Curriculum vitæ of Dario Malchiodi
Personal information
Dario Malchiodi
Department of Computer Science,
University of Milan
Room 5015 ·
Via Celoria 18, 20133 Milano ITALY
first . last at unimi . it
+39 02 503 16338
malchiodi.di.unimi.it ·
PGP key
Current position
Since 2011 I have been an associate professor at the Computer Science Department of the University of Milan.
Previous positions
- 2002–2011
- Assistant professor at the Computer Science Department of the University of Milan.
- 2001–2002
- Research assistant at the Computer Science Department of the University of Milan, within the Neural Networks Laboratory.
- 2000–2001
- Software architect in the private sector, designing statistical and neural architectures for financial forecasts.
- 1997–2000
- Statistical analyst in the private sector, within an R&D project on flexible regression models for financial data.
- 1996–1997
- Software developer in the private sector.
Education
- 2000
- PhD in Computational Mathematics and Operations Research, University of Milan.
- 1996
- MSc (cum laude) in Computer Science, University of Milan.
- 1994
- Specialization in Unix lab Administration, Regione Lombardia.
- 1994
- Specialization in Multimedia programming with Motif and C, Regione Lombardia.
Awards
- 2026
- Best Paper Runner-Up Award at the GLOW 2026 workshop (Graph-enhanced LLMs for trustworthy Web data management, The Web Conference 2026) (Emanuele Cavalleri, Miad Alavinezhad, Marco Mesiti and Dario Malchiodi, Better Negatives, Better Predictions: Negative Sample Selection Strategies for Enhancing Biomedical KG Edge Classification)
- 2018
- CSEDU 2018 best poster award (Carlo Bellettini, Fabrizio Carimati, Violetta Lonati, Riccardo Macoratti, Dario Malchiodi, Mattia Monga and Anna Morpurgo, A Platform for the Italian Bebras)
- 2016
- Informatics Europe Best Practices in Education Award (ALaDDIn laboratory)
Research activities
Reliable and efficient machine learning
Reliability and AI systems
This line of research focuses on the use of artificial intelligence methods to assess the reliability and security of systems. [Frasson and Malchiodi, 2024] extends support vector-based anomaly detection techniques to federated learning, [Biagiotti et al., 2025] investigates interpretable models for quench detection and localization in superconducting magnets, and [Paravisi et al., 2024] uses machine learning techniques to analyze the security of cryptographic algorithms. Particular attention is devoted to the reliability of AI-based systems: [Zanaboni et al., 2026] proposes a hypothesis testing procedure to detect covariate drift in queries submitted to a machine learning model, and [Malchiodi et al., 2027] detects hallucinations in large language models by applying anomaly detection techniques to the latent representations produced by the models themselves.
Compression of machine learning models
Models learned from data, particularly deep neural networks, often have memory and transmission bandwidth requirements that exceed the resources available on embedded or resource-constrained devices. This line of research, initiated within the PRIN project Multicriteria Data Structures and Algorithms: from compressed to learned indexes, and beyond, investigates techniques for reducing the storage space required by a trained model while limiting the loss of accuracy. [Marinò et al., 2021b] introduced compact representations of deep neural networks based on Huffman coding, whose implementation is described in [Marinò et al., 2021a]. These representations are used in [Marinò et al., 2023a] to compress deep neural networks, while [Marinò et al., 2023b] presents an experimental comparison of compression techniques, providing recommendations for an informed choice among them. [Malchiodi et al., 2026] instead proposes regularizers that promote model compressibility directly during training. Compression techniques have been applied to estimating the Ki67 index in breast cancer on resource-constrained devices in [Gliozzo et al., 2024].
Learned data structures
Learned data structures extend classical ones by incorporating machine learning models trained on the data to be stored, with the aim of reducing storage space or query time. Within the PRIN project Multicriteria Data Structures and Algorithms: from compressed to learned indexes, and beyond, interaction between a classifier and the auxiliary components in learned Bloom filters has been investigated. [Fumagalli et al., 2022; Malchiodi et al., 2023] analyse how the choice of classifier affects storage space, false positive rate and query time, while [Malchiodi et al., 2024] relates these performance metrics to data complexity, providing recommendations for selecting and using these structures.
Fuzzy sets and learning from uncertain data
Data-driven induction of fuzzy sets
A learning algorithm for fuzzy sets processing data labeled with their membership degrees has been proposed in [Malchiodi and Pedrycz, 2013; Malchiodi, 2019]. Such algorithm has been applied to axiom mining within semantic Web [Malchiodi and Tettamanzi, 2018] and to negative examples selection in bioinformatics [Frasca and Malchiodi, 2017; Frasca and Malchiodi, 2016]. This approach has been extended in [Cermenati et al., 2020] to the simultaneous induction of several fuzzy sets, and in [Malchiodi and Zanaboni, 2019] to shadowed sets. More recently, [Dashti Genave et al., 2026] studied techniques for compressing the membership functions learned in this way.
Data quality-based learning · Analysis of relations between granular computing and machine learning
Machine learning for the life sciences
Knowledge graphs and LLM-based information extraction in biomedicine
Biomedical knowledge is scattered across numerous databases and a rapidly growing body of scientific literature. Knowledge graphs provide an effective means of integrating information from these heterogeneous sources, enabling it to be queried and analysed using machine learning techniques. [Cavalleri et al., 2024a; Cavalleri et al., 2024b] propose a system based on LLMs and graph machine learning to improve the quality of relations extracted from scientific articles on RNA-related topics. [Mesiti et al., 2026] describes a web application that supports experts in reviewing and validating biomedical knowledge graphs, while [Cavalleri et al., 2026] investigates the selection of negative examples for edge classification in these graphs.
Language models for protein and enzyme design
Protein sequences can be viewed as sentences written in a language whose alphabet consists of amino acids: large language models trained on corpora of sequences can be used to generate new protein sequences with desired functional properties. [Valentini et al., 2023] discusses the potential of LLMs for protein design and modelling. [Nicolini et al., 2024] shows that fine-tuning conditional Transformers on a specific protein family improves amino acid sequence prediction and enables the generation of new, biologically plausible sequences. [Nicolini et al., 2025] extends this approach to several enzyme categories, highlighting the benefits of fine-tuning for specific functional categories and evaluating the structural and functional properties of the generated sequences in silico.
Negative sample selection in biological networks and knowledge graphs
In many supervised learning problems in bioinformatics, positive examples and unlabelled data are available: the latter may include both true negatives and positive cases that have not yet been identified. This line of research investigates how to select reliable negative examples from unlabelled data. In [Frasca and Malchiodi, 2017; Frasca and Malchiodi, 2016], the problem was addressed through a ranking based on fuzzy set membership functions, while [Frasca et al., 2017; Boldi et al., 2018] proposed a data representation designed to facilitate negative example selection for protein function prediction. In [Frasca et al., 2019], negative example selection was applied to gene prioritisation. More recently, [Cavalleri et al., 2026] compared strategies for selecting negative examples for edge classification in biomedical knowledge graphs. The paper received the Best Paper Runner-Up Award at the GLOW 2026 workshop.
Applications of machine learning
Machine learning in human and veterinary medicine, forensic sciences and cultural heritage
This line of research investigates the application of machine learning and statistical analysis techniques to problems in veterinary medicine, forensic science and archaeology. In particular, [Galizzi et al., 2021; Bagardi et al., 2021] describe the use of statistical techniques to analyse the relationship between cardiovascular factors and mortality in dogs undergoing a specific treatment. [Casali et al., 2021] presents a pilot study on the use of classification algorithms to predict the type of vehicle involved in a pedestrian collision, while [Blandino et al., 2025] assesses the feasibility of estimating the height of a fatal fall using artificial intelligence techniques. In archaeology, [Zanaboni et al., 2022; Ruschioni et al., 2023] use classification algorithms to predict the provenance of pottery fragments from chemical element concentrations, while [Malchiodi et al., 2025] compares one-class and binary classifiers for the same task.
ML-based COVID-19 risk prediction · Mining of knowledge bases in semantic Web
Earlier research lines
Computing education and popularization
Teaching computer programming · Popularization of informatics culture · Training of computing teachers · Computational thinking challenges · Informal learning of computing
Statistical learning and algorithmic inference
Design of learning algorithms · Bootstrap techniques for regression algorithms · Development of inference models for machine learning problems · Design of hardware-implementable statistics
Hybrid and neuro-symbolic systems
Automatic simplification of symbolic descriptions · Design of hybrid learning systems · Automatic classification of emotions · Intelligent systems for pervasive and ubiquitous computing
Scientific computing and simulation
Applications of systems for scientific computation · Study of population dynamics
Membership to research projects
- 2026–now
- DRIFTWISE: Deep and Robust Inference with Fuzzy representaTions, WIth anomaly detection and model comprESSion
- 2024–now
- DREAM: Mind your DRug: biobehavioral modEl towArd precision Medicine in depression
- 2024–2026
- PRECOCO: Metodi di AI per diagnostica PRECOce del carcinoma squamoso del Cavo Orale basato su imaging label-free
- 2019–2021
- Multicriteria Data Structures and Algorithms: from compressed to learned indexes, and beyond
- 2016–2018
- Fostering a correct view of informatics
- 2015–2017
- SMILE: Slow down, Move your body, Improve your diet, Learn for life, and Enjoy school time
- 2015
- Teaching advanced informatics concepts to high school students
- 2012–2015
- SandS: Social AND Smart
- 2012–2014
- VIOPE: Learning computer programming in virtual environment
- 2008–2013
- PASCAL2: Pattern Analysis, Statistical Modelling and Computational Learning
- 2009
- Calcoli statistici per la risoluzione di problemi informatici avanzati
- 2005–2008
- PASCAL: Pattern Analysis, Statistical Modelling and Computational Learning
- 2008
- Processi con memoria della famiglia Pareto-like
- 2007
- Processi non markoviani per reti di telecomunicazione opportunistiche
- 2006
- Metodi di inferenza su «membership function»
- 2002–2004
- Processi stocastici
- 2001–2003
- ORESTEIA: mOdular hybRid artEfactS wiTh adaptivE functIonAlity
- 1998–2000
- PHYSTA: Principled Hybrid Systems: Theory and Applications
- 2000
- Metodi statistici e neurali di supporto alle decisioni in ambito finanziario
- 2000
- Metodi statistico-neurali per lo studio di popolazioni
- 1999
- Processi stocastici con natura spaziale
Research funds managed
- 2018
- Piano sostegno alla ricerca, University of Milan
- 2017
- Computer Science Department, University of Milan
- 2017
- Piano sostegno alla ricerca, University of Milan
- 2016
- SMILE project, European Commission
- 2016
- Piano sostegno alla ricerca, University of Milan
- 2015
- Piano sostegno alla ricerca, University of Milan
International collaborations
- 2016–now
- Visiting scientist at INRIA/Université de la Côte d'Azur within the WIMMICS project
- 2023–2024
- Proposer of the research collaboration agreements between the I3S laboratory of Université Côte d'Azur and the Computer Science Department, University of Milan (2023 and 2024)
Membership to academic associations and research groups
- 2022–now
- Web Algorithmics Laboratory, Computer Science Department, University of Milan
- 2021–now
- CINI Laboratory on Data Science
- 2020–now
- COVID-19 International Research Team
- 2019–now
- Data science research centre, University of Milan
- 2002–now
- GRIN: Italian Association of Computer Science University Professors
- 2008–2019
- ALaDDIn laboratory
- 2002–2013
- Italian Society for Neural Networks
- 1996–2011
- Neural Networks Laboratory, Computer Science Department, University of Milan
Publications
- Overview
- Books: 5 · Journals: 37 · International conferences: 82 · Chapters: 8 · Theses: 2 · Software: 5 · Other publications: 4
- Bibliometric indices
- OpenAlex: H-index 14, 970 citations · Google Scholar: H-index 21, 1549 citations · Scopus: H-index 14, 785 citations · Web of Science: H-index 10, 423 citations
Books (5)
Algorithmic Inference in Machine Learning, 2nd Edition
Advanced Knowledge International, International Series on Advanced Intelligence, Vol. 5, ISBN 0-9751004-2-4
Papers in international journals (37)
The role of classifiers and data complexity in learned Bloom filters: insights and recommendations
Journal of Big Data 11(45)
The promises of large language models for protein design and modeling
Frontiers in Bioinformatics 3, pp. 1304099.1—1304099.11
Journal of Forensics and Legal Medicine 84, pp. 102256
Polish Journal of Veterinary Sciences 24(1), pp. 109–118
Reports in Medical Imaging 14, pp. 27–39
BMC Veterinary Research 17(1), pp. 1–14
IEEE Access 8, pp. 196299–196325
Constructionist Attempts at Supporting the Learning of Computer Programming: A Survey
Olympiads in Informatics 13, pp. 99–121
Fostering Computational Thinking in Primary School through a LEGO®-based Music Notation
Procedia computer science 112, pp. 1334–1344 · Special issue: KES 2017 - Proceedings of the 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems
Exploiting Negative Sample Selection for Prioritizing Candidate Disease Genes
Genomics and Computational Biology 3(3), pp. e47
Relevance regression learning with support vector machines
Nonlinear Analysis 73, pp. 2855–2867
Playing monotone games to understand learning behaviors
Theoretical Computer Science 411(25), pp. 2384–2405
Nonlinear Analysis: Theory, Methods & Applications 71(12), pp. e2883–e2901
An experimental analysis of the impact of accuracy degradation in SVM classification
International Journal of Computational Intelligence Studies 1(2), pp. 163–190
Solving complex regression problems via Algorithmic Inference: a new family of bootstrap algorithms
Far East Journal of Theoretical Statistics 22(2), pp. 141–180
Appreciation of medical treatments by learning underlying functions with good confidence
Current Pharmaceutical Design 13(15), pp. 1545–1570
Controlling the losing probability in a monotone game
Information Sciences 176(10), pp. 1395–1416
Functional bootstrap: a hardware constrained implementation of on-line bootstrap
InterStat October
Papers in international conference proceedings (82)
Detecting LLM Hallucinations via Anomaly Detection on Latent Representations
In Modeling Decisions for Artificial Intelligence, Springer Nature Switzerland, pp. 122–123
An Intelligent Web Application for Biomedical Knowledge Graph Curation
In Proceedings of Ital-IA 2026 · In press
ADAZOR: Hypothesis Testing for Concept Drift Detection in Machine Learning
In L. Iliadis, I. Maglogiannis, M. Antonakakis, C. Jayne (eds.), Engineering Applications of Neural Networks, vol. 3025, Springer Nature Switzerland (Communications in Computer and Information Science), pp. 256–269
Quantization-Aware Regularizers for Deep Neural Networks Compression
In IJCNN 2026 Proceedings. · In press
Compression Techniques for Membership Functions to Fuzzy Sets Learned from Data
In 2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Pisa, Italy, 2026, IEEE, pp. 1–6
In WWW Companion '26: Companion Proceedings of the ACM Web Conference, Association for Computing Machinery, pp. 597–606 · In press
Quench detection and localization via interpretable machine learning
In L. Iliadis, I. Maglogiannis, E. Kyriacou, C. Jayne (eds.), Engineering Applications of Neural Networks. EANN 2025., vol. 2582, Springer (Communications in Computer and Information Science), pp. 151–164
Initial achievements in relation extraction from RNA-focused scientific papers
In M. Atzori, P. Ciacca, M. Ceci, F. Mandreoli, D. Malerba, M. Sanguinetti, A. Pellicani, F. Motta (eds.), Proceedings of the 32nd Symposium on Advanced Database Systems, pp. 61–69
Security Analysis of Cryptographic Algorithms: Hints from Machine Learning
In L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (eds.), Engineering Applications of Neural Networks. EANN 2024., vol. 2141, Springer (Communications in Computer and Information Science), pp. 569–580
Support Vector Based Anomaly Detection in Federated Learning
In L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (eds.), Engineering Applications of Neural Networks. EANN 2024., vol. 2141, Springer (Communications in Computer and Information Science), pp. 274–287
SPIREX: Improving LLM-based relation extraction from RNA-focused scientific literature using graph machine learning
In Proceedings of Workshops at the 50th International Conference on Very Large Data Bases, vldb.org, pp. 1–11
In BIOSTEC 2024 - 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Proceedings, vol. 1, SCITEPRESS, pp. 561–568
Resource-Limited Automated Ki67 Index Estimation in Breast Cancer
In Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications (ICBRA '23), ACM, pp. 165–172
A Critical Analysis of Classifier Selection in Learned Bloom Filters: the Essentials
In L. Iliadis, I. Maglogiannis, S. A. Castro, C. Jayne, E. Pimenidis (eds.), Engineering Application of Neural Networks — 24th International Conference — EAAAI/EANN 2023 — León, Spain, June 14—17, 2023 —Proceedings, Springer Nature (Communications in Computer and Information Science 1826), pp. 47–61
Classification of Pottery Fragments Described by Concentration of Chemical Elements
In P. L. Mazzeo, E. Frontoni, S. Sclaroff, C. Distante (eds.), Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022., vol. 13373, Springer (Lecture Notes in Computer Science), pp. 141–151
In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods — ICPRAM, SciTePress, pp. 675–682
Reproducing the sparse Huffman Address Map compression for deep neural networks
In B. Kerautret, M. Colom, A. Krähenbühl, Adrien, D. Lopresti, P. Monasse, H. Talbot (eds.), Reproducible Research in Pattern Recognition, Springer International Publishing (Lecture Notes in Computer Science 12636), pp. 161–166
Compression strategies and space-conscious representations for deep neural networks
In 2020 25th International Conference on Pattern Recognition (ICPR), IEEE, pp. 9835–9842
Classifying Candidate Axioms via Dimensionality Reduction Techniques
In V. Torra, Y. Narukawa, J. Nin, N. Agell (eds.), Modeling Decisions for Artificial Intelligence. 17th International Conference, MDAI 2020 Sant Cugat, Spain, September 2–4, 2020 Proceedings, ch. 15, Springer (Lecture Notes in Computer Sciencce 12256), pp. 179–191
Simultaneous Learning of Fuzzy Sets
In A. Esposito, M. Faundez-Zanuy, M. Morabito, E. Pasero (eds.), Neural Approaches to Dynamics of Signal Exchanges, vol. 151, Springer (Smart Innovation, Systems and Technologies), pp. 167–175
Data-Driven Induction of Shadowed Sets Based on Grade of Fuzziness
In R. Fullér, S. Giove, F. Masulli (eds.), Fuzzy Logic and Applications — 12th International Workshop, WILF 2018 Genoa, Italy, September 6–7, 2018 — Revised Selected Papers, Springer Nature Switzerland AG (Lecture Notes in Artificial Intelligence 11291), pp. 17–28
In R. Fullér, S. Giove, F. Masulli (eds.), Fuzzy Logic and Applications — 12th International Workshop, WILF 2018 Genoa, Italy, September 6–7, 2018 — Revised Selected Papers, Springer Nature Switzerland AG (Lecture Notes in Artificial Intelligence 11291), pp. 240–243
Disease-Genes Must Guide Data Source Integration in the Gene Prioritization Process
In M. Bartoletti, A. Barla, A. Bracciali, G. W. Klau, L. Peterson, A. Policriti, R. Tagliaferri (eds.), Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2017, Springer (Lecture Notes in Computer Science 10834 / Lecture Notes in Bioinformatics 10834), pp. 60—69
In Informatics in Schools. Fundamentals of Computer Science and Software Engineering., Springer (Lecture Notes in Computer Science 11169), pp. 194–205
Predicting the Possibilistic Score of OWL Axioms through Support Vector Regression
In D. Ciucci, G. Pasi, B. Vantaggi (eds.), Scalable Uncertainty Management. SUM 2018, Springer (Lecture Notes in Artificial Intelligence 11142)
Learning to Program in a Constructionist Way
In V. Dagienė, E. Jasutė (eds.), Constructionism 2018: Computational Thinking and Educational Innovation: conference proceedings, Vilnius University, pp. 906–929
Informatica e pensiero computazionale: una proposta costruttivista per gli insegnanti
In G. Adorni, M. Cicognani, F. Koceva, G. Mastronardi (eds.), Didamatica 2018: Didattica Informatica, AICA, pp. 201–210
A Platform for the Italian Bebras
In Proceedings of 10th International Conference on Computer Supported Education, SCITEPRESS, pp. 350–357
Predicting the Possibilistic Score of OWL Axioms through Modified Support Vector Clustering
In H. Haddad, R. L. Wainwright, R. Chbeir (eds.), SAC'18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing, ACM, pp. 1984–1991
Promoting Computational Thinking Skills: Would You Use this Bebras Task?
In V. Dagienė, H. Hellas (eds.), Informatics in Schools: Focus on Learning Programming, Springer (Lecture Notes in Computer Science), pp. 102–113
Learning Greedy Strategies at Secondary Schools: An Active Approach
In A. Sforza, C. Sterle (eds.), Optimization and Decision Science: Methodologies and Applications, ch. 23, Springer (Proceedings in Mathematics & Statistics), pp. 223–231
Bebras as a teaching resource
In ITiCSE '17 Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education, ACM, pp. 366–366
Nothing to fear but fear itself: introducing recursion in lower secondary schools
In International Conference on Learning and Teaching in Computing and Engineering (LATICE), 2017, IEEE, pp. 91–98
Analysis of Informative Features for Negative Selection in Protein Function Prediction
In I. Rojas, F. Ortuño (eds.), Bioinformatics and Biomedical Engineering 5th International Work-Conference, IWBBIO 2017, Granada, Spain, April 26–28, 2017, Proceedings, Part II, vol. 10209
In P. Escudeiro, G. Costagliola, S. Zvacek, J. Uhomoibhi, B. M. McLaren (eds.), Proceedings of the 9th International Conference on Computer Supported Education, SCITEPRESS, pp. 117–124
A playful tool to introduce lower secondary school pupils to recursive thinking
In Proceedings of 9th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2016, pp. 51–52
Selection of Negative Examples for Node Label Prediction through Fuzzy Clustering Techniques
In S. Bassis, A. Esposito, F. C. Morabito, E. Pasero (eds.), Advances in Neural Networks: Computational Intelligence for ICT, Springer International Publishing, pp. 67–76
How Challenging are Bebras Tasks? An IRT analysis based on the performance of Italian students
In ITiCSE '15 Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education, ACM, pp. 27–32
Is coding the way to go?
