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Andrea PasseriniView profile

Professor

University of TrentoItaly

Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.

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Francesca MarazziView profile

Assistant Professor

Campus Bio-Medico University of RomeItaly

Francesca Marazzi is an Assistant Professor at the University of Rome Tor Vergata's Department of Economics and Finance. She holds affiliations with the CESifo Research Network (as an affiliate), the CESIEG research centre at LUISS Guido Carli University (Deputy Director), and the DEMA P research cluster at Middlesex University, London. Her research focuses on behavioral and experimental economics, particularly exploring dishonest behavior, responsibility avoidance, and health economics issues like women's health and obesity interventions. She teaches courses such as 'Coding for Economic Applications' and 'Research Methods for Social Sciences' at both bachelor's and master's levels. Her work bridges theoretical models with empirical experimentation, addressing topics like corruption, public goods provision, and policy design. Notable contributions include studies on transparency's impact on bribery, pandemic-related behavioral changes, and the effects of soft drink taxation on adolescent health. She actively participates in interdisciplinary projects, such as the CREA initiative integrating AI and mathematics for fairness assertions, and the LongITools exposome analysis in chronic disease research. Marazzi's academic output emphasizes experimental methodologies, with recent focus on pandemic-driven behavioral shifts, financial stability mechanisms, and innovative governance metrics leveraging earth observation data post-wildfires. Her research portfolio reflects a commitment to applied microeconomic analysis with direct societal relevance.

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Salvatore RuggieriView profile

Professor

National Research Council of Italy (CNR)Italy

Salvatore Ruggieri is a Full Professor in the Department of Computer Science at the University of Pisa, where he teaches in the Master Programme in Data Science and Business Informatics. He is affiliated with the KDD LAB, a joint research group of ISTI-CNR and the University of Pisa, and actively contributes to national and European AI initiatives such as XAI, NoBIAS, TAILOR, and SoBigData.eu. His research focuses on data mining and knowledge discovery, with a strong emphasis on ethical AI. Key areas include discrimination discovery and prevention, fairness, privacy, explainable AI (XAI), causal inference, and classification algorithms. He has led significant projects such as ENFORCE, a national FIRB project on legal and computational enforcement of non-discrimination and privacy rights in ICT systems (2010–2014), and has served as program chair for the XIII Italian Symposium on Artificial Intelligence (2014). The recent publications (2018–2023) highlight a consistent trend in interpretable and fair machine learning, including selective classification, stability of interpretable models, and causal reasoning for fairness. His work often involves collaboration with leading researchers like Dino Pedreschi and Riccardo Guidotti, and appears in top venues such as AAAI, IEEE TKDE, and WIREs. His scientific honors include the award for the best Ph.D. thesis in Theoretical Computer Science from the Italian Chapter of EATCS. Best Ph.D. Thesis in Theoretical Computer Science, Italian Chapter of EATCS He advises and collaborates with numerous researchers in the KDD LAB and has contributed to major grants and research initiatives in AI and data science. He is involved in educational programs, including the National Ph.D. in Artificial Intelligence - Society, and promotes interdisciplinary research at the intersection of computer science, law, and ethics. Ruggieri is a member of the KDD LAB, where he leads research in ethical and transparent AI. He is also part of large collaborative networks such as SoBigData.eu and HumanE-AI-Net, which aim to build socially responsible and human-centered AI systems.

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Chiara LongoniView profile

Associate Professor

Bocconi UniversityItaly

Chiara Longoni is an Associate Professor in the Department of Marketing at Bocconi University in Milan, Italy. Her interdisciplinary research examines consumer responses to artificial intelligence applications in healthcare, government services, and sustainability, as well as drivers of societal well-being. She has received multiple scientific awards including the 2023 MSI Young Scholar award and 2022 Journal of Consumer Research Best Article Award. Ph.D. in Marketing from New York University’s Stern School of Business M.S. (summa cum laude) from Bocconi University M.A. (Honors) in Psychology from NYU M.Phil. in Marketing from NYU Stern Her research spans two primary domains: AI Adoption: Investigates psychological responses to artificial intelligence in healthcare, recommendation systems, and governance. Sustainability: Analyzes behavior change mechanisms and climate action drivers through global interventions involving 63 countries. Key publication venues include Journal of Consumer Research , Journal of Marketing , Nature Human Behavior , and Science Advances . Current editorial roles as Associate Editor for the Journal of Consumer Research and reviewer for top journals across marketing, management, and medicine.

