CV

Work Experience

PostDoc Researcher, IRCCS Ospedale Galeazzi Sant'Ambrogio

Start: Dec 2022 - End: Dec 2023

Location: Milan, Italy

I am currently employed as a PostDoc Researcher at the IRCCS Ospedale Galeazzi Sant'Ambrogio, one of the most important research hospitals in Italy and Europe for radiology, orthopaedics, cardiology and metabolic disease research. My research is associated with the research project "Computational support for clinical and patient-centred decisions" and my main aims and research topics concern both Machine Learning (and, more broadly, Data Science) as well as human-AI interaction.
On the ML side, my research regards the development and evaluation of ML techniques and algorithms for clinical applications, with a focus on the management of uncertain data, uncertainty quantification, and statistical learning methods for clinical decision-making based on patient-reported data (PROMs) and laboratory medicine data.
On the human-AI interaction side, my research regards the design and evaluation of AI-based clinical support systems and impact-assessment protocols in clinical decision making, based on a human-centered approach.

Visiting Researcher, Fraunhofer Portugal Research Center for Assistive Information and Communication Solutions

Start: Jan 2021 - End: Apr 2021

Location: Lisbon, Portugal

I spent 3 months as a visiting researcher at the Fraunhofer Portugal Research Center for Assistive Information and Communication Solutions, under the supervision of prof. Hugo Gamboa.
During this period, my research projects focused on uncertainty quantification in machine learning (conformal prediction), with applications to time series classification, as well as eXplainable AI and Human-AI interaction in the medical setting.

Visiting Researcher, Heudiasyc, Université de Compiègne

Start: Sep 2021 - End: Dec 2021

Location: Compiègne, France

I spent 3 months as a visiting researcher at the Heudiasyc research lab, under the supervision of prof. Thierry Denoeux.
During this period, my research projects focused on uncertainty representation theory (mainly, the relationships between rough set theory and belief functions theory), with applications to knowledge representation and machine learning, as well as the development of evaluation metrics for soft clustering based on optimal transport theory.

Research Consultant, IRCCS Istituto Ortopedico Galeazzi

Start: Jul 2019 - End: Dec 2019

Location: Milan, Italy

I worked at the IRCCS Istituto Ortopedico Galeazzi (one of the major research hospitals in Italy) as a research consultant on machine learning and data reliability, mainly working on projects related to AI-supported diagnosis and explainable AI.

Clinical Data Scientist, Link Up and Deloitte Italy

Start: Nov 2018 - End: Jun 2019

Location: Milan, Italy

I worked as a machine learning and database engineer at Link Up (a start-up focusing on consulting services for hospitals), which was later acquired by Deloitte Italy. In particular, I was the head of a small team (2 data scientists and 1 biomedical engineer) devoted to database/data warehouse design and machine learning development consulting for different hospitals and clinics in Italy and Europe.

Teaching Experience

Lecturer on Complex and Uncertain Systems, MSc in Computer Science, University of Milano-Bicocca

Start: Feb 2022 - End: Sep 2023

Location: Milan, Italy

Lecturer for the Master-level course "Complex and Uncertain Systems". The main topics taught regard uncertainty representation in dynamical systems, soft clustering, calibration and uncertainty quantification, and feature selection in weakly supervised learning.

Lecturer on Advanced Data Management and Decision Support Systems, MSc in Artificial Intelligence, University of Milano-Bicocca

Start: Feb 2022 - End: Sep 2023

Location: Milan, Italy

Lecturer for the Master-level course "Advanced Data Management and Decision Support Systems". The main topics taught regard the theoretical and mathematical foundations of decision making, focusing on: normative decision theory, (non-cooperative) game theory, coalitional game theory, social choice theory. I also provided an introduction to the application of the above mentioned topics in AI and ML, focusing on: utility theory in the evaluation of predictive models (net benefit theory), generative adversarial networks, Shapley values for eXplainable AI, voting methods in ensemble learning.

