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Sara Vinco is an Associate Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy. She specializes in battery simulation, digital twins, and energy-efficient design automation for heterogeneous embedded systems, aligning with Industrial and Information Engineering (Area 0009) and ERC sectors including Computer Architecture and Machine Learning . Her research focuses on advancing cyber-physical systems through simulation frameworks like SystemC-AMS, enabling holistic modeling of analog, digital, and thermal domains. Key projects include data-driven digital twins for EV batteries and low-area digital circuits in industrial/medical applications, supported by commercial contracts such as C-based virtual prototyping. Her recent publications (2022-2023) emphasize machine learning for battery SOH/SOC estimation , energy monitoring in production lines , and multi-domain fault modeling . These works span journals like IEEE Transactions and conferences including DATE and ISLPED. Awarded the FFABR 2017 grant and IEEE FDL Best Paper Award 2011 , she also chairs editorial boards for IEEE Transactions on CAD and DATE Conference. She supervises PhD students Giovanni Pollo (Digital Circuits) and Khaