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Posts
Web&Graph workshop at WSDM 2026
Published:
The call for papers for the Web&Graph workshop at WSDM 2026 is out now!
What is Machine Unlearning?
Published:
Why would I want my model to unlearn something?
publications
workshop Enhancing fairness in classification tasks with multiple variables: a data-and model-agnostic approach
Giordano d'Aloisio, Giovanni Stilo, Antinisca Di Marco, Andrea D'Angelo
Published in International Workshop on Algorithmic Bias in Search and Recommendation, 2022
DIORAMA: Digital twIn fOR sustAinable territorial MAnagement
Andrea Bianchi, Giordano d'Aloisio, Andrea D'Angelo, Antinisca Di Marco, Alessandro Di Matteo, Jessica Leone, Giulia Scoccia, Giovanni Stilo, Luca Traini
Published in itaDATA, 2022
Q1 Debiaser for Multiple Variables to enhance fairness in classification tasks
Giordano d'Aloisio, Andrea D'Angelo, Antinisca Di Marco, Giovanni Stilo
Published in Information Processing & Management, 2023
workshop Data-driven analysis of gender fairness in the software engineering academic landscape
Giordano d'Aloisio, Andrea D'Angelo, Francesca Marzi, Diana Di Marco, Giovanni Stilo, Antinisca Di Marco
Published in European Conference on Software Architecture (Tracks & Workshops), 2023
Q1 Exploiting spatial relations for grammar-based specification of multidimensional languages
Giuseppe Della Penna, Sergio Orefice, Andrea D'Angelo
Published in Knowledge and Information Systems, 2023
A PlayMyData: a curated dataset of multi-platform video games
Andrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei
Published in Proceedings of the 21st International Conference on Mining Software Repositories, 2024
workshop Grammar-based anomaly detection of microservice systems execution traces
Andrea D'Angelo, Giordano d'Aloisio
Published in Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024
Winner of Best Short Paper award!
Q1 A method to comprehensively identify germline SNVs, INDELs and CNVs from whole exome sequencing data of BRCA1/2 negative breast cancer patients
Andrea Bianchi, Veronica Zelli, Andrea D'Angelo, Alessandro Di Matteo, Giulia Scoccia, Katia Cannita, Antigone S. Dimas, Stavros Glentis, Francesca Zazzeroni, Edoardo Alesse, Antinisca Di Marco, Alessandra Tessitore
Published in NAR Genomics and Bioinformatics, 2024
Towards a Novel Visual Evaluation of Algorithmic Bias: Insights on the Italian Academic System
Francesca Ciccarelli, Andrea D'Angelo, Giovanni Stilo
Published in KDD 2024 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining), Barcelona, 2024
A Novel Relevance Score for Unsupervised Retrieval with Large Language Models
Andrea D'Angelo, Antinisca Di Marco, Giovanni Stilo
Published in KDD 2024 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining), Barcelona, 2024
Q1 Uncovering gender gap in academia: A comprehensive analysis within the software engineering community
Andrea D'Angelo, Giordano d'Aloisio, Francesca Marzi, Antinisca Di Marco, Giovanni Stilo
Published in Journal of Systems and Software, 2024
Best Practices and Lessons from Academia-Industry Collaboration Initiatives
Published in Actions for Gender Balance in Informatics Across Europe, 2025
On the Need for Reproducibility Guidelines for Open-Source Games: A itch.io Case Study
Claudio Di Sipio, Andrea D'Angelo, Riccardo Rubei, Cristiano Politowski
Published in 2025 IEEE Conference on Games (CoG), 2025
A* How to Make Reproducible Research in Machine Unlearning with ERASURE
Andrea D'Angelo, Claudio Savelli, Gabriele Tagliente, Flavio Giobergia, Elena Baralis, Giovanni Stilo
Published in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2025), 2025
HybridKAN: Leveraging Multi-Sized Sub-MLPs for Enhanced Performance
Fabio D'Andreamatteo, Andrea D'Angelo, Giovanni Stilo
Published in ITADATA (Italian Conference on Big Data and Data Science) 2025, 2025
Q1 The Forget-set Identification Problem
Andrea D'Angelo, Francesco Gullo, Giovanni Stilo
Published in Machine Learning Journal (Springer), 2025
A ERASURE: a Modular and Extensible Framework for Machine Unlearning
Andrea D'Angelo, Claudio Savelli, Gabriele Tagliente, Flavio Giobergia, Elena Baralis, Giovanni Stilo
Published in Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM 2025), 2025
Q1 On the Evaluation of Machine Unlearning Methods: A Multi-Domain Classification Benchmark
Andrea D'Angelo, Claudio Savelli, Flavio Giobergia, Elena Baralis, Giovanni Stilo
Published in Machine Learning Journal (Springer), 2026
A* GRACE: Gradient-guided Coreset Selection for LLM Unlearning
Praveen Bushipaka, Andrea D'Angelo, Lucia Passaro, Tommaso Cucinotta
Published in EMNLP 2026 Findings, 2026
A* Lethe: Link Inference Attacks For Evaluation of Edge Unlearning Methods
Andrea D'Angelo, Francesco Gullo, Davide Mottin, Sayan Ranu, Giovanni Stilo
Published in Advances in Neural Information Processing Systems (NeurIPS 2026), Evaluations and Datasets Track, 2026
service
Territori Aperti: dai risultati alle sfide future
Published:
Role: Co-Organizer
CIKM 2024 — ACM International Conference on Information and Knowledge Management
Published:
Role: Proceedings Chair
Tutorial: Unraveling Graph Counterfactual Explainability
Published:
Role: Co-Organizer
WIPE-OUT 2025: Workshop on Machine Unlearning
Published:
Role: Co-Organizer & Program Committee Chair