In A. Brodnik, J. Vahrenhold (eds.), Informatics in Schools. Curricula, Competences, and Competitions, Springer International Publishing, pp. 165–174
Experience of an International Collaborative Project with First Year Programming Students
In Proceedings of the IEEE 39th Annual Computer Software and Applications Conference (COMPSAC'15), pp. 829–834
Extracurricular Activities for Improving the Perception of Informatics in Secondary Schools
In Y. Gülbahar, E. Karataş (eds.), Informatics in Schools. Teaching and Learning Perspectives – 7th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2014, Istanbul, Turkey, September 22-25, 2014. Proceedings, vol. 8730, Springer International Publishing (Lecture Notes in Computer Science), pp. 161–172
Teaching Informatics for Fun and Profit
In A. Raschi, A. Di Fabio, L. Sebastiani (eds.), Proceedings of the International Workshop on Science Education and Guidance in Schools: The Way Forward, Edizioni ETS, pp. 125–128
Avoiding the Cluster Hypothesis in SV Classification of Partially Labeled Data
In S. Bassis, A. Esposito, F. C. Morabito (eds.), Recent Advances of Neural Networks Models and Applications. Proceedings of the 23nd Workshop of the Italian Neural Networks Society (SIREN), May 23-25, Vietri sul Mare, Salerno, Italy, vol. 26, Springer (Smart Innovation, Systems and Technologies), pp. 33–40
Learning Membership Functions for Fuzzy Sets through Modified Support Vector Clustering
In F. Masulli, G. Pasi, R. Yager (eds.), Fuzzy Logic and Applications. 10th International Workshop, WILF 2013, Genoa, Italy, November 19–22, 2013. Proceedings., vol. 8256, Springer International Publishing, Switzerland (Lecture Notes on Artificial Intelligence), pp. 52–59
What you see is what you have in mind: constructing mental models for formatted text processing
In I. Diethelm, J. Arndt, M. Dünnebier, J. (eds.), Informatics in Schools: Local Proceedings of the 6th International Conference ISSEP 2013 - Selected Papers, vol. 6, Universitätsverlag Potsdam (Commentarii informaticae didacticae), pp. 139–147
MUT: un framework di test automatico per Wolfram Mathematica
In Mathematica Italia User Group Meeting 2013 - Atti del Convegno, Adalta
In B. Apolloni, S. Bassis, A. Esposito, F. C. Morabito (eds.), Neural Nets and Surroundings. 22nd Italian Workshop on Neural Nets, WIRN 2012, May 17-19 2012, Vietri sul Mare, Salerno, Italy, Springer (Smart Innovation, Systems and Technologies 19), pp. 21–27
Exploring the processing of formatted texts by a kynesthetic approach
In WiPSCE'12 Proceedings of the 7th Workshop in Primary and Secondary Computing Education, ACM, pp. 143–144
Scrivi anche tu un libro con Mathematica!
In Mathematica Italia User Group Meeting 2011 - Atti del Convegno, Adalta
Uso di Mathematica per la classificazione di dati di qualità variabile
In Mathematica Italia User Group Meeting - Atti del Convegno 2010, Adalta
Mathematica per l'introduzione dei rudimenti della programmazione nelle scuole superiori
svMathematica: implementazione in Mathematica di algoritmi di machine learning basati su vettori di supporto
Discovering regression data quality through clustering methods
In B. Apolloni, M. Marinaro, S. Bassis (eds.), New Directions in Neural Networks, 18th Italian Workshop on Neural Networks: WIRN 2008, 22-24 May 2008, Vietri sul Mare, IOS Press (FAIA-KBIES vol. 193), pp. 76–85
The head fake, ovvero insegnando è concesso imbrogliare
A Modified SVM Classification Algorithm for Data of Variable Quality
In B. Apolloni, R. Howlett, L. Jain (eds.), Knowledge-Based Intelligent Information and Engineering Systems 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007. Proceedings, Part III, Springer-Verlag (Lecture Notes in Artificial Intelligence 4694), pp. 131–139
In B. Apolloni, R. Howlett, L. Jain (eds.), Knowledge-Based Intelligent Information and Engineering Systems 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, September 12-14, 2007. Proceedings, Part III, Springer-Verlag (Lecture Notes in Artificial Intelligence 4694), pp. 184–193
Embedding sample points relevance in SVM linear classification
In V. Torra, Y. Narukawa, A. Valls, J. Domingo-Ferrer (eds.), MDAI 2006 - Proceedings of 3rd International Conference on Modeling Decisions for Artificial Intelligence, Universitat Rovira I Virgili
Interpolating Support Information Granules
In S. Kollias, A. Stafylopatis, W. Duch, E. Oja (eds.), Artificial Neural Networks - ICANN 2006 - 16th International Conference, Athens, Greece, September 10-14, 2006, Proceedings, Part II, Springer (Lecture Notes in Computer Science 4132), pp. 270–281
Implementing an XML-RPC client in Mathematica
In B. Autin, Y. Papegay (eds.), eProceedings of the 8th International Mathematica Symposium, INRIA
BICA: a Boolean Independent Component Analysis Algorithm
In N. Nedjah, L. Mourelle, M. B. R. Vellasco, A. Abraham, M. Köppen (eds.), Proceedings of HIS 2005: Fifth International Conference on Hybrid Intelligent Systems, IEEE Computer Society, pp. 131–136
Tight Bounds for SVM Classification Error
In M. Zhao, Z. Shi (eds.), Proceedings - 2005 International Conference on Neural Network & Brain (ICNN&B'05), IEEE Press, pp. 5–8
In B. Apolloni, M. Marinaro, G. Nicosia, R. Tagliaferri (eds.), Neural Nets. 16th Italian Workshop on Neural Nets, WIRN 2005 and International Workshop on Natural and Artificial Immune Systems, NAIS 2005. Vietri sul Mare, Italy, June 2005, Springer (Lecture Notes in Computer Science 3931)
An Evolution Hypothesis of Bacterial Populations
In B. Apolloni, M. Marinaro, G. Nicosia, R. Tagliaferri (eds.), Neural Nets. 16th Italian Workshop on Neural Nets, WIRN 2005 and International Workshop on Natural and Artificial Immune Systems, NAIS 2005. Vietri sul Mare, Italy, June 2005, Springer (Lecture Notes in Computer Science 3931), pp. 214–230
Computing confidence intervals for the risk ofa SVM classifier through algorithmic inference
In B. Apolloni, M. Marinaro, R. Tagliaferri (eds.), Biological and Artificial Intelligence Environments, Springer, pp. 225–234
Learning continuous functions through a new linear regression method
In B. Apolloni, M. Marinaro, R. Tagliaferri (eds.), Biological and Artificial Intelligence Environments, Springer, pp. 235–243
Appreciation of medical treatments through confidence intervals
In E. Biganzoli, P. Boracchi, P. Duca, E. Ifeachor (eds.), Proceedings of the 1t European Workshop on the Assessment of Diagnostic Performance, RCE Edizioni, pp. 165–174
In J. Boulicaut, F. Esposito, F. Giannotti, D. Pedreschi (eds.), Knowledge Discovery in Databases - PKDD 2004. 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004. Proceedings, Springer (Lecture Notes in Artificial Intelligence 3202), pp. 528–530 · demonstrating paper
An Attention Monitoring System for High Demanding Operational Tasks
In Proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, IEEE Press, pp. 23–29 · invited paper
Learning rule representations from boolean data
In O. Kaynak, E. Alpaydin, E. Oja, L. Xu (eds.), Artificial Neural Networks and Neural Information Processing - ICANN/ICONIP 2003, Joint International Conference ICANN/ICONIP 2003, Istanbul, Turkey, June 26-29, 2003, Proceedings, Springer (Lecture Notes in Computer Science 2714), pp. 875–882
A man-machine human interface for a special device of the pervasive computing world
In A. Kameas, N. Streitz (eds.), Proceedings of DC Tales: Tales of the Disappearing Computer, Santorini Greece, June 1-4, 2003, CTI Press, pp. 263–267
A symbolic description of the awareness state in car driving
In A. Kameas, N. Streitz (eds.), Proceedings of DC Tales: Tales of the Disappearing Computer, Santorini Greece, June 1-4, 2003, CTI Press, pp. 93–96
Driving Attention to the Dangerous
In O. Kaynak, E. Alpaydin, E. Oja (eds.), Artificial Neural Networks and Neural Information Processing - ICANN/ICONIP 2003, Joint International Conference ICANN/ICONIP 2003, Istanbul, Turkey, June 26-29, 2003, Proceedings, Springer (Lecture Notes in Computer Science 2714), pp. 909–916
Monitoring of car driving awareness from biosignals
In B. Apolloni, M. Marinaro, R. Tagliaferri (eds.), Neural Nets: 14th Italian Workshop on Neural Nets, WIRN VIETRI 2003, Vietri sul Mare, Italy, June 4-7, 2003, Springer (Lecture Notes in Computer Science 2859), pp. 269–277
Cooperative games in a stochastic environment
In B. Apolloni, M. Marinaro, R. Tagliaferri (eds.), Neural Nets: 14th Italian Workshop on Neural Nets, WIRN VIETRI 2003, Vietri sul Mare, Italy, June 4-7, 2003, Springer (Lecture Notes in Computer Science 2859), pp. 25–34
Narrowing confidence interval width of PAC learning risk function by algorithmic inference
In On-line proceedings of the 7th International Symposium on Artificial Intelligence and Mathematics (Fort Lauderdale, USA, January 2-4 2002)
Fuzzy Methods for Simplifying a Boolean Formula Inferred from Examples