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Anh Nguyen Nguyen DucView profile

Professor

Free University of Bozen-BolzanoItaly

Dr. Anh Nguyen Nguyen Duc serves as Full Professor at the University of South-Eastern Norway and the Norwegian University of Science and Technology (NTNU), with visiting scholar positions across Norwegian, Finnish, Italian, and Vietnamese institutions. His academic work centers on software engineering with emphasis on human, process, and ecosystem dimensions of development. Education: MS: Technical University of Kaiserslautern and Blekinge Institute of Technology (double degree) PhD: Norwegian University of Science and Technology Research fingerprint analysis reveals dominant focus on software startups (27%), supplemented by software processes (6%) and engineering education (5%). His expertise spans cybersecurity, global software development, business-driven methodologies, and software analytics, consistently addressing human-organizational challenges in dynamic development environments. Recent publications (2024-2025) demonstrate accelerating integration of AI in software engineering, particularly through large language models for startup assistance, generative AI adoption frameworks, and autonomous agent systems. Concurrently, he investigates risk management in software ventures and fairness in educational ML applications, reflecting interdisciplinary work bridging software engineering with business, AI ethics, and educational technology.

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Saverio MascoloView profile

Professor

Polytechnic University of BariItaly

Saverio Mascolo is a Full Professor at the Polytechnic University of Bari , Department of Electrical and Information Engineering. He leads the Control of Computing and Communication Systems Lab (C3Lab) and contributes to IEEE/ACM Transactions on Networking as an Associate Editor. His research focuses on Future Internet, network congestion control, and real-time communication systems. Laurea in Electronic Engineering, Politecnico di Bari (1991) PhD in Electronic and Automatic Control, Politecnico di Bari (1995) Visiting researcher roles at UCLA (1995, 1999), INRIA (2004), and FTW (2004) Research spans network congestion control , adaptive video streaming , and real-time communication . His lab develops protocols like TCP Westwood+ and contributes to WebRTC standards. Current projects include low-delay protocols for immersive video streaming and autonomous systems control. Recent publications emphasize adaptive threshold mechanisms in congestion control, millimeter-wave radar datasets , and immersive teleoperation systems . Projects integrate nonlinear control , time-delay analysis , and cloud-based multimedia delivery . Scientific recognition includes: Elevated to IEEE Fellow (2018) for congestion control contributions Google Faculty Award (2014) for WebRTC research Cisco Research Award (2013) for video streaming control Best paper awards at MMSYS (2025, 2024, 2016) Grants fund research in cloud-based video platforms (MISE, 2017-2020), WebRTC optimization (MIUR, 2012-2015), and network control algorithms. His lab collaborates with institutions like Uppsala University (since 2001) and industry partners.

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Nicolò Cesa-BianchiView profile

Professor

University of MilanItaly

Nicolò Cesa-Bianchi is a Professor of Computer Science at the University of Milan, Department of Computer Science (Dipartimento di Informatica), and affiliated with the DEIB Department at Politecnico di Milano. His research focuses on foundational aspects of machine learning, particularly online learning, multi-armed bandits, reinforcement learning, and graph analytics. He is an ELLIS Fellow and a corresponding member of the Accademia Nazionale dei Lincei. Research interests include the design and analysis of algorithms for prediction, clustering, and online decision-making, with applications to digital markets, social networks, and bioinformatics. Notable contributions span cooperative online learning, multitask learning, and bandit algorithms. He co-authored the influential book Prediction, Learning, and Games (2006). Professional roles include Board member of ELLIS, co-director of the Milan ELLIS unit, and involvement in EU initiatives like ELSA (Secure & Safe AI) and ELIAS (AI for Sustainability). He teaches graduate courses on statistical methods, machine learning, and reinforcement learning, with a focus on theoretical foundations. Key awards: ELLIS Fellowship (2020), Corresponding Member of the Accademia Nazionale dei Lincei (Italian National Academy of Sciences). His work bridges theory and practice, addressing challenges in adaptive systems, market design, and algorithmic fairness. Current projects explore distributed learning, regret minimization in adversarial environments, and interpretable models.

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Salvatore RuggieriView profile

Professor

University of PisaItaly

Salvatore Ruggieri is a Full Professor at the Department of Computer Science, University of Pisa, Italy. He coordinates the National PhD Program in Artificial Intelligence for Society and teaches in the Master Program in Data Science and Business Informatics. His research focuses on algorithmic fairness, explainable AI, causality, and discrimination discovery, with contributions to tools like YaDT, X-SPELLS, and SCube. He co-chaired FAT*2020 and contributed to projects such as NoBias and HumanE-AI. His work bridges theoretical foundations with practical applications in fairness, privacy, and societal impact. Education: Ph.D. in Computer Science (1999), University of Pisa. Research Interests: Algorithmic Fairness and Non-Discrimination Explainable AI (XAI) Causal Inference Methods Decision Tree Algorithms Social Network Analysis Key Contributions: Developer of YaDT (decision tree tool) and SCube (segregation discovery). Advocacy for ethical AI through policy frameworks and GDPR-compliant explanations. Scientific Awards: Recipient of the Best Ph.D. Thesis in Theoretical Computer Science (EATCS, 1999).