WEB&GRAPH 2026: Workshop on Web & Graphs, Responsible Intelligence, and Social Media
Published:
Role: Co-Organizer
WSDM 2026 — ACM International Conference on Web Search and Data Mining
Published:
Role: Proceedings Chair
WIPE-OUT 2: Workshop on Machine Unlearning and Privacy Preservation
Published:
Role: Co-Organizer
Knowledge Graphs: Connecting Theory, Algorithms, and Applications
Published:
Role: Co-Organizer
talks
Data-Driven Analysis of Gender Fairness in the Software Engineering Academic Landscape
ECSA 2023 2023 (September) · 📍 Istanbul, Turkey
Uncovering Gender Bias in Academia
AIGAP 2023 2023 (October) · 📍 L'Aquila, Italy
Privacy Implications in the Training and Use of Large Language Models
Territori Aperti 2024 (January) · 📍 Napoli, Italy
Echocardiographic Epicardial Adipose Tissue Quantification: Challenges and Insights
PerFail @ PerCom 2024 2024 (March) · 📍 Biarritz, France
Machine Unlearning: Safeguarding Privacy and Security in AI Models
Technical University of Munich 2024 (July) · 📍 Munich, Germany
A Novel Relevance Score for Unsupervised Retrieval with Large Language Models
KDD 2024 2024 (August) · 📍 Barcelona, Spain
HybridKAN: Leveraging Multi-Sized Sub-MLPs for Enhanced Performance
ITADATA 2025 (September) · 📍 Turin, Italy
Forgetting Right: Towards Reproducible Benchmarks in Machine Unlearning with ERASURE
WIPE-OUT @ ECML-PKDD 2025 2025 (September) · 📍 Porto, Portugal
Unraveling Graph Counterfactual Explainability: from Theoretical Foundations to Technical Mastery
ECML-PKDD 2025 2025 (September) · 📍 Porto, Portugal
Perspectives on Machine Unlearning and Privacy-preserving Machine Learning
Technical University of Dresden 2026 (February) · 📍 Dresden, Germany (Remote)
Opportunities and Privacy Risks with Artificial Intelligence
Istituto Tecnico Marconi Penne 2026 (February) · 📍 Penne, Italy
Trustworthy AI and the Right to be Forgotten: The Role of Machine Unlearning
LUISS Guido Carli 2026 (July) · 📍 Rome, Italy
teaching
Reinforcement Learning Laboratory
University of L'Aquila Master Degree course · 2023
Lab module on reinforcement learning algorithms and policy optimization, part of the AI Master's course.
Reinforcement LearningAIPolicy Optimization
By clicking on “Download slides”, you will be redirected to the Github that I used to teach the Reinforcement Learning module of the AI course @ Univaq in 2023 (updated for 2024).
Deep Neural Networks Laboratory
University of L'Aquila Master Degree course · 2024
Lab course on deep neural network architectures, with hands-on implementations covering modern deep learning techniques.
Deep LearningNeural NetworksPyTorch
By clicking on “Download slides”, you will be redirected to the Github that I used to teach the Deep Neural Networks Laboratory @ Univaq in 2024.
Reinforcement Learning (MOC Course)
SoBigData Academy Online course (MOC) · 2024
Co-creator of the MOC course on Reinforcement Learning for the SoBigData Academy, covering fundamental and advanced RL algorithms.
Reinforcement LearningMOCSoBigData
Co-creator of the MOC course on “Reinforcement Learning” for the SoBigData Academy.
Reinforcement Learning Laboratory
University of L'Aquila Master Degree course · 2024
Lab module on reinforcement learning algorithms and policy optimization, part of the AI Master's course.
Reinforcement LearningAIPolicy Optimization
By clicking on “Download slides”, you will be redirected to the Github that I used to teach the Reinforcement Learning module of the AI course @ Univaq in 2024.
Big data management: data mining and analysis for management decisions
LUISS University of Rome Master's course · 2026
Course on big data management techniques and data mining methods for business decision-making in AI-driven environments.
Big DataData MiningMachine Learning
No slides are publicly available for this course. Contact me for further information.
Privacy Preservation for Machine Learning
Engage.EU Summer School Summer school lecture · 2026
Lecture on privacy-preserving machine learning, covering the main threats to data privacy and mitigation techniques such as differential privacy and machine unlearning.
Privacy-preserving Machine LearningDifferential PrivacyMachine Unlearning
No slides are publicly available for this lecture. Contact me for further information.
theses
Recent Advances in Chain-of-Thought Prompting: Current Trends and Automation Approaches
University of L'Aquila 2025
From ERASURE to Evaluation of Machine Unlearning Techniques
University of L'Aquila 2025
HybridKAN: Leveraging Multi-Sized Sub-MLPs for Enhanced Performance
University of L'Aquila 2025
Beyond the Systematic Evaluation of Large Language Models: From Theory to Practical Analysis of Results
University of L'Aquila 2025
ERASURE: Improving Usability and Community Adoption of a Machine Unlearning Framework
A thesis focused on debugging, refactoring, and documenting the ERASURE machine unlearning framework, lowering the skill floor so that researchers can adopt it without reading the source code.
Fairness-Aware Machine Unlearning
Can selectively forgetting training data improve or harm model fairness? This thesis investigates the interplay between machine unlearning and fairness metrics across multiple domains using the ERASURE framework.
Machine Unlearning Applied to Time Series and Human Activity Recognition
University of Urbino 2026