In L. Wang, S. Halgamuge, X. Yao (eds.), FSDK'02, Proceedings of the 1st International Conference on Fuzzy Systems and Knowledge Discovery: Computational Intelligence for the E-Age, November 18-22, 2002, Orchid Country Club, Singapore, Vol. 2, , pp. 554–558 · extended version in «A Fuzzy Method for Learning Simple Boolean Formulas from Examples» (2005)
Cooperative games in a stochastic environment
In E. Damiani, R. Howlett, L. Jain, N. Ichalkaranje (eds.), Knowledge-Based Intelligent Information Engineering Systems and Allied Technologies - KES 2002 (Proceedings of KES'2002: Sixth Internatinal Conference on Knowledge-Based Intelligent Information & Engineering Systems, Crema, Italy, September 18-19, 2002, vol. 82, IOS Press/Ohmsha (Frontiers in Artificial Intelligence and Applications), pp. 296–300
Twisting features with properties
In M. Marinaro, R. Tagliaferri (eds.), Neural Nets WIRN Vietri-01: Proceedings of the 12th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, 17-19 May, 2001, Springer (Perspectives in Neural Computing), pp. 301–312
Twisting statistics with properties
In A. Morazevich, V. Levashenko, E. Zaitseva, N. Ichalkaranje (eds.), Proceedings of ICINASTe 2001: Internatinal Conference on Information, Networks and System Technlogies (Minsk, Belarus, October 2-4, 2001), BSEU, pp. 48–56
From synapses to rules
In Workshop notes of ECAI 2000: European Conference on Artificial Intelligence - Workshop of connectionist-symbolic integration: representation, paradigm and algorithms (Berlin, Germany, 2000)
Book chapters (8)
Algomotricità: manipolare i fondamenti dell'Informatica
In E. Nardelli (eds.), Coding e oltre: l'informatica nella scuola, Liscianilibri
La formazione degli insegnanti della classe 42/A – Informatica: l'esperienza dell'Università degli Studi di Milano
In A. Labella (eds.), E questo tutti chiamano Informatica, ch. 4, Sapienza Università Editrice, pp. 53–76
A Fuzzy Method for Learning Simple Boolean Formulas from Examples
In S. Halgamuge, L. Wang (eds.), Computational Intelligence for Modelling and Prediction, ch. 26, Springer (Studies in Computational Intelligence, Vol. 2), pp. 367–382 · extended version of «Fuzzy Methods for Simplifying a Boolean Formula Inferred from Examples» (2002)
Statistical bases for learning
In B. Apolloni, F. Kurfess (eds.), From synapses to rules. Discovering symbolic rules from neural processed data, ch. 1, Kluwer Academic/Plenum Publishers, pp. 5–40
Learning regression functions
In B. Apolloni, F. Kurfess (eds.), From synapses to rules. Discovering symbolic rules from neural processed data, ch. 3, Kluwer Academic/Plenum Publishers, pp. 61–73
Cooperative games in a stochastic environment
In B. Apolloni, F. Kurfess (eds.), From synapses to rules. Discovering symbolic rules from neural processed data, ch. 4, Kluwer Academic/Plenum Publishers, pp. 75–86
Fuzzy methods for simplifying a Boolean formula inferred from examples
In B. Apolloni, F. Kurfess (eds.), From synapses to rules. Discovering symbolic rules from neural processed data, ch. 7, Kluwer Academic/Plenum Publishers, pp. 117–128
Learning and checking confidence regions for the hazard function of biomedical data
In B. Apolloni, F. Kurfess (eds.), From synapses to rules. Discovering symbolic rules from neural processed data, ch. 13, Kluwer Academic/Plenum Publishers, pp. 251–260
Theses (2)
Algorithmic approach to the statistical inference of non-Boolean function classes
Università degli Studi di Milano, PhD thesis in Computational Mathematics and Operations Research
Algoritmi di apprendimento per reti neurali non standard
Università degli Studi di Milano, MSc thesis in Computer Science (in Italian)
Software (5)
svMathematica: a Mathematica package for SV classification and regression
Wolfram Mathematica library
Other publications (4)
V Kangourou dell'Informatica 2012--2013. Testi, soluzioni e commenti
Edizioni Kangourou Italia, ISBN 978-88-89249-34-5
Teaching activities
Current activities
- 2020–now
- Algorithms for massive data (DSEH)
- 2019–now
- Algorithms for massive datasets
- 2015–now
- Statistics and data analysis
Bachelor and Master Courses
- 2023–2024
- Deep learning in bioinformatics
- 2019–2022
- Computer programming for data analysis
- 2014–2020
- Computing education
- 2012–2019
- Big scale analytics
- 2018–2019
- Data bases II
- 2018–2019
- Data mining
- 2017–2018
- Analysis of multidimensional data
- 2006–2017
- Simulation
- 2015–2016
- Big data analytics and technologies
- 2015–2016
- Big data and digital methods
- 2011–2016
- Computer programming 3
- 2010–2015
- Operating systems
- 2011–2012
- Computer programming 1
- 2010–2011
- Software design
- 2003–2010
- Laboratory of computer programming 1
- 2006–2010
- Computing systems 2
- 2002–2006
- Theoretical bases for learning
- 2003–2005
- Computer Science
- 2003–2005
- Computer Science
Courses and lectures in PhD programs and graduate schools
- 2018–2019
- Data integration and visualization
- 2016–2018
- Data science seminars
- 2017–2018
- Elements of R and python
- 2017–2018
- Parallel and distributed computing
- 2014–2015
- Computer programming education
- 2013–2014
- Computing education
- 2006–2007
- Symbolic processing laboratory
- 2004–2005
- Mathematica basics
Lectures within university courses
- 2004
- Exercises for the Probability and Statistics course
- 2000–2003
- Lectures within the Neural Networks course
- 2000–2003
- Lectures within the Probability and Statistics course
- 1998
- Exercises for the Probability and Statistics course
Other educational activities
- 2003–2004
- Organization of the vocational course Intelligent Systems for Symbolic Processing, funded by the FSE project
- 2002
- Organization of the course From Synapses to rules – discovering symbolic rules from neural processed data
Thesis supervision
163 theses supervised as advisor or co-advisor: Master theses 66 · Bachelor theses 97. Full list on the website →
Master theses (66)
- 2025/26
- Erica Cappelletti, Application of Machine Learning Techniques for Prediction in Forensic Medicine Using Cross-Institutional Data, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2025/26
- Rana Nosabahsalout, A Vector Database for Automatically Generating Cypher Queries in the Social Domain, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Amirreza Dashti Genave, Analysis of compression techniques for membership function to fuzzy sets learned from data, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Damir Uvayev, Cost-efficient Local RAG for AI Onboarding Assistants, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Greta Angolani, Market-basket analysis for fashion retail: a review, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Isabella Cadisco, NER in the Italian legal domain, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Ivan Mazzon, Famiglie di reti di Hopfield multitask per la classificazione di dati gerarchici, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2024/25
- Magdalena Skowerska, Refining forensic fall height prediction using machine learning: addressing challenges of high-rise buildings, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2024/25
- Mattia Ferraretto, Training tecniqueis for succinct deep neural networks, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2024/25
- Simone Laudani, Utilizzo di algoritmi di rilevamento delle anomalie per l'apprendimento di insiemi fuzzy, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2023/24
- Alessandro Biagiotti, Supervised Machine Learning techniques for quench detection in superconductors, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2023/24
- Antoine Nasra, Drift detection in machine learning via hypothesis testing, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2023/24
- Giordano Vitale, Advancing flight simulator realism through AI-driven semantic segmentation of satellite imagery, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2023/24
- Matteo Rusconi, Estensione e ingegnerizzazione di algoritmi di apprendimento per insiemi fuzzy tramite tecniche basate su vettori di supporto, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2023/24
- Nicola Rinaldi, Analisi comparativa e implementazione di filtri di Bloom appresi, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2023/24
