PhD Survival Kit: Everything You Need to Know (and No One Tells You)

Lecturer: Prof. Carlo Augusto Grazia

Schedule:
Dec 2025 - 4 hours

Program:
This course delves into the fundamentals of graph mining and graph machine learning, introducing foundational techniques like PageRank and Spectral Theory that underpin today’s advanced graph analysis methods. We will explore introductory concepts in graph machine learning, including Graph embedding (e.g., DeepWalk, VERSE, NetMF), Graph Neural Networks (e.g., GCN, GAT, GIN), to bridge traditional and modern approaches. By the end of the course, students will have a preliminary set of skills to work with graph data, perform basic analyses to uncover network structures, and make predictions based on graph information. In short we Will touch upon (1) traditional graph mining methods, (2) deep and shallow graph embeddings, (3) evaluation measures and applications.

Exam:
no exam

CFD: 1

From Bayesian Estimation to Kalman Filtering. Application to smart connected agents

Lecturer: Prof. Laura Giarrè – UniMORE

Schedule:
Jan 2026

Program:

In this teaching the following topics will be addressed:

• Bayesian Estimation
• Kalman Filtering
• Extended Kalman filtering
• Recursive Least Square
• Application to smart connected agents (vehicles, humans) for sensor fusion and localization

Exam:
t.b.d.

CFD: 3

Academic English Workshop II

Lecturer: t.b.d.

Schedule:
May/June 2026 - 12 hours

Program:
he main objective of the workshop is to provide PhD students with the knowledge of the rhetorical and linguistic models that characterize the English academic language. The seminar intends to introduce language and stylistic tools 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 and oral presentations.

Exam:
Written assessment: writing a paper introduction; Oral assessment: poster presentation.

CFD: 3

Academic English Workshop I

Lecturer: t.b.d.

Schedule:
May/June 2026 - 12 hours

Program:
The workshop aims at giving an overview of the linguistic conventions adhered to by the English-speaking academic community, focusing 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:
Written assessment: abstract writing; Oral assessment: conference presentation.

CFD: 3

Methodology and Techniques for Neurophysiological Research

Lecturer: Prof. Daniela Gandolfi and Prof. Fausta Lui – UniMORE

Schedule:
16 hours

Program:

In this teaching the following topics will be addressed:

• Basic Neurobiology
• Synaptic connections and neuronal properties
• fMRI, Broca areas and brain functions
• MRI principles, DTI, DWI, tractography, EEG
• Point Neuron models and Brain virtual Twin

Exam:
Not yet defined

CFD: 4

Uprising thermal issues in (nanoscale) electronics

Lecturer: Prof. Luca Selmi

Schedule:
June 2026

Program:
t.b.d.

Exam:
t.b.d.

CFD: 3

Enhance your Soft Skills: ICT Summer School for Personal and Professional Development

Lecturer: Various lecturers

Schedule:
4 days in August 2026

Program:
t.b.d.

Exam:
The participation to the summer camp is mandatory for first year students.

CFD: 5

An introduction to signal processing methods for automotive MIMO radars

Lecturer: Prof. Pasquale Di Viesti – UniMORE

Schedule:
Sept 2026

Program:
The purpose of the course is to provide an overview of radar systems by addressing both fundamental principles and advanced signal processing techniques. After an introduction to the essential components and operation of radars, the main types of antennas, beamforming techniques, and the impact of noise on system performance will be analyzed. Different types of radar waveforms will be explored, with emphasis on the principles of Frequency-Modulated Continuous Wave (FMCW) and Stepped-Frequency Continuous Wave (SFCW). The course will also cover advanced radar systems, such as phased array and multiple-input multiple-output (MIMO) systems, focusing on beamforming techniques, target localization, and Direction-of-Arrival (DoA) estimation. The final part of the course will be devoted to hands-on MATLAB sessions on distance estimation, slow-time signal analysis, and filtering techniques. Finally, advanced applications such as motion detection and respiratory and heart rate estimation using radar will be explored.

Exam:
written test

CFD: 3