Academic English Workshop I

Lecturer: Prof. Marco Socciarelli – Future Education Modena

Schedule:

• 23/04/2025        10am-1pm         Meeting Room - MO26 – 1st floor
• 24/04/2025        10am-1pm         Meeting Room - MO26 – 1st floor
• 28/04/2025        10am-1pm         Meeting Room - MO26 – 1st floor
• 29/04/2025        10am-1pm         Meeting Room - MO27 – 1st floor

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

Advanced graph mining and learning

Lecturer: Prof. Davide Mottin - Aarhus University

Schedule:

• 05/05/2025        9am-1pm            Meeting Room - MO27 – 1st floor
• 05/05/2025        2pm-6pm           Meeting Room - MO27 – 1st floor
• 06/05/2025        9am-1pm            Meeting Room - MO27 – 1st floor
• 06/05/2025        2pm-6pm           Meeting Room - MO27 – 1st floor

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:
Assignment

CFD: 4

Academic English Workshop II

Lecturer: Prof. Marco Socciarelli – Future Education Modena

Schedule:

• 12/05/2025        10am-1pm         Meeting Room - MO26 – 1st floor
• 13/05/2025        10am-1pm         Meeting Room - MO27 – 1st floor
• 14/05/2025        10am-1pm         Meeting Room - MO26 – 1st floor
• 15/05/2025        10am-1pm         Meeting Room - MO26 – 1st floor

Program:
The 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

Advanced CMOS devices and emerging trends for future nanoelectronics

Lecturer: Prof. Luca Selmi

Schedule:
9-12 and 19-20 June 2025

Program:

Exam:
Not yet defined

CFD: 3

Study of the electronic components from the simulation perspective

Lecturer: Dr. Marco Villena – University of Granada

Schedule:

• 16/06/2025        10am-1pm         MO25 – Lab P0.1
• 17/06/2025        10am-1pm         MO25 – Lab P0.1
• 18/06/2025        10am-1pm         MO25 – Lab P0.1
• 19/06/2025        10am-1pm         MO25 – Lab P0.1

Program:

• Introduction to basics simulation methods (1.5 hours)

  What the simulation is and why it is important.
  Type of simulation methods (ab initio, Monte Carlo, finite elements, compact models).
  Overview of the available tools.

  Introduction to Ginestra (1.5 hours)

  What is Ginestra?
  How to use Ginestra?
  How to explore the simulation results it provides us?
  How to design a Design of Experiment (DoE)? How to create a new device geometry?

  Brief introduction to the semiconductor physics (1 hour)

  Basics concepts, Type of semiconductors, Bands diagrams and Density of State (DOS).
  Non-ideal materials: Role of the defects.

  PN junction (1 hour)

  Theoretical introduction. Characterization by the bands' structure.
  Simulation using Ginestra and comparison with the theoretical predictions.
  Design of a diode following some technological requirements supported by Ginestra.

  BJT transistor (1 hour)

  Theoretical introduction. Characterization by the band structure.
  Simulation using Ginestra and comparison with the theoretical predictions.

  MOSFET transistor (3 hours)

  Theoretical introduction. Characterization by the band structure.
  Simulation using Ginestra and comparison with the theoretical predictions.
  Problems related to the miniaturization of the device (short-channel effect, leakage current, etc.) Alternative geometries and why (FinFET, GAA transistor, etc.)
  Design of a transistor following some technological requirements supported by Ginestra.

  Introduction to the new technologies (2 hours)

  Introduction to RRAM devices.
  Introduction to FeRAM devices.

Exam:
Written test (1 hour)

CFD: 3

Trends and challenges for the security of Machine Learning systems

Lecturer: Prof. Fabio Pierazzi - Univ. College London

Schedule:
7-11 July 2025

Program:
Machine Learning (ML) has shown incredible success in many applications, and this trend was followed also by cybersecurity to deal with an increasing number of threats in network intrusion and malware detection. However, using ML increases also attack surface, and opens the way to attackers to evade detection systems. It is then important to understand how to assess the risks and the attack surface of ML models. While Machine learning is going to be a main focus, we will focus in general on hostile environments in which attackers aim to compromise systems to take some advantage out of it (e.g., compromising the availability, integrity or confidentiality of a Machine Learning system). This course will provide you with an overview of the challenges and trends in assessing risks and robustness of applying machine learning in cybersecurity, i.e., contexts that consider the presence of an adversary, and that require modification of complex objects (e.g., software). The outcome is expected to be the understanding of fundamental challenges of applying machine learning in adversarial settings with evolving scenarios, with case studies and labs on the malware detection domain.

Exam:
Extended research abstract

CFD: 5

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

Lecturer: tbd

Schedule:
25-29 August 2025

Program:

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:

• 15/09/2025        10am-1pm         Meeting Room - MO27 – 1st floor
• 16/09/2025        10am-1pm         Meeting Room - MO27 – 1st floor
• 17/09/2025        10am-1pm         Meeting Room - MO27 – 1st floor
• 18/09/2025        10am-1pm         Meeting Room - MO27 – 1st floor

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

Reliability of electron devices

Lecturer: Prof. Francesco Maria Puglisi, Prof. Andrea Padovani – UniMORE

Schedule:
tbd

Program:
In this course we will introduce the main concepts relate to the reliability analysis of electron devices. The main failure mechanisms that limit the reliability of modern electron devices will be reviewed, and the required mathematical tool introduced (such as the Weibull distribution). The main models adopted today to explain key phenomena, such as Time-Dependent Dielectric Breakdown, Bias Temperature Instability, Hot Carrier Degradation, Random Telegraph Noise, will be given, together with a detailed analysis on the role of defects in different materials. Open questions in the literature will be also presented.

Exam:
tbd

CFD: 3

X-ray detectors design: principle and experiments

Lecturer: Dr. Giovanni Pinaroli - Brookhaven National Laboratories

Schedule:

• 01/09/2025        2pm-6pm           Meeting Room - MO26 – 1st floor
• 02/09/2025       9am-1pm            Meeting Room - MO26 – 1st floor
• 03/09/2025       9am-1pm            Meeting Room - MO26 – 1st floor

Program:
The course/lecture will cover the design and principles of X-ray detectors for scientific experiments covering a wide range of applications: Synchrotron, FEL and astrophysics. Focus will be given to the design and implementation of the CMOS readout with particular emphasis on low noise performances and pixelated architectures.

Exam:
Written test

CFD: 3

Querying and transforming property graphs

Lecturer: Prof. Angela Bonifati - Lyon 1 University

Schedule:
20-24 October 2025

Program:
Graph data modeling and querying arise in many practical application domains such as social, biological and fraud detection networks where the primary focus is on concepts and their relationships. Property graphs are expressive data models coupled with complex graph patterns involving multiple labels and lightweight recursion in their querying endeavors. In this course, I present a concise unified view on the current challenges which arise over the complete life cycle of formulating and processing queries on property graphs. To that purpose, I present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the predominant data model adopted by modern graph database systems. I also introduce property graph schemas and graph indexing techniques for label-constrained reachability queries on graph databases. I will present graph transformation and repairing techniques that capture the intricacies of the property graph data model and query languages. The theoretical part will be coupled with practical work with a focus on real-world datasets using the openCypher query language on top of an open-source graph database.

Exam:
Practical lab on graph queries in Neo4j

CFD: 3