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Anna MonrealeView profile

Associate Professor

National Research Council of Italy (CNR)Italy

Anna Monreale is an Associate Professor in the Department of Computer Science at the University of Pisa and a key member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa. Her academic career is rooted in the University of Pisa, where she completed her Bachelor's, Master's, and Ph.D. in Computer Science. Her research focuses on privacy-preserving data analytics, with core interests in big data analytics, social network analysis, spatio-temporal mining, and explainable AI. She is particularly known for her work on privacy-by-design in data mining and evaluating privacy risks in analytical processes. Her research bridges technical innovation with ethical and legal considerations in data science. Her recent publications reveal a strong trend toward explainable AI, privacy in federated learning, and risk assessment in mobility and health data. She actively contributes to developing methods for explaining black-box models, assessing privacy exposure, and balancing privacy, utility, and fairness in AI systems. Privacy by Design Ambassador (2014) ISTI-CNR Young++ Researcher Award (2014) Monreale has advised and co-chaired several international workshops, including PriSMO, PinSoDa, and MoKMaSD, and serves on editorial boards such as Transactions on Data Privacy. She teaches advanced data mining, big data ethics, and database systems across multiple graduate and undergraduate programs. She is involved in major EU projects like SoBigData, XAI, TAILOR, and HumMingBird, reflecting her leadership in data science and AI ethics. She is affiliated with the KDD-Lab, a prominent research group focused on knowledge discovery, social mining, and big data analytics, contributing to both theoretical advances and real-world applications in privacy-aware data science.

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Nicoletta CorrocherView profile

Lecturer

Bocconi UniversityItaly

Nicoletta Corrocher is a Lecturer in Applied Economics at Bocconi University and Research Fellow at ICRIOS (Invernizzi Center for Research on Innovation, Organization, Strategy and Entrepreneurship). She holds a PhD in Economics and Management of Innovation from Sant'Anna School of Advanced Studies and an MSc in Science and Technology Policy from SPRU, University of Sussex. Her research focuses on innovation dynamics, digital transformation, and sustainability, particularly in ICT industries and service sectors. Key areas include eco-innovation, technology diffusion, and policy impacts on innovation adoption. Her teaching portfolio includes courses such as Innovation in Services , Innovation, Growth and Sustainability , and Entrepreneurship Lab , emphasizing critical thinking and real-world application. Recent research explores algorithmic decision-making fairness, unintended effects of environmental policies, and SME digitalization strategies. Corrocher’s work spans empirical analyses of green technology catch-up, mobile commerce adoption, and cluster policy effectiveness. Her contributions appear in journals like Research Policy , Regional Studies , and Industry and Innovation . Ongoing projects address digitalization-sustainability complementarity in SMEs and the role of science in green technologies. Her research highlights include studies on patent growth in environmental technologies, personalized pricing in telecom, and the 'resource curse' in European regions. She advises on innovation policy design, emphasizing evidence-based approaches to bridge theory and practice. Labs and collaborations involve interdisciplinary teams at ICRIOS, focusing on innovation ecosystems, sustainable transitions, and digital economy dynamics. Her work integrates quantitative methods with institutional analysis to address global challenges in innovation and development.

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Luca Di GasperoView profile

Associate Professor

University of UdineItaly

Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services

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Giuseppe ContissaView profile

Associate Professor

University of BolognaItaly

Giuseppe Contissa is an Associate Professor at the Department of Legal Sciences, University of Bologna. His work focuses on Legal Informatics, AI & Law, Legal Theory, and Law & Technology, particularly in robotics and automated systems. He holds a PhD in Legal Informatics from the University of Bologna and has extensive experience in research projects like ALIAS (air traffic management liability) and CLAUDETTE (AI-driven contract analysis). He is affiliated with ALMA Ai (Human-Centered AI Institute) and ARCES (Electronic Systems Research). Education: PhD in Legal Informatics (2006, University of Bologna), Master's in Legal Informatics (2002), Laurea in Jurisprudence (2001). Research Interests: Computable legal reasoning, AI ethics in healthcare, liability frameworks for autonomous systems, socio-technical systems governance, and automated vehicle regulation. He leads projects on AI certification in aviation and consumer protection through AI systems. Key Projects: CrossJustice (digital criminal procedure rights), SAFELAND (air traffic safety), and COMPULAW (computable law models). He advises the Council of Europe on AI ethics in justice systems. Labs/Teams: CIRSFID (Computer Law Research), ALMA Ai, and collaborations with CodeX (Stanford).

