Courses of Academic Year 2023/2024

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.

LEGAL ISSUES FOR AUTOMOTIVE ENGINEERS

Program:
This course examines the interaction between law and engineering, in order to provide students with an interdisciplinary perspective on nowadays global challenges. The course will deeply touch on the so-called 'Law by design' approach, comparing efficient solutions set by governments, parliaments and technical players on the domestic and the international stage.

Exam:
Not yet defined

CFD: 3


IP Law

Program:
This course examines Intellectual Property laws by means of a comparative approach, focusing on international and domestic rules and proceedings, in order to provide engineering students with an overview on a central topic in their prospective career. The course will deeply touch on existing intellectual property laws, which encourage and protect intellectual goods, usually for a limited period of time, and their main output: to provide an economic incentive for design and creation, preventing illegal copying, and stimulating innovation and technological progress. There are various types of intellectual property, the most well-known being copyrights, patents, trademarks, and trade secrets, which will be analyzed in class.

Exam:
Not yet defined

CFD: 4


Power electronics converters for automotive applications: trends and challenges

Program:
Program: Module 1 (4h) Multi-level converters, an automotive prospective for high speed drive applications Module 2 (4h) High performance DC/DC converters for automotive applications Module 3 (4h) Potential of Active thermal control for reliability improvement of automotive drives.

Exam:
Not yet defined

CFD: 5


Academic English Workshop II

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


Data Analytics

Program:
The aim of the course is to introduce students to two important elements of data engineering technology that makes it possible to extract valuable knowledge from “Big Data”, namely distributed data processing using the MapReduce framework, and data analytics on large graphs. In each case, the course will first introduce fundamental theoretical and architectural concepts, and then present technology for using MapReduce and querying large graphs, respectively. For MapReduce, we present examples of algorithms that can be successfully parallelised and thus are able to take advantage of distributed data architectures, and we will suggest practical exercises using the Spark and Hadoop technology stack. Regarding graph analytics, we focus on community detection algorithms as an example, and we will use the Neo4J graph DBMS along with the Graph Data Science library for practical exercises.

Exam:
Not yet defined

CFD: 5


The basic principles of project management

Program:
The course aims at providing the theoretical and practical fundamental knowledge of project management as a required tool for the design and the development of a project. The topics will be covered within the framework of PMBOK (Project Management Body of Knowledge) of PMI (Project Management Institute).

Exam:
Not yet defined

CFD: 3


Applied spectroscopic methods and Working principles of organic optoelectronic devices

Program:
The course aims at introducing electron and optical spectroscopies for the characterization of the chemical and physical properties of materials. Optical and electron spectroscopies are widely used analytical tools, even at industrial level. The basics of spectroscopic characterization tools will be given, together with examples of applications. During the course a section aims at providing the fundamental conceptual elements at the basis of the working of electronic and opto-electronic organic devices together with the context of exploitation of this technology from the more consolidated applications already in the market to the most pioneering approaches.

Exam:
Not yet defined

CFD: 3


Semiclassical and quantum mechanical foundations of modern nanoscale FET device operation

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. Selected elements of quantum mechanics are merged with classical electrostatics and transport theory to yield a state of the art description of advanced nanoscale FET. Conventional, strained and alternative channel materials, quasiballistic transport in a 2D or 1D electron gas, FinFET, double gate FDSOI, nanowire, nanosheet and nanofork gate all around device architectures will be addressed.

Exam:
Not yet defined

CFD: 3


Modelling, Identification and Control of Robot

Program:
The course introduces the theory of optimal predictive control (Model Predictive Control), starting from the formulation of the optimal control problem with quadratic cost for linear systems (LQ control). The main stability and persistent feasibility results will be illustrated using numerical examples and applications in the automotive and Matlab toolboxes such as MPT and MPC toolbox.

Exam:
Not yet defined

CFD: 3


Deep Learning Framework Implementation

Program:
The course will show how the operations that we normally delegate to a deep learning framework are implemented, starting from the three-year experience of developing the EDDL library, during the DeepHealth project.

Exam:
Not yet defined

CFD: 5