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.
Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains
Federica Burini is a Full Professor of Geography at the Department of Foreign Languages, Literatures and Cultures of the University of Bergamo . She serves as Scientific Coordinator of the Imago Mundi Lab, member of the Center for Territorial Studies, and Scientific Director of OrobieLab. Her academic career spans participatory processes, collaborative mapping, and sustainable territorial regeneration. Full Professor of Geography Imago Mundi Lab Coordinator Center for Territorial Studies member OrobieLab Scientific Director Research Focus : Federica specializes in participatory geography through collaborative mapping techniques for environmental governance in both rural and urban contexts. Her work emphasizes sustainable development in Sub-Saharan Africa and European mountainous regions, with particular attention to landscape valorization via participatory processes and responsible tourism. Key projects include digital co-mapping initiatives for community engagement and territorial regeneration. Participatory mapping tools Sustainable tourism frameworks Mountainous area development Rural community empowerment Digital geospatial applications Landscape perception studies Publications : Recent works explore digital collaborative mapping tools (2024), industrial heritage interpretation for slow tourism (2024), and water resource-driven community regeneration (2024). Earlier contributions examine pandemic impacts on tourism (2020) and participatory cartography methodologies (2016). Her research consistently bridges geographical theory with practical territorial governance solutions.
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.
Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.
Pier Cesare Rivoltella is a Full Professor of Educational Technology at the University of Bologna's Department of the Arts. He holds leadership roles in academic organizations such as the Italian Society of Pedagogy (SIREM) and the Accademia Nazionale dei Lincei. His academic career spans over three decades, including roles as Associate Professor (2000–2005) and Full Professor (2005–2023) at the Catholic University of the Sacred Heart before joining Bologna in 2023. He earned a Philosophy degree from the Catholic University of the Sacred Heart and a PhD in Social Communication Sciences from the Pontifical Salesian University. His research focuses on media literacy, education technology, and pedagogical innovation, with notable contributions to neurodidactics and AI in education. Rivoltella founded the CREMIT research center (2006–2023) and co-leads editorial initiatives like REM – Research on Education and Media . He has received prestigious awards, including the Italian Pedagogy Prize (2014) and the REN Award for Educational Neuroscience (2021). His teaching includes courses on Media and Technologies for Teaching at the University of Bologna. He actively collaborates with institutions worldwide, including Brazilian universities through CNPq-funded projects.
Andrea Maurino is a Full Professor at the University of Milano-Bicocca and leads the Insid&s LAB. His research focuses on data quality, knowledge graphs, machine learning, and their applications in healthcare, finance, urban planning, and organizational analysis. He explores cutting-edge techniques like Large Language Models (LLMs) for decision support systems and semantic annotation of tabular data. Key research interests include improving data quality frameworks for large RDF datasets, developing enterprise knowledge graphs for organizational insights, and applying AI to social media analysis and hate speech detection. His work bridges theoretical advancements with real-world applications such as smart city mobility prediction and nutritional strategies for healthy aging. Notable contributions include scalable tools like ABSTAT-HD for knowledge graph profiling and the 3d-clost mobility prediction model. Maurino’s interdisciplinary approach integrates data science with fields like psychology (ICD-11 decision support) and environmental science (ESG activity detection in financial texts). His lab collaborates on projects like Food NET, combining nutrition science with social network analysis. While no formal awards are listed here, his prolific publication record reflects sustained innovation in data-driven methodologies.