Lecturer on Fuzzy Systems and Evolutionary Computing, BSc in Artificial Intelligence, University of Milano-Bicocca

Start: Feb 2022 - End: Sep 2023

Location: Milan, Italy

Lecturer for the the Bachelor-level course "Fuzzy Systems and Evolutionary Computing". The main topics taught regard the theory, design, implementation and evaluation of techniques based on fuzzy systems (fuzzy set theory and fuzzy logic, fuzzy rule-based and control systems, fuzzy clustering) and evolutionary computing (genetic algorithms, genetic programming, applications of evolutionary methods in ML), adopting an hands-on teaching approach.

Lecturer on Weakly Supervised Feature Selection, MSc in Computer Science, University of Milano-Bicocca

Start: Jun 2021 - End: Jun 2021

Start: Apr 2022- End: Apr 2022

Location: Milan, Italy

I taught two 2hrs-module lessons within the Master-level course "Complex and Uncertain Systems". The main topic was the application of rough set theory and belief functions to feature selection in weakly supervised learning problems.

Lecturer on Uncertainty in Dynamical Systems, MSc in Computer Science, University of Milano-Bicocca

Start: Jun 2021 - End: Jun 2021

Start: Jun 2022 - End: Jun 2022

Location: Milan, Italy

I taught two 2hrs-module lesson within the Master-level course "Complex and Uncertain Systems". The main topic was the application of rough set theory for uncertainty modeling and knowledge representation in discrete dynamical systems.

Lecturer on Explainability and Fairness in Artificial Intelligence, Master Degree in Nudge and Public Policies, University of Milano-Bicocca

Start: Mar 2021 - End: Apr 2021

Location: Milan, Italy

I taught a 4hrs module on Explainability and Fairness in Artificial Intelligence and Machine Learning: 2hrs theoretical lesson and 2hrs hands-on lesson.

Lecturer on "Languages and Computability", BSc in Computer Science, University of Milano-Bicocca

Start: Nov 2019 - End: Sep 2021

Location: Milan, Italy

Laboratory lecturer and tutor for the Bachelor-level course "Languages and Computability" for 2 consecutive years, teaching a 30hrs module per year. My responsibilities encompassed teaching and assisting students in the use of standard tools (lex, yacc) for parser generation, and more generally illustrating and teaching applications of formal language theory in Computer Science, such as compiler and interpreter generation.

Education

PhD in Computer Science, University of Milano-Bicocca

Final Vote: Excellent with honors (2 positive reviews with no corrections for the thesis)
Start: Nov 2019 - End: Feb 2023

Thesis Title: Robust Learning Methods for Imprecise Data and Cautious Inference

My main research topic was uncertainty in machine learning, with a focus on weakly supervised learning, unsupervised learning and uncertainty quantification (cautious prediction), both from an algorithmic/theoretical as well as experimental point of view. In particular I have investigated three main problems: learning and dimensionality reduction in the learning from fuzzy labels task; theory and evaluation of soft clustering algorithms; conformal prediction, three-way decision and ensemble learning methods in cautious inference and uncertainty quantification.
During my PhD I worked with different hospitals, in Italy (IRCCS Ospedale Galeazzi - Sant'Ambrogio, IRCCS Ospedale San Raffaele, ASST Gaetano Pini) and abroad, on projects related to medical ML. I have also worked in uncertainty representation more in general, as well as in Human-AI Interaction.
My supervisors were Davide Ciucci and Federico Cabitza.
The courses I followed were: Graph Theory and Algorithms, Deep Learning, Human-AI Interaction, Artificial Intelligence for Network Medicine, Population-based Optimization Methods, Causal Networks and Inference, Neuro-Symbolic Computation. I also attended the Ninth school of the Society for Imprecise Probability and the Mediterranean Machine Learning School.