- Silvia Mazzoleni, Forecast of corporate credit rating variation with machine learning techniques, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- Antonio Belotti, Algoritmi di classificazione basati su vettori di supporto per la produzione di modelli succinti, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Davide Raimondi, Studio e progettazione di un'architettura orientata ai servizi per la creazione di una Data Mesh, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Elena Valentina Serbu, Pipeline Reengineering and Optimization -- Rethinking ETL using Pyspark, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- Gianmarco Lodi, Development of a Manufacturing-focused Cloud Data platform using Snowflake, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Lorenzo Polli, Data-driven techniques as a support for customer needs understanding and in-store product placement: the Iper La Grande I case study, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- Loris Bartesaghi, Design and development of a music recommendation system based on Markov Chains, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- Luca Bertoletti, E-commerce insights: analyzing customer reviews through LDA topic modeling and association rules, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- Marco Lassandro, Tecniche di regressione per problemi di medicina forense, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Massimo Frasson, Support Vector Anomaly Detection in Federated Learning, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Mattia Paravisi, Security analysis of cryptographic algorithms: hints from machine learning, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Nicola Manca, Evaluating online and batch machine learning models in production, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2022/23
- Stefano De Filippis, The importance of marketing channels: attribution models and forecasts, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2022/23
- William Biondi, Recommendation system for the fashion industry: a semantic approach, Laurea magistrale in Data Science for Economics, Università degli Studi di Milano
- 2021/22
- Alesia Sommariva, Online machine learning models for a scalable streaming machine learning platform, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2021/22
- Alessandro Beranti, Metodi per la classificazione automatica di pazienti con long-COVID, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2021/22
- Ali Rafiei, Towards computer vision-based natural language processing, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2021/22
- Giulio Lodi, Software architecture for deployment of machine learning models in distributed and reactive environments, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2021/22
- Jaspreet Kaur, Bringing natural language processing in the legal domain: state of the art and evolution of Q&A, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2021/22
- Ruben Popper, Image segmentation and fashion item recognition for luxury brands, Laurea magistrale in Data Science and Economics, Università degli Studi di Milano
- 2020/21
- Andrea Marconi, Tecniche di machine learning per la rilevazione di comportamenti anomali in ambito finanziario e anti-riciclaggio, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2020/21
- Davide Gavio, Towards semantic powered insight engines, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2020/21
- Ivan Lamperti, Data pipeline monitoring through machine learning, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2020/21
- Laura Elena Ciurca, Data science for cybersecurity: a machine learning approach for detecting brute force attacks, Laurea magistrale in Data Science and Economics, Università degli Studi di Milano
- 2020/21
- Luca Fumagalli, Metodi di deep learning per la predizione di siti di missplicing nel genoma umano, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2019/20
- Alessandra Saitta, Applicazione di algoritmi di apprendimento per la riqualificazione delle aree dismesse nelle regioni italiane, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2019/20
- Andrea Adami, Design and implementation of recommender systems for luxury brands, Laurea magistrale in Data Science and Economics, Università degli Studi di Milano
- 2019/20
- Andrea Ferretti, Applying online deep learning in a streaming data platform, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2019/20
- Giovanni Laganà, Rilevazione di fake news basata sull'induzione di insiemi fuzzy, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2019/20
- Simone Quadrelli, Forecasting the occupation of parking slots at Malpensa Airport: a comparison of parametric and machine learning approaches, Laurea magistrale in Data Science and Economics, Università degli Studi di Milano
- 2018/19
- Filippo Vajana, Progettazione e implementazione di misure di affidabilità per problemi di deep learning, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2018/19
- Leonardo Medici, Analisi e perfezionamento di modelli per la valutazione dell'empatia, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2017/18
- Daniele Tria, Delivering online Machine Learning in real-time predictive systems relying on open source distributed streaming processors, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2017/18
- Luca Cermenati, Apprendimento simultaneo di fuzzy set, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2015/16
- Cristiano Aitis, Analisi finanziarie anti-riciclaggio basate su algoritmi di apprendimento bayesiani, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2015/16
- Germana Natalia La Rocca, Sviluppo di un percorso didattico sui sistemi concorrenti per la scuola, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2015/16
- Marco Forlivesi, Ottimizzazione blackbox di funzioni computazionalmente onerose, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2015/16
- Simone Scarano, Gestione della coerenza dell'informazione a priori negli algoritmi di label propagation gerarchici, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2015/16
- Valentina Arrigoni, Unconventional numerical representations for accelerated convolutional neural networks, Laurea magistrale in Matematica, Università degli Studi di Milano
- 2014/15
- Manuel Previtali, Progettazione e sviluppo di un percorso didattico sulla ricorsione come approccio alla soluzione per il problem solving e di un'architettura software di supporto, Laurea magistrale in Informatica per la Comunicazione, Università degli Studi di Milano
- 2013/14
- Leonardo Andrea Calvi, Analisi dell'attendibilità di siti Web per previsioni meteorologiche, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2013/14
- Simone Robutti, Classificazione di dati con etichette incerte tramite metodi basati su vettori di supporto, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2012/13
- Andrea Venturelli, Progettazione e realizzazione di un ambiente online per la fruizione di gare informatiche rivolte a studenti degli istituti secondari di primo e di secondo grado, Laurea magistrale in Informatica per la Comunicazione, Università degli Studi di Milano
- 2012/13
- Omar Negri, Aggregazione e visualizzazione interattiva di dati provenienti da reti sociali, Laurea magistrale in Tecnologie dell'Informazione e della Comunicazione, Università degli Studi di Milano
- 2011/12
- Tommaso Legnani, Utilizzo delle macchine a vettori di supporto nell'apprendimento semi-supervisionato, Laurea magistrale in Matematica, Università degli Studi di Milano
- 2007/08
- Giuseppe Lopes, Algoritmi di controllo del traffico di rete mediante utilizzo di tecniche di granular computing, Laurea in Scienze dell'Informazione, Università degli Studi di Milano
- 2006/07
- Lorenzo Valerio, Progettazione e analisi di algoritmi di regressione per dati di qualità variabile, Laurea magistrale in Tecnologie dell'Informazione e della Comunicazione, Università degli Studi di Milano
- 2006/07
- Luca Natali, Progettazione e analisi di algoritmi di apprendimento per SVM basati su misure di rilevanza, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2004/05
- Stefano Pilia, Un progetto di e-Democracy e e-Government. Il caso Sardegna, Laurea magistrale in Informatica, Università degli Studi di Milano
- 2003/04
- Alberto Minora, Algoritmi di apprendimento basati su modelli dinamici per il flusso delle informazioni, Laurea in Informatica, Università degli Studi di Milano
- 1997/98
- Marco Testa, Modelli di apprendimento di algoritmi approssimati per problemi di ottimizzazione combinatoria, Laurea in Scienze dell'Informazione, Università degli Studi di Milano
Service to the scientific community
Membership to editorial boards of international journals
- 2025–now
- Frontiers in Genetics (Review Editor)
- 2010–2017
- Mathematics and Computers in Simulation
- 2010–2014
- Intelligent decision technologies
Conference organization
- 2026
- Co-chair of the Doctoral Consortium of EANN 2026 (International Conference on Engineering Applications of Neural Networks)
- 2026
- Member of the program committee of AIxIA 2026 (International Conference of the Italian Association for Artificial Intelligence)
- 2025
- Member of the program committee of EANN-EAAAI 2025 (International Conference on Engineering Applications of Neural Networks)
- 2017–2023
- Member of the program committee of DSIR: International Conference on Data Science and Institutional Research
- 2017
- Member of the local organizing committee of the 2017 Bebras international workshop
- 2017
- Member of the local organizing committee of 21st Century Strategies to Tackle Early School Leaving
- 2009–2015
