Courses of Academic Year 2025/2026
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.
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 offers first-year PhD students a practical overview of the core activities that define their doctoral experience. We examine the bureaucratic framework of the program, the milestones to track, and the expectations for progression. A major focus is placed on producing and disseminating research—understanding publication venues, timelines, and effort, as well as preparing presentations for internal evaluations and international conferences. The session provides a realistic map of the challenges and opportunities ahead.
Exam:
no exam
CFD: 1
From Bayesian Estimation to Kalman Filtering. Application to smart connected agents
Lecturer: Prof. Laura Giarrè – UniMORE
Schedule:
January 26th 11am-1pm and 3pm-5pm Room P.2.3 MO25 or remote
January 27th 10am-1pm and 3pm-5pm Room P.2.3 MO25 or remote
January 29th 10am-1pm Room P.2.4 MO25 or remote
Remote link: https://teams.microsoft.com/meet/34688126000486?p=e0ut30OhGvEGCGp49e
Program:
In this teaching the following topics will be addressed:
Introduction
- Smart sensing from Noisy Data
- ML vs Estimation
- Parametric vs Nonparametric Estimation
- Kalman filtering, Bayesian approach, and ML
- Applications of Kalman Filtering
- Literature on Kalman filtering
Estimation Theory
- Parametric estimation
- Properties of estimators
- Minimum variance estimator
- Maximum likelihood estimators
- Bayesian estimation
Least square Algorithm (RLS,LMS)
- Linear regressions
- LS Estimates: Statistical properties
- Bias, variance, covariance
- BLUE estimation
- RLS algorithms
- LMS algorithms
- The relation between Kalman and RLS
Kalman Filtering
Markov Processes
- Linear Stochastic System
- State Estimation
- Kalman filter
- Kalman filter in Prediction form
- Asymptotic Properties of Kalman Filter
- EKF
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