Training Course in "Antropo-Psycho-Pedagogical Disciplines

Start: Jan 2019 - End: Apr 2019

24 ECTS

I graduated from an educational program (recognized by the Italian Ministry of Education) to train teacher and educators, focusing on the following subjects: intercultural education, educational planning and evaluation methodologies, special needs education.

Master of Science in Computer Science, University of Milano-Bicocca

Final Vote: 110/110 cum laude
Start: 2015 - End: 2017

120 ECTS

Thesis Title: Uncertainty Measures for Orthopairs and Their Application to Clustering

The subject of my thesis regarded the study of logico-algebraic uncertainty models (orthopairs, rough sets) and their relationships with other uncertainty representation approaches. In particular, I was interested in studying the generalization of information theoretic-measures to this setting, as well as in applications to semi-supervised and unsupervised machine learning.
My studies were mostly focused on theoretical computer science and artificial intelligence. The courses I followed were: knowledge and uncertainty representation, machine learning, probabilistic graphical models, computational complexity, non-classical logics, information theory, high-performance computing, complex systems theory, formal methods.

Bachelor of Science in Computer Science, University of Milano-Bicocca

Final Vote: 110/110 cum laude
Start: 2012 - End: 2015

180 ECTS

Thesis Title: Implementation of a pipeline to infer somatic selective advantage relations in Renal Carcinoma

The subject of my thesis regarded the use of causal graphical models for inferring and representing the evolution of cancer. In particular, I designed a pipeline (in R) for cancer data analysis based on these models.
My studies were mostly focused on theoretical computer science and data sciences. The courses I followed were: algorithms and data structures, bioinformatics, probability and statistics, operations research and optimization, models of concurrent and dynamical systems, databases, mathematics (analysis, linear algebra, logics, discrete math), computability and language theory, programming (Java, C/C++, Prolog, Lisp), software engineering.

Technical Skills and Expertise

Technical Expertise

• Uncertainty representation (probability theory, rough sets, fuzzy sets, belief function theory)
• Machine learning (supervised, unsupervised, weakly-supervised, conformal prediction, ensemble learning, kernel methods)
• Algorithm design and computational complexity
• Theoretical computer science (learning theory, logics, discrete dynamical systems)
• Applied maths (probability theory, statistics, optimization, analysis)
• Software engineering and architecture

Knowledge of Programming Languages and Frameworks

• Python
• Python ML ecosystem (scikit-learn, numpy/scipy, matplotlib/seaborn, pandas, tensorflow/keras/pytorch)
• SQL and relational databases
• Version Control Systems (Git)
• Java
• C/C++

Academic Activity

I have been acting as member of the editorial board of the International Journal of Medical Informatics (Elsevier) since 2021.

I have been Guest Editor for the Array journal (Elsevier) for the Special Issue Weak and cautious learning: conceptual foundations and practical algorithms

I will be Program Chair (and editor of the proceedings) at the International Joint Conference on Rough Sets 2023 (IJCRS 2023), who will be located at the AGH University of Science and Technology in Krakow, Poland.

I will be Program Chair (and editor of the proceedings) at the International IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) (CD-MAKE 2023), who will be located at the University of Sannio in Benevento, Italy (co-located with ARES 2023).

I am organizing, jointly with Valerio Basile and Federico Cabitza, the Special Session on Multi-Perspectivist Data and Learning at CD-MAKE 2023

I organized, jointly with Nahuel Costa and Luciano Sánchez, the Special Session on Machine Learning for Partially Labeled Data at IPMU 2022

I organized, jointly with Valerio Basile, Federico Cabitza and Teresa Scantamburlo, the Special Session on Data Perspectivism in Ground Truthing and Artificial Intelligence at IPMU 2022

I have been Program Committee member for the following conferences:

• ECAI 2023
• CBMS 2023
• CIBB 2023
• XAI 2023
• KoDis 2023 (International Workshop on Knowledge Diversity)
• UAI 2022, UAI 2023
• ECML 2022
• IJCRS 2022
• IPMU 2022
• CD-MAKE 2021, CD-MAKE 2022
• HEALTHINF 2020, HEALTHINF 2021, HEALTHINF 2022, HEALTHINF 2023