- Member of the scientific committee of the Mathematica Italia User Group Meeting
- 2012
- Member of the local organizing committee of Italian Agile Day 2012
- 2011
- Member of the organizing committee of INFOCULT 2011
- 2011
- Member of the program committee of KES2011
- 2010
- Member of the program committee of ECML PKDD 2010 (European Conference on Machine Learning / Principles and Practice of Knowledge Discovery in Databases)
- 2010
- Member of the organizing committee of the Mathematica Italia User Group Meeting
- 2008
- Member of the technical committee of WCCI2008>
- 2007
- Member of the program committee of WIRN 2007/KES2007
- 2006
- Collaboration in the organization of CISI2006: Conferenza Italiana sui Sistemi Itelligenti
- 2003
- Collaboration in the organization of WIRN2003 (XIV Workshop Italiano Reti Neurali)
Tutorials, workshops, panels and special sessions
- 2023
- Chair of the EANN2023 session CLASSIFICATION / SECURITY / ETHOLOGY
- 2018
- Speaker in the round table Zadeh and the Future of Fuzzy Logic, organized during WILF2018
- 2018
- Chair of the IWBBIO2017 session Computational systems for modelling biological processes
- 2013
- Speaker in the panel Computational Intelligence Methods for Big Data Analysis, organized during WILF2013
- 2007
- Chair of the KES2007/WIRN2007 special session Learning from uncertain data
- 2006
- Co-chair of the workshop New paradigms in hybrid learning systems, at the International Conference on Hybrid Systems and Applications
- 2005
- Tutorial Statistical bases of Machine Learning at IDA 2005: Sixth International Symposium on Intelligent Data Analysis
- 2005
- Tutorial Statistical bases of Machine Learning at HIS'05: Fifth International Conference on Hybrid Intelligent Systems
- 2004
- Tutorial Statistical approaches used in Machine Learning at the 15th European Conference on Machine Learning and 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
- 2004
- Tutorial Statistical approaches used in Machine Learning at the 15th International Conference on Algorithmic Learning Theory
- 2004
- Tutorial Statistical methods for biomedical data processing at the XV Workshop Italiano Reti Neurali (WIRN2004)
Reviewing
- Journals (18)
- Applied Sciences · BMC Bioinformatics · Computers and Operations Research · Data Science and Engineering · Engineering Science and Technology, an International Journal · IEEE Access · IEEE Transactions on Fuzzy Systems · IEEE Transactions on Neural Networks · Information Sciences · Intelligenza Artificiale · Journal of Fuzzy Optimization and Decision Making · Mathematics and Computers in Simulation · Neural Computing and Applications · Neural Networks · Neurocomputing · RAIRO – Theoretical Informatics and Applications · Scientific Reports · Theoretical Computer Science
- Conferences (19)
- AIxIA: International Conference of the Italian Association for Artificial Intelligence · CSTST: International Conference on Soft Computing as Transdisciplinary Science and Technology · DSIR: International Conference on Data Science and Institutional Research · FUN: International Conference on Fun with Algorithms · HIS: International Conference on Hybrid Intelligent Systems · ICANN/ICONIP: Joint 13th International Concerence on Artificial Neural Networks and 10th International Conference on Information Processing · ICTAI: IEEE International Conference on Tools with Artificial Intelligence · IJCNN: IEEE International Joint Conference on Neural Networks · IPMU: Information Processing and Management of Uncertainty in Knowledge-Based Systems · ISSEP: International Conference on informatics in Schools. Situation, Evolution and Perspectives and Automation · IWBBIO: International Work-Conference on Bioinformatics and Biomedical Engineering and Automation · KES: International Conference on Knowledge-Based and Intelligent Information & Engineering Systems · NAIS05: International Workshop on Natural and Artificial Immune Systems · SOFSEM: International Conference on Current Trends in Theory and Practice on Computer Science · STACS2003: 20th International Symposium on Theoretical Aspects of Computer Science · The Web Conference · WCCI: IEEE World Congress on Computational Intelligence · WCICA: IEEE World Congress on Intelligent Control and Automation · WIRN: Italian Workshop on Neural Networks
Other activities
- 2009
- Design of the Web site of the Italian Association of Computer Science University Professors, GRIN.
- 2006
- Design of the Web site of the Italian Society for Neural Networks
Evaluation activities
PhD theses and defences
- 2024
- Review of a PhD thesis
- 2022
- Review of a PhD thesis
- 2018
- Review of a PhD thesis
- 2017
- Member of the PhD defense jury of the École doctorale des sciences et technologies de l'information et de la communication, Université de la Côte d'Azur.
- 2015
- Member of the PhD defense jury of the École doctorale des sciences et technologies de l'information et de la communication, Université de Nice – Sophia Antipolis.
Research projects
- 2023
- FAR (Fondo di Ateneo per la Ricerca) 2023
- 2023
- Ateneo per la ricerca 2023
- 2021
- Research funding scheme A 2020/21
- 2019
- Research funding scheme B 2019/20
- 2019
- Bando SEED (Linea 3 del Piano di Sostegno alla Ricerca)
- 2014
- SIR 2014 (Scientific Independence of young Researchers)
Prize committees
- 2025
- Member of the committee of the Department of Computer Science, University of Milan, for the con.Scienze 2025 PhD awards (Premi di Dottorato).
- 2023
- Chair of the Committee for the assignment of the AIFOS award «Il punto sulla ricerca in materia di salute e sicurezza in Italia: analisi analitica (data analytics) degli elaborati della biblioteca tesi sicurezza AIFOS».
Institutional service
Roles and committees
- 2025–now
- Member of the Technical-Scientific Committee of the University of Milan for the evaluation of the reports of PRIN projects.
- 2024–now
- Member of the joint student-teacher committee (Commissione paritetica docenti-studenti) of the master in Data Science for Economics and Health (Data Science for Economics until 2024/25), University of Milan.
- 2024–now
- Tutor for Erasmus+ exchanges and international mobility of the master in Data Science for Economics and Health (Data Science for Economics until 2024/25), University of Milan.
- 2024–now
- Member of the faculty board of the PhD programme in Computer Science, University of Milan.
- 2022–now
- Member of the Erasmus committee of the Computer Science Department, University of Milan.
- 2021–now
- Orientation tutor for the bachelor in Computer Science, University of Milan.
- 2017–2018
- Member of the faculty board of the PhD programme in Computer Science, University of Milan.
- 2017–2018
- Member of the steering committee of the specialization course in Data science for economics, business and finance of the University of Milan.
- 2013–2017
- Coordinator of the commission for prospective students and vocational orientation of the Science and Technology division of the University of Milan.
- 2012–2017
- Deputy Director of the Computer science Department of the University of Milan for activities related to cultural promotion and counseling for prospective students.
- 2012–2017
- Member of the executive committee of the Computer Science Department, University of Milan.
- 2010–2017
- Coordinator of the committee for prospective students in computer science, Science Division, University of Milan
- 2017
- Member of the steering committee of the specialization course in Management of clinical studies in oncology and hematology-oncology of the University of Milan.
- 2013–2015
- Member of the committee of the Specialization in Mathematics, Physics and Computer science Teaching, University of Milan.
- 2013–2014
- Member of the workgroup for prospective students and vocational orientation of the Academic Senate of the University of Milan.
- 2009–2012
- Member of the executive committee of the Computer Science Department, University of Milan
- 2008–2010
- Member of the committee for prospective students in computer science, Science Division, University of Milan
- 2006–2007
- Member of the committee for prospective students in computer science
- 2002–2005
- Representative of the assistant professors within the Science Division of the University of Milan.
Selection committees
- 2026
- Member of the committee for the assignment of post-graduate research scholarships (art. 18, law 240/2010), University of Milan.
- 2026
- Member of the committee for the assignment of a research appointment within the project «Mind your DRug: biobehavioral modEl towArd precision Medicine in depression» (DREAM), University of Milan.
- 2025
- Member of two selection committees for research grants (type A and type B), Computer Science Department, University of Milan.
- 2023
- Member of the committee for the assignment of a technical position at the Department of Agricultural and Environmental Sciences - Production, Territory, Agroenergy of the University of Milan.
