aula P0.1

Program:
The main objective of the workshop is to provide PhD students with the knowledge of the theoretical and linguistic models that characterize the English academic language. The seminar intends to introduce language and stylistic tools t to write accurate texts. In particular, the AEWII will focus on some specific written genres of the academia, i.e. doctoral theses and posters and Phd students will have extensive opportunities to practice both with text analysis and with their production. Special attention will be given to argumentative techniques of posters ‘ oral presentations.

Exam:
Not yet defined

CFD: 5