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Fosca GiannottiView profile

Professor

National Research Council of Italy (CNR)Italy

Fosca Giannotti is a Full Professor at Scuola Normale Superiore in Pisa, Italy, and leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Founded in 1994, the Pisa KDD Lab is one of the earliest research labs focused on data mining. Giannotti is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Her educational background includes a Master Degree in Computer Science from the University of Pisa (1982) with 110/100 cum laude. She has held numerous visiting positions including at MCC in Austin, CWI Amsterdam, UCLA, and the Barabasi Lab at Northeastern University. Giannotti's research focuses on social mining from big data, encompassing smart cities, human dynamics, social and economic networks, ethics and trust, and diffusion of innovations. She has authored more than 300 papers and coordinated tens of European projects and industrial collaborations. Her current work increasingly centers on Explainable AI (XAI), as evidenced by her prestigious ERC Advanced Grant for the XAI project focused on "Science and technology for the explanation of AI decision making." Her recent publications reveal a strong emphasis on trustworthy AI, with research spanning privacy-preserving techniques, fairness in machine learning, human-AI collaboration frameworks, and medical applications of explainable AI. The breadth of her work demonstrates how data mining principles are being applied across diverse domains from social sciences to healthcare. ERC Advanced Grant for XAI project Premio Internazionale Tecnovisionarie 2021 Intelligenza Artificiale Giannotti has coordinated numerous significant projects including SoBigData (the European research infrastructure on Big Data Analytics and Social Mining), XAI, TAILOR (Foundations of Trustworthy AI), HumanE-AI-Net, and AI4EU. As former coordinator of SoBigData, she led an ecosystem of ten cutting-edge European research centers providing an open platform for interdisciplinary data science. She leads the Pisa KDD Lab, which serves as a hub for research on knowledge discovery and data mining. The lab has been instrumental in developing techniques for mobility data analysis, social network mining, and privacy-preserving data analytics, with applications ranging from smart cities to pandemic response.

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Marco ScialdoneView profile

Lecturer

European University of RomeItaly

Marco Scialdone is a Lecturer at the European University of Rome, specializing in Information Technology Law and Legal Categories related to Technology. He holds a PhD from the same university (2016) and Master’s degrees from La Sapienza University of Rome (2005). A Fellow of the IAIC – Italian Academy of the Internet Code, he focuses on AI ethics, digital rights, and consumer protection law. His research bridges legal frameworks with emerging technologies like artificial intelligence and robotics. Education: PhD in Legal Categories and Technology (2016), European University of Rome Master’s in Computer Law (2005), La Sapienza University of Rome LL.B. in Law (Cum Laude, 110/110), LUISS Guido Carli University Research Interests: His work explores the intersection of law and technology, including AI governance, digital copyright, consumer rights in the digital age, and the legal implications of robotics. He emphasizes ethical AI development, regulatory challenges in digital markets, and public administration digitization. Recent studies analyze algorithmic bias in judicial systems and the legal protection of user-generated content. Publications & Expertise: Authored over 20 publications, including monographs like Living with Artificial Intelligence (2021) and The Legal Protection of User-Generated Content (2018). His articles address topics such as non-human creativity rights, predictive justice models, and cross-border copyright conflicts. He has served as an expert in AI policy (Italian Government’s High-Level Group on AI, 2018) and on the Permanent Advisory Committee for Copyright (2019). Professional Roles: Head of Litigation & Academic Outreach at Euroconsumers (since 2021) Former lecturer at La Sapienza University (2015–2018) and University of Perugia (2007–2012)

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Andrea VitalettiView profile

Associate Professor

Sapienza University of RomeItaly

Andrea Vitaletti is an Associate Professor at Sapienza University of Rome , affiliated with the Department of Computer Engineering, Automatics and Management Antonio Ruberti (DIAG) in the College of Engineering. His academic career spans over two decades of research in networking and algorithmic topics. PhD in Computer Science, Sapienza University of Rome (1998–2002) Assistant Professor (Ricercatore) at Sapienza (2007–2019) Co-founder of spin-offs WSENSE (2012–2019) and WLAB (2002–2016) Research Interests focus on decentralized systems , particularly blockchain technologies , Internet of Things (IoT) , federated machine learning , and data privacy . His work bridges theoretical algorithmic research with practical implementations in wireless sensor networks and distributed ledger systems. Scientific Contributions include over 90 publications, 2 patents, and leadership in the EU FET OPEN project PLEASED. His applied research has been recognized with multiple awards: 2000: Wonderland Contest - Media and Communication 2002: Simagine Innovation Prize 2004: Simagine Bronze Award 2007: Premio Perotto Top Prize 2012: Italiacamp Winner He leads the Wireless Sensor Networks lab at DIAG, supervising 2 PhD students, 1 post-doc, and 5 master students. His teaching portfolio includes courses on IoT, blockchain, cybersecurity, and digital entrepreneurship since 2000.

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