I have been a reviewer for the following journals:

• Artificial Intelligence Review
• Applied Soft Computing
• Cognitive Computation
• Expert Systems with Applications
• IEEE Transactions on Fuzzy Systems
• Information Sciences
• International Journal of Approximate Reasoning
• International Journal of Fuzzy Systems
• International Journal of Intelligent Systems
• Knowledge and Information Systems
• BMC Bioinformatics
• BMC Decision Making and Medical Informatics
• BMC Medical Research Methodology
• International Journal of Medical Informatics
• NPJ Digital Medicine
• Scientific Reports

And the following conferences:

• MIE 2022
• IPMU 2021
• ICAART 2020, ICAART 2021, ICAART 2022
• CD-MAKE 2020
• IJCRS 2019, IJCRS 2020, IJCRS 2021
• HEALTHINF 2019

Supervised Students

I really love knowledge transmission and education. As such, I have been thesis supervisor for several student at the University of Milano-Bicocca, mainly on topics regarding Machine Learning, Data Visualization, Medical Informatics and Human-AI Interaction. More in particular, I supervised 7 students at the Master level:

• Enrico Conte (Impact of Biological and Analytical Variation in Biomedical Machine Learning) - MSc in Data Science
• Mirko Lantieri (Human-AI Interaction in Deep Learning-assisted Radiology) - MSc in Computer Science
• Martina Mattioli (Agreement and Reliability in Face Emotion Recognition) - MA in Communication Theory and Technology
• Riccardo Oltolini (Review on Abstention in Machine Learning) - MSc in Computer Science
• Luca Ravasi (Comparison of Ensemble Learning Methods) - MSc in Computer Science
• Luca Ronzio (Collective Intelligence in Medicine) - Medical degree
• Christian Uccheddu (Machine Learning for the Analysis of Biological Variation) - MSc in Data Science

And several students at the BSc level in Computer Science:

• Nicola Armas (Development of Innovative Data Visualization methods)
• Federico Benaglia (Development of a Web Tool for ML External Validation)
• Giovanni Brusadelli (Density-based Three-way and Rough Clustering)
• Paolo Calvi (Evidential Clustering: Implementation and Validation)
• Luca Carlassara (Implementation of a Web Tool for Decision Support Systems' Quality Assessment)
• Matteo Cusini (Ensemble Learning based on Collective Intelligence approaches)
• Andrea D'Amicis (Fuzzy Clustering: Implementation and Validation)
• Jury D'Onofrio (Design of Web Tools and Visualizations to Assess Reliability of ML Kodels)
• Alessio De Gennaro (Ensemble Learning based on Similarity Measures)
• Nubia Colombo Dugoni (Human-AI Interaction for Group Decision Making)
• Andrea Ippolito (Survey of Collective Intelligence methods)
• Simone Mallei (Partition-based Three-way and Rough Clustering)
• Niccolò Mandelli (Impact of AI-based support and XAI on Clinical Decision Making)
• Elettra Messuri (Review on Three-way Decisions in Machine Learning)
• Lorenzo Neglia (Development of a Eye-tracking and Heatmap Generator Plugin for LimeSurvey)
• Davide Negri (Web Tools for Human-AI Interaction research in Radiology)
• Emanuele Papa (Comparison of Machine Learning algorithms for Weakly Supervised Learning)
• Giovanni Occhiuto (Human-AI Interaction in Medical Decision Making)
• Matteo Selvaggi (Possibilistic Clustering: Implementation and Validation)
• Giacomo Stoffa (Development of web tools for ML-assisted COVID-19 diagnosis)
• Lorenzo Tomasoni (Design of visualizations for Collective Intelligence)
• Simone Vendramini (Rough Fuzzy Clustering: Implementation and Validation)
• Carlotta Vierchowod (Development of web tools for Human-AI Interaction research)