Roberto Navigli serves as an Associate Professor in the Department of Computer Science at Sapienza University of Rome, conducting pioneering research in Natural Language Processing. He holds editorial leadership positions including Associate Editor of the Artificial Intelligence Journal and membership on the Journal of Natural Language Engineering editorial board. His research program centers on multilingual semantic technologies, with foundational contributions to word sense disambiguation, ontology learning from unstructured text, and large-scale knowledge acquisition systems. Navigli's work bridges theoretical linguistics with practical applications in relation extraction and open information extraction, emphasizing cross-lingual capabilities and resource scalability. Publication analysis reveals a sustained focus on semantic resource development, evolving from early WordNet extensions (2003) to contemporary open knowledge extraction frameworks (2015). This trajectory demonstrates consistent innovation in transforming unstructured text into structured knowledge representations for multilingual applications. Major scientific recognition includes: Marco Cadoli 2007 AI*IA Prize for best doctoral thesis in AI Marco Somalvico 2013 AI*IA Prize for best young AI researcher ERC Starting Grant (2011-2016) for multilingual word sense disambiguation Google Focused Research Award on Natural Language Understanding Navigli directs significant research initiatives funded by competitive grants, including his ERC project and Google collaboration, while providing academic leadership through area chair roles at ACL, WWW, and *SEM conferences. His service as senior program committee member for IJCAI and editorial board positions underscores substantial community impact.
Giacomo Fiumara is an Associate Professor at the University of Messina, Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences. He holds academic rank since October 2021. Previously, he served as a Permanent Researcher (2008–2021) and secondary school teacher (1997–2008). He earned a Doctorate in Physics (1993) and a Degree in Physics (1989), both from the University of Messina. He is an associate member of the Accademia Peloritana dei Pericolanti and qualified as an associate professor in INF/01 and ING-INF/05 sectors. His research focuses on social network analysis, network science, data science, criminal networks, knowledge representation, bioinformatics, and computational modeling. He has supervised over 170 theses and advised PhD students in Mathematics and Computational Sciences. Key collaborations include work with Prof. Pasquale De Meo on criminal networks and complex systems, and international projects with institutions in the US, UK, China, and Australia. Teaching includes courses on Algorithms, Data Structures, Bioinformatics, and Machine Learning across Computer Science, Engineering, and Medical programs since 2000. He also contributed to international programs at Lviv Polytechnic, Birzeit University, Cluj-Napoca, and Murcia. His editorial roles include Associate Editor of IEEE Access and Academic Editor of Complexity. He holds a patent for predictive analysis of criminal organizations' social structures and has received FFABR research funding. Key awards include FFABR funding (2017) and recognition in the FFABR Unime 2020 II edition. He organized conferences like Crimenet 2014 and participated in high-profile events such as the 2022 Complex Networks conference in Palermo, presenting on quantum walks for criminal network analysis.
Federico Demaria is a Researcher at the Environmental Science and Technology Institute, Universitat Autònoma de Barcelona. He focuses on ecological economics, political ecology, and environmental justice, advocating for socio-ecological transformation beyond economic growth. As a founding member of Research & Degrowth and a board member of the European Society for Ecological Economics, he bridges academic research with activism. His current role includes deputy coordination of the ERC-funded EnvJustice project, studying global environmental justice movements. Research emphasizes waste management conflicts, informal recyclers' roles, and degrowth alternatives. Key publications include Decrecimiento: Vocabulario para una nueva era and Pluriverse: A Post-Development Dictionary , translated into multiple languages. Research interests coalesce around dismantling growth-based paradigms, centering marginalized groups in environmental struggles, and redefining sustainability beyond capitalist modernity. His work critiques extractive systems while proposing pluriversal alternatives grounded in indigenous and communal knowledge. Key Projects: EnvJustice (ERC), Degrowth initiative Key Themes: Waste politics, environmental conflicts, post-development, degrowth economics
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.
Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.
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.