Tushar Sharma is an Assistant Professor at the Faculty of Computer Science, Dalhousie University, Canada. His research focuses on software code quality , refactoring , sustainable AI , and machine learning for software engineering (ML4SE) . He holds a PhD in Software Engineering from Athens University of Economics and Business (2019) and an MS in Computer Science from IIT-Madras (India). Current affiliations: Dalhousie University, SMART Lab, IEEE Senior Member Past experience: Siemens Research (2019-2021), Siemens Corporate Technology (2008-2015) Research interests span code quality assessment, technical debt management, and sustainable AI. He founded Designite , a widely used software design quality assessment tool, and contributed to the book Refactoring for Software Design Smells . Recent work examines energy-efficient language models for code, reproducibility issues in configuration scripts, and human-guided code smell detection. Publication trends reveal expertise in code smell detection, refactoring techniques, and green AI. His articles address topics like commit message generation, model quantization, and empirical studies on code quality. Collaborative efforts include tools like DesigniteJava 2.0 and frameworks for attention mechanisms in code language models. Scientific recognition: Dean's Research Excellence Award (2025), Best Artifact Award (SCAM 2023) Grants: Mitacs Accelerate grants ($225K, $15K, $30K), NSERC Discovery Grant ($154M CFREF climate action project), DRA computing resources ($51K) He actively contributes to academic service as PC Co-chair (ICSE 2024), editorial board member (JSS), and organizer of workshops on technical debt. His media coverage highlights environmental impacts of AI and software quality challenges.
Giorgio Satta is a Full Professor at the Department of Information Engineering , University of Padua, Italy. He received his Ph.D. in Computer Science from the University of Padua in 1990. His career includes research positions at Fondazione Bruno Kessler (Trento) and the University of Pennsylvania (IRCS). Research Focus : His work centers on computational linguistics and formal language theory , with emphasis on: Parsing algorithms (CCG, TAG, LCFRS) Computational complexity of grammar formalisms Probabilistic language modeling Dependency parsing and synchronization techniques Professional Service : He chaired the European Chapter of the ACL (2009-10), served on editorial boards for Computational Linguistics , Transactions of the ACL , and co-chaired ACL-2001/IWPT-2001. Teaching : Current courses include Automata, Languages, and Computation and Natural Language Processing (2024-25).
Paolo Trunfio is a Professor of Computer Engineering at the University of Calabria, Italy, and co-founder of DtoK Lab S.r.l., an academic spin-off focused on data analysis and distributed systems. He holds a Ph.D. and is affiliated with the DIMES Department, specializing in big data, cloud computing, and high-performance computing (HPC). His research emphasizes scalable data analysis frameworks, edge-cloud continuum solutions, and machine learning applications for social media and disaster monitoring. Trunfio serves as an Associate Editor for ACM Computing Surveys and Journal of Big Data , and is on the editorial boards of several journals including Future Generation Computer Systems . He has authored four influential books, including Programming Big Data Applications (2024) and Data Analysis in the Cloud (2015). His work spans distributed systems, IoT-based smart objects, and exascale computing. Notable projects include the EU-funded eFlows4HPC and ASPIDE initiatives, which focus on HPC workflows and exascale programming models. Trunfio’s publications (over 200 papers) address topics like social media analytics, energy-efficient P2P networks, and parallel data mining. He leads research in urgent computing for disaster response, edge-cloud integration for urban mobility, and AI-driven data analysis. His contributions to cloud frameworks (e.g., JS4Cloud, ParSoDA) and HPC libraries (e.g., DCEx) highlight his expertise in bridging theory and practice in distributed computing ecosystems.