- 2022
- Coordinator of the selection committee for access of foreign students to the master in Computer science of the University of Milan.
- 2020–2021
- Member of the selection committee for access of foreign students to the master in Computer science of the University of Milan.
- 2020
- Member of the admission committee for the competitive PhD position in «Applications of artificial intelligence to study the interaction between genetic and environmental factors underlying human diseases», multi-annual work-programme in genomics and bioinformatics, University of Milan and Ispra Joint Research Center of the European Commission.
- 2020
- Member of the selection committee for access to the 2nd-level specialization course in Bioinformatics and functional genomics of the University of Milan.
- 2014
- Chair of the committee for admission to the specialization in Computer Science teaching
- 2006–2008
- Secretary of the committee for the assignment of abroad student specialization grants for the Computer Science Area, Division of Sciences, University of Milan.
- 2007
- Secretary of the committee for the assignment of an assistant professor position in the Computer Science field at the Law division of "Naples Parthenope" University.
- 2007
- Member of the committee for the renewal of a research associate position in the Computer Science field at the Computer Science Department of the University of Milan.
- 2006
- Secretary of the committee for the assignment of a research associate position in Computer Science at the Computer Science Department of the University of Milan.
- 2005
- Secretary of the committee for the assignment of a research associate position in Computer Science at the Computer Science Department of the University of Milan.
- 2002
- Member of the committee for the assignment of a research associate position in Computer Science at the Computer Science Department of the University of Milan.
- 2002
- Member of the committee for the assignment of a technical position at the Computer Science Department of the University of Milan.
- 2002
- Member of the committee for the assignment of a technical position at the Computer Science Department of the University of Milan.
Third mission
Public engagement
Activities for prospective students and placement
- Talk «Imparare informatica @unimi» («Learning computer science at the University of Milan») at the open day of Liceo Einstein, Milan (30/1/2025).
- Talk «Mezza vita da informatico» («Half a life as a computer scientist») for the students of I.I.S. Cardano (3/2/2018).
- Organization of Programmare in Python («Programming in Python»), an outreach activity for schools.
- Meetings in high schools and organization of visits at the Computer Science department, with the aim of presenting teaching programs.
- Welcome day for first-year students of degrees in the computer science area.
- Presentation of teaching programs in the computer science area at the University open days.
- Organization of meetings between enterprises and students of the programs «Video Games» and «Predictive Modeling and Data Science» for the Master in Computer science on 29/01/2019.
- Organization of the combined school- and work-based program «Doing data science» between february and june 2016.
- Organization of the summer school «Computing as a scientific enterprise», in collaboration with Educandato Setti Carraro Dalla Chiesa, during 2015/16.
- Presentation of the teaching programs in Computing during the national finals of the First Lego League on March, 6/7 2015.
- Presentation of the teaching programs in Computing during the 2014 and 2015 editions of New Game Designer.
- Organization of the learning weeks «Let's play with Google maps» (2010 and 2012) and «The job of data scientist». for high school students.
- Series of lectures for high school students.
Teacher education
- Teacher training course on computer tools for teaching mathematics at the Scuola Militare «Teulié» (Milan, 2025).
- Teacher of Computing education between 2015-16 and 2019-20 (within the master in Computer science).
- In-service teacher training for primary and secondary schools within the «Digit Iscol@» project organized by Regione Sardegna in 2016.
- Selection of the participants in the abilitation course for teachers of Computer Science (2012/13-2014/15).
- Teacher of Teaching 1 in the abilitation course for teachers of Computer Science (2014/15).
- Organization of in-service teacher trainin courses for primary and secondary schools at the Museo Nazionale della Scienza e della Tecnologia «Leonardo da Vinci» in 2013/14.
- Teacher of Computing education in the abilitation course for teachers of Computer Science (2013/14).
- Teacher of Operating systems and networks in the abilitation course for teachers of Computer Science (2012/13).
- Teacher of Symbolic processing laboratory in the Postgraduate school for teachers (2006/07).
Popularization of computer science
- Organization of «You&AI», a digital zone exploring artificial intelligence at the Museo Nazionale della Scienza e della Tecnologia «Leonardo da Vinci» (2021–2022), including a talk at its workshop on face recognition during the European researchers' night (24/9/2021).
- Talk «Gender gap e informatica: bilanciare o ripensare?» («Gender gap and computing: balancing or rethinking?») within the Download Innovation Festival (online, 15/9/2021).
- A short explanatory text on machine learning for the Museo Nazionale della Scienza e della Tecnologia «Leonardo da Vinci» (2020).
- Talk «Big data: che ce ne facciamo?» («Big data: what do we do with them?») at the Museo Nazionale della Scienza e della Tecnologia «Leonardo da Vinci» (2018).
- Talk at the conference «STEM with and in the city» about gender gap in computer science (Università degli Studi di Milano, 19/4/2017).
- Talk at the conference «Gli stati generali dell'alternanza scuola-lavoro» about mixed work/university teaching programs in computer science (Università degli Studi di Milano, 10/4/2017).
- Talk at the conference «Quando i matematici non entrano in aula» about informatics teaching (PRISTEM, Trento, 9/4/2017).
- Presentations and round tables at the Museo Nazionale della Scienza e della Tecnologia «Leonardo da Vinci» during the European researchers night in 2015 and 2016.
- Experiences for schools and general public during the European researchers night between 2013 and 2019.
- Book «Alan Turing – La nascita dell'intelligenza artificiale», published by Grandangolo Scienza (co-authored with Mattia Monga, Anna Morpurgo and Mauro Torelli).
- The radio programme Digito ergo sum, broadcast on Radio popolare in 2011 and 2012 (co-authored with C. Bellettini, A. Dini, A. Ferrara, V. Lonati and M. Monga).
- A set of experiences for school students and general public in the festival The adventure of science organized yearly between 2010 and 2012 by the Division of Mathematical, Physical and Natural Sciences fo the University of Milan.
- Several information activities describing the modifications of the higher education system in Italy contained in law 230 of 4/11/2005 and law 240 of 30/12/2010 (the so-called Moratti and Gelmini reforms) and of its funding by the government (law 133 of 6/8/2008), addressed to professors and students of the Division of Mathematical, Physical and Natural Sciences and to the general public.
Informal learning of computer science
- The design and organization of a set of computer science laboratories addressed to high schools within the Matematita center between 2012 and 2017.
- The organization of the italian chapter of the Bebras challenge between 2015/16 and 2018/19.
- The organization of the challenge Kangourou of Informatics between 2011/12 and 2014/15.
- The organization of INFOCULT, a conference on the popularization of computer science, held in Gargnano (BS) in 2011.
Diffusion of software for scientific computation
- Participating and collaborating to the organization of the Mathematica Italia User Group Meeting.
- The textbook «Fare mathematica con Mathematica» (in italian).
- The implementation of free software.
Continuing education
- 2026
- Python programming (basic level), for the technical, administrative and library staff
- 2025
- Computer tools for teaching mathematics, teacher training course
- 2024
- Seminar within the masterclass «Scienza delle decisioni e intelligenza artificiale»
- 2019
- Python for data science and introduction to machine learning, corporate training
- 2017–2018
- Python programming and relational databases, corporate training
- 2007
- Development of computer systems
- 2004
- Science communication
- 2002–2003
- Intelligent Systems for Symbolic Processing
- 1999–2000
- Visual Basic Programming
Contracts and consultancy
- 2025
- Teacher training contract, Scuola Militare «Teulié», Milan
- 2024
- Consultancy agreement «Intelligent processing of legal knowledge bases using large language models», PBV Monitor s.r.l. (scientific lead)
- 2017
- Osservatorio Milano Duomo
- 2017
- Social Thingum
- 2016
- Consorzio Sardegna Ricerche
- 2010
- Centro Orientamento Scuola e Professioni, University of Milan
Foreign languages skill
- Mother tongue
- Italian
- English
- C2 (proficient)
- French
- C2 (proficient)
- Spanish
- B1 (independent)