Fabrizio Falchi is a researcher at the Artificial Intelligence for Media and Humanities (AIMH) Lab of the Institute of Information Science and Technologies (ISTI) within Italy's National Research Council (CNR). He also maintains an associate position at the Biorobotics Institute of Scuola Superiore Sant'Anna. His work focuses on developing advanced multimedia retrieval systems, with the VISIONE platform being his most notable contribution, which has won international competitions including the Video Browser Showdown in 2024 and placed second in 2023. Falchi's educational background includes: Ph.D. in Information Engineering from University of Pisa (Italy) Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic) M.B.A. from Scuola Superiore Sant'Anna in Pisa His research spans deep learning, convolutional neural networks, deep features extraction, similarity search algorithms, distributed indexing systems, multimedia information retrieval, computer vision applications, and peer-to-peer systems. Falchi has made significant contributions to fine-grained visual understanding, cross-modal retrieval (particularly image-text matching), and robustness of deep learning systems against adversarial attacks. His work demonstrates a strong focus on practical applications of these technologies, particularly in video retrieval systems and safety monitoring solutions. Analysis of Falchi's recent publications reveals a strong focus on video and image retrieval systems, with the VISIONE platform being central to his work. His research shows increasing emphasis on fine-grained understanding in computer vision, cross-modal retrieval, and addressing practical challenges like cross-resolution face recognition. Recent work demonstrates innovation in making these systems more efficient through techniques like knowledge distillation (ALADIN) and leveraging virtual worlds for training data. His publications consistently bridge theoretical advances with practical applications in surveillance, safety monitoring, and multimedia search. Falchi's work has received significant recognition: Best paper award at CBMI 2024 for 'Is ClLIP the main roadblock for fine-grained open-world perception?' VISIONE 2024 won the Video Browser Showdown competition in Amsterdam VISIONE obtained second place at Video Browser Showdown 2023 in Bergen Best Paper Award for 'Learning Safety Equipment Detection using Virtual Worlds' at CBMI 2019 Falchi collaborates extensively with researchers at ISTI-CNR, particularly within the AIMH Lab. His work on VISIONE involves collaboration with Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. As co-chair of Ital-IA 2023, the 3rd National Conference on Artificial Intelligence, he plays an active role in the academic community. He is a member of ACM (since 2012), the Computer Vision Foundation, the Italian Association for Computer Vision Pattern Recognition and Machine Learning (CVPL), and the CINI Lab on Artificial Intelligence and Intelligent Systems. Falchi is a key member of the Artificial Intelligence for Media and Humanities (AIMH) Lab at ISTI-CNR, where he leads research on video retrieval systems. The lab has developed the award-winning VISIONE platform, which combines multiple scientific results in content-based video retrieval. His team focuses on developing systems that enable users to search for target videos using textual prompts, drawing objects and colors, or images as query examples. The lab's work demonstrates strong interdisciplinary collaboration, bridging computer science with practical applications in media, safety monitoring, and urban environments.
Giorgio Riello is a Full-time Professor and Chair of Early Modern Global History at the European University Institute in Florence, where he joined in 2019 after a distinguished career at the University of Warwick. He previously served as Professor of Global History and Culture at Warwick University (2011-present), Director of the Warwick Institute of Advanced Study (2014-17), and Chair of the Pasold Research Fund (2016-19). His academic journey began with a Ph.D. in History from University College London (2002) following a Laurea in Economia Aziendale from Ca' Foscari University, Venice (1998). Riello's research fundamentally explores the intersections of material culture, trade, and consumption in early modern Europe and Asia, with particular focus on textiles, fashion, and luxury goods. His work challenges Eurocentric narratives by demonstrating how Asian commodities and production techniques shaped global economic development. Key research areas include global cotton trade networks, the material culture of fashion, early modern capitalism, and Indian Ocean trade systems. His methodological approach combines economic history with material culture studies, using objects as primary sources for understanding global connections. His influential publications include Cotton: The Fabric that Made the Modern World (2013), which won the World History Association Bentley Prize, Luxury: A Rich History (2016, co-authored with Peter McNeil), and Back In Fashion: Western Fashion since the Middle Ages (2020). His recent work has focused on the 'Diamond-shaped Trade' concept connecting Atlantic and Indian Ocean systems, and he is currently co-authoring 'Cultures of Innovation: Silk in Pre-Modern Eurasia' with Dagmar Schaefer. World History Association Bentley Book Prize (2014) Iris Foundation Award for Decorative Arts (2016) Philip Leverhulme Prize (2011) Fernand Braudel Senior Fellowship (2012) Stanford Humanities Center Fellow (2010-11) Riello leads the ERC Advanced Grant project 'CAPASIA: The Asian Origins of Global Capitalism' and has successfully secured numerous major research grants including a Marie Curie COFUND and Leverhulme International Network funding. He supervises approximately 10 PhD students at the EUI and serves as second reader for another 8 students. His collaborative work extends to major international museums including the Victoria and Albert Museum, Peabody Essex Museum, and MUDEC Museum in Milan, where he participated in the redisplay of their permanent collection between 2019-2022.
Simone Paolo Ponzetto is an Assistant Professor (Juniorprofessor) at the University of Mannheim since 2013, affiliated with the Research Group Data and Web Science. His research focuses on Semantic Web technologies, Natural Language Processing (NLP), and knowledge acquisition, particularly leveraging collaboratively built resources like Wikipedia. Prior to Mannheim, he held postdoctoral roles at Sapienza University of Rome and research positions at the University of Heidelberg and Stuttgart. His work includes pioneering projects like BabelNet, a multilingual semantic network. Ponzetto earned his PhD in Computational Linguistics from the University of Stuttgart, with interdisciplinary contributions to coreference resolution, semantic relatedness, and ontology learning. Research Interests: Unsupervised/weakly-supervised knowledge extraction Multilingual ontology learning and semantic networks Lexical semantics (word sense disambiguation, semantic similarity) Discourse semantics (coreference resolution, coherence modeling) Professional Contributions: Guest editor for a Artificial Intelligence Journal special issue on AI and Wikipedia Area chair for EMNLP-CoNLL 2012 and EACL 2014 Program committee member for ACL, AAAI, and other top conferences Lab/Team: Active in the Research Group Data and Web Science at Mannheim, advancing AI and NLP applications in collaborative knowledge systems.
Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics
Enrico Franconi is a tenured full Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano, Italy. He is the founder and director of the KRDB Research Centre for Knowledge-based Artificial Intelligence, established in 2002. His research focuses on applying database, AI, and semantic technologies to address challenges in information systems design, data integration, and big data analysis. He holds leadership roles including former Vice-Rector for Research (2005-2006) and director of the European Masters Program in Computational Logic (2004-2019). His academic contributions span Description Logics, knowledge representation, and ontology engineering, with a strong emphasis on theoretical foundations and practical applications. He has led numerous EU-funded projects, including ONTORULE and SeWAsIE, and contributed to international conferences as a program committee member and keynote speaker. His work bridges theory and practice, aiming to translate foundational results into real-world solutions. He is a prolific author with an h-index of 42 and has mentored researchers in areas like semantic web technologies and conceptual modeling. Key achievements include advancing ontology-driven data integration, developing tools like ICOM for conceptual modeling, and contributing to standards for semantic web languages. He is affiliated with the Computational Logic community and actively participates in international research networks such as CAIRNE. His research has been recognized through ANVUR evaluations ranking his department among Italy’s top computer science faculties.
Marco Maggini is a Full Professor in the Department of Information Engineering and Mathematics at the University of Siena, a position he has held since joining the university in 1996. His academic career spans over 25 years with foundational expertise in computer engineering and artificial intelligence, focusing on theoretical and applied machine learning research. His educational background includes: Laurea degree (cum laude) in Electronics Engineering from the University of Florence (1991) Ph.D. in Computer Engineering and Control Systems from the University of Florence (1995) Prof. Maggini's research encompasses machine learning, neural networks, kernel machines, and the integration of symbolic and sub-symbolic knowledge systems. He extends these foundations into practical applications including web mining, search engine technology, pattern recognition, natural language processing, and computer vision. This interdisciplinary approach bridges theoretical computer science with real-world implementation challenges across multiple domains. Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on multilingual NLP applications, particularly educational puzzle generation for low-resource languages (Italian, Arabic, Persian, Turkish) using LLMs. His work demonstrates consistent innovation in named entity recognition, commonsense reasoning evaluation, and cross-lingual adaptation techniques. Secondary research threads include medical imaging segmentation, molecular property prediction, and AI security vulnerabilities, reflecting his broad technical mastery across computer vision, bioinformatics, and adversarial machine learning. No specific scientific awards were mentioned in the provided documentation, though his editorial roles indicate peer recognition within the academic community. While student mentoring details are absent from the source material, his position as Full Professor and leadership of SAILab imply active graduate supervision. His extensive publication record (120+ papers) and editorial service suggest significant research grant involvement, though specific funding sources remain undocumented. He directs the Siena Artificial Intelligence Laboratory (SAILab), which serves as an interdisciplinary hub for advancing machine learning theory and applications. The lab's current projects emphasize educational technology, multilingual NLP systems, and the integration of symbolic reasoning with neural architectures, maintaining strong industry and international academic collaborations.
Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.
Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).
Elisa Bordin is an Associate Professor at the Department of Linguistics and Comparative Cultural Studies (DSLCC) at Ca' Foscari University of Venice. Her research focuses on postcolonial literature, African diaspora studies, and cultural hybridity in contemporary narratives. She is actively involved in academic governance as a member of the DSLCC Commission for Knowledge Valorisation. Her work critically examines themes of race, migration, and transnational identities through analyses of literature and cinema. She has published extensively on authors such as Taiye Selasi, C Pam Zhang, and John Fante, exploring topics ranging from Afropolitanism to multicultural representation in Western film genres. Research Interests: African American studies, diasporic literatures, critical race theory, cultural hybridity, and postcolonial film. Awards: No specific awards listed, though her scholarly contributions are recognized in academic circles. Grants/Advising: No explicit mention of grants or advisees in the provided texts. Her recent publications (2022-2024) emphasize the intersection of migration narratives, racial identity, and cultural representation in contemporary media. She has contributed chapters to edited volumes on transnationalism and conducted interviews with prominent authors like Ayesha Harruna Attah. Bordin teaches at Ca' Foscari and holds office hours primarily on Wednesdays. Her academic profile reflects a commitment to interdisciplinary research bridging literature, cinema, and socio-cultural critique.