Prof. Tomaso Fontanini is a researcher at the Department of Engineering and Architecture, University of Parma. His academic contributions span multiple disciplines, including computer science, artificial intelligence, and computer vision. 2025/2026: Deep Learning and Generative Models (Master's in Computer Engineering) 2024/2025: Processing Systems (Bachelor's in Prevention Techniques) 2023/2024: Processing Systems (Bachelor's in Prevention Techniques) 2022/2023: Processing Systems (Bachelor's in Prevention Techniques) Research Focus: His work primarily explores generative models, image synthesis, and style transfer with a strong emphasis on semantic control and attention mechanisms. Recent research has advanced state space models for efficient style transfer (Mamba-ST), semantic image synthesis via class-adaptive cross-attention, and diffusion model acceleration through U-shape architectures. Scientific Contributions: Publications include breakthroughs in controllable face synthesis, mask-based generative modeling, and video anomaly detection. His work bridges theoretical advancements in neural architectures with practical applications in remote sensing and educational technology. 2025: FLAV (audio-video generation), Swin2-MoSE (remote sensing) 2024: MARS (text-based person search), MCGM (mask conditioning) 2023: FrankenMask (face part editing), Student attendance systems
Roberto Giorgi is an Associate Professor of Computer Engineering at the Department of Information Engineering, University of Siena, Italy. He has held this position since October 1, 2006, following his tenure as an Assistant Professor since March 15, 1999. His educational background includes a Ph.D. in Computer Engineering from the University of Pisa (1999) with a thesis on coherence protocols for shared-memory multiprocessors, and an Electronic Engineering degree (1995) with a thesis on trace-driven performance evaluation of multiprocessors. Giorgi's primary research focuses on Computer Architecture , particularly on multiprocessor/multicore issues including processor design, coherence protocols, programmability, and energy efficiency. His work spans both theoretical and practical aspects of computer architecture, with emphasis on real-world implementations and educational tools. He has coordinated significant EU-funded projects including AXIOM (2014-2018) on Smart Cyber-Physical Systems and TERAFLUX (2009-2014) on Many-Cores. His recent publications (2022-2025) demonstrate a strong progression toward practical applications of computer architecture research, with particular emphasis on RISC-V architecture, FPGA-based acceleration, dataflow computing models (especially DF-Threads), and graph processing. Many of his papers address educational tools for computer architecture education, real-time object detection on embedded platforms, and novel execution paradigms for edge computing and HPC. IEEE Senior Member ACM Lifetime Member Coordinator of EU-funded AXIOM project (2014-2018) on Smart Cyber-Physical Systems Coordinator of EU-funded TERAFLUX project (2009-2014) on Many-Cores Giorgi has been actively involved in securing research funding and building collaborations, particularly in high-performance computer architecture research with emphasis on scalable architectures and embedded systems. He leads the Computer Architecture Lab (ROOM 223) at the University of Siena, which was established in 2007, and has been instrumental in developing practical implementations of architectural concepts including the AXIOM platform for cyber-physical systems.
Alessio Malizia is a Professor of User Experience Design at the University of Hertfordshire, UK, and concurrently holds a full Professorship at the Computer Science Department of the University of Pisa, Italy. His research focuses on Human-Centered Systems, Human-Centered AI, and Design Fictions, emphasizing ethical AI, user participation, and the integration of visual programming languages. He has held roles at institutions including Sapienza University of Rome, IBM, Silicon Graphics, and Xerox PARC, where he researched neural networks and gestural interfaces. His work bridges academia and industry, addressing challenges in healthcare, agriculture, and education. Malizia’s career includes visiting research at Xerox PARC, associate professorship at the University Carlos III of Madrid, and senior lecturer roles at Brunel University London. He is an ACM Distinguished Speaker and actively promotes democratizing AI through tools like BlocklyBias and PyFlowML. His research spans touchless interfaces, collaborative design methodologies, and AI explainability. Key contributions include frameworks for socio-technical process modeling in agriculture, tools for bias detection in AI data, and visual languages fostering user participation in ML systems. His work on telemedicine and healthcare AI emphasizes co-design and trusted AI systems. Recent studies explore end-user development for smart environments, digital agriculture, and computational thinking education through tools like TAPASPlay. Awards: ACM Distinguished Speaker Key Interests: Human-AI Interaction, UX Design, AI Ethics, IoT Ecosystems, and Co-Creation Methodologies Notable Projects: Figmant, ModeLLer, and the Chatbot Usability Scale validation His grants and collaborations focus on improving AI transparency, user-centered design processes, and participatory innovation in technology adoption across sectors.
Tania Cerquitelli is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where she leads research in data science, concept-drift management, and inclusive AI technologies. She is a member of SmartData@PoliTO, the GEDI Observatory for Gender Equality, and serves in leadership roles related to social affairs and community policies at the university level. She also acts as a scientific advisor for the partnership with Accenture. Her research interests span Data Science , Concept-Drift Management , Database Systems , Conversational Data Science , and Industry 4.0 . She applies AI and machine learning to industrial, societal, and ethical challenges, particularly in promoting inclusive communication and gender equality in research. The most recent publications highlight her work in explainable AI, concept drift detection, multimodal diagnostics, and AI for social good. Her research integrates machine learning, natural language processing, and computer vision to address real-world problems in manufacturing, healthcare, agriculture, and education. She is an Associate Editor for several prestigious journals including Expert Systems with Applications , Computer Networks , Future Generation Computer Systems , and Knowledge and Information Systems . She has served on the program committees of major conferences such as ECML PKDD, EDBT/ICDT, and ACM KDD, and has been a reviewer and selection committee member for ETH Zurich and EMPA. She actively supervises PhD students and teaches a wide range of courses including Data Science and Database Technologies, Business Intelligence for Big Data, and Gender and Diversity in Research. She is involved in multiple national and international research projects such as E-MIMIC, WEBFARE, and EnABLES, focusing on inclusive AI, smart data, and industrial applications. Her lab affiliations include the DBDM - Database and Data Mining Group (DAUIN) and the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory , where she contributes to advancing data science methodologies and their societal impact.
Matteo Mario Pietro Motterlini is a Full Professor of Philosophy of Science at Università Vita-Salute San Raffaele in Milan, where he is affiliated with the Faculty of Philosophy. He is the director of the Center for Research in Experimental and Applied Epistemology (CRESA) and the Behavior Change Lab, and collaborates with the Cognitive Neuroscience Center and Division of Neuroscience. He holds teaching responsibilities in Cognitive Economics and Neuroeconomics, and Behavior Change, and serves on the university's academic committee. Università degli Studi di Milano – Philosophy London School of Economics – Economics Carnegie Mellon University – Cognitive Science His research lies at the intersection of philosophy, behavioral economics, and cognitive neuroscience, focusing on human rationality, decision-making processes, emotions, regret, and social learning, particularly in economic and financial contexts. He investigates how behavioral science can inform public policy and improve organizational practices. His work integrates experimental methods with neuroimaging to uncover the neurobiological foundations of judgment and choice. The recent publications highlight a strong trend in applying behavioral and cognitive sciences to societal challenges such as vaccine hesitancy, disinformation, charitable giving, and policy design. His work combines empirical rigor with philosophical depth, exploring topics like the epistemology of nudges, truth perception, and the role of expert endorsement. The integration of neuroscience, psychology, and economics is evident across his research output. Chief Behavioral Officer, E.ON Italia Spa Chief Behavioral Officer, Gruppo San Donato Scientific Advisor, MilanLab (AC Milan) Scientific Advisor, MarketPsych LLC Advisor for Behavioral Finance, Fidelity (Growth, Income & Stability project) Advisor for Social and Behavioral Sciences, Presidency of the Council of Ministers (Italy) He has received no explicitly mentioned scientific awards in the provided text. However, his advisory roles in high-impact public and private institutions reflect recognition of his expertise. His books are international bestsellers, translated into multiple languages, indicating broad scholarly and public influence. Motterlini has been actively involved in public engagement through collaborations with Corriere della Sera, Il Sole 24 Ore, and Il Foglio. He has delivered keynote lectures and participated in public festivals and media appearances, including on Sky TG24. He has advised on financial education (EDUFIN) and participated in events on longevity risk, health, and sustainability. His research is supported by interdisciplinary collaborations and applied projects with industry partners. He leads two major research units: the Center for Research in Experimental and Applied Epistemology (CRESA) and the Behavior Change Lab (also referred to as the E.ON Customer Behavior Lab), which focus on biometric and neuroscientific analysis of behavior. These labs serve as hubs for experimental research in decision-making, nudging, and behavioral interventions in health, finance, and sustainability.
