Provenance-Based Data Curation: Unraveling Insights in Earth and Biodiversity Sciences

Lecturer: Prof. Genoveva Vargas-Solar – CNRS, LIRIS

Schedule:

Monday, 14 September, 2026 – MO27 Building - First Floor, Meeting Room - DIEF
10:30 AM – 12:30 PM: Theory
2:00 PM – 4:00 PM: Hands-on Lab
 

Tuesday, 15 September, 2026  – MO27 Building - First Floor, Meeting Room - DIEF
10:30 AM – 12:30 PM: Theory
2:00 PM – 4:00 PM: Hands-on Lab
 

Wednesday, 16 September, 2026  – MO27 Building - First Floor, Meeting Room - DIEF
10:30 AM – 12:30 PM: Theory
2:00 PM – 4:00 PM: Hands-on Lab
 

Thursday, 17 September, 2026  – MO27 Building - First Floor, Meeting Room - DIEF
10:30 AM – 12:30 PM: Theory
2:00 PM – 4:00 PM: Hands-on Lab  

Program:

The course (http://vargas-solar.com/data-curation-tutorial/) introduces essential concepts, tools, and techniques for provenance-based data curation in data-driven sciences. It addresses the fundamental notions of provenance, data curation, data quality, explainability, and reproducibility, with a particular focus on Earth and biodiversity sciences. The course combines theoretical lectures and hands-on activities. It will present the main problems addressed by provenance and curation techniques, existing models and solutions, and current open challenges. Through representative use cases, students will explore how provenance can document data, workflows, computational experiments, decisions, assumptions, and transformations involved in scientific
processes. Beyond a standard technical perspective, the course also promotes critical thinking and introduces sociotechnical perspectives on data science. Particular attention will be given to the multidisciplinary nature of data science teams, the role of
communication between technical and domain experts, and the importance of shared vocabularies for collaborative scientific work. At the end of the course, students will be able to understand how provenance and data curation are interleaved with data science practices, how they contribute to reproducibility and explainability, and how they can be applied to complex scientific
problems in Earth and biodiversity domains. The following topics will be addressed:
- Fundamentals of provenance and data curation
- Data quality, explainability, and reproducibility in data-driven sciences
- Provenance models and representations
- Curation of data, workflows, processes, and experimental decisions
- Use cases in Earth and biodiversity sciences (other experimental science will be added)
- Critical and sociotechnical perspectives on data science
- Multidisciplinary collaboration and communication in data science teams
- Hands-on activities for modelling provenance and curating scientific processes
 

Express your interest: Interested in taking this course? Please fill in this short form to help us estimate participants and share course materials https://docs.google.com/forms/d/e/1FAIpQLSc5BbzXkbx4A4kIp2_SIbHEW2jXqPhHO1qPrlmnObQrcgQLNg/viewform?usp=preview

Exam:
Students will complete a final project, to be submitted after the end of the course.

CFD: 4

An introduction to signal processing methods for automotive MIMO radars

Lecturer: Prof. Pasquale Di Viesti – UniMORE

Schedule:
September 7 through 10 (all days) from 10 am to 1 pm
Meeting room @ MO26 - First 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

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

Electrical interfaces for quantum technologies

Lecturer: Prof. Fabio Sebastiano, Delft University of Technology (NL)

Schedule:
08-11 June 2026 (16 hours)

Program:

Quantum computers hold the promise of changing our everyday lives in this century in the same radical way that classical computers did in the last century, by efficiently solving problems that are intractable today, such as large number factorization and the simulation of quantum systems. Quantum computers operate by processing information stored in quantum bits (qubits), which typically require operation at cryogenic temperatures. Today, the qubits are mostly controlled by conventional electronics working at room temperature. This thermal gap can be readily bridged by a few wires since today’s quantum computers employ only a few qubits. However, practical quantum computers will require more than thousands of qubits, making this approach impractical. A solution is to build the qubit electrical interface using CMOS integrated circuits that operate at cryogenic temperatures (cryo-CMOS), thereby bringing them very close to the qubits. This course will introduce the basic concepts of quantum computation from a quantum information perspective, highlighting also the challenges in building a quantum computer architecture. We will then provide an overview of the quantum hardware used to physically implement the qubits and discuss how these qubit platforms impose stringent constraints on the classical electronics and their implementations. After providing an overview of the cryogenic behavior of semiconductor devices, we will delve into the various circuit components necessary for controlling and reading out qubits, including RF, analog, mixed-signal, and digital components. Before concluding, we will also introduce the need for cryogenic electronics for cryogenic sensors, which share similar challenges as quantum computers. Finally, an overview of the current trends and future challenges will be presented.

Exam:
written test

CFD: 4

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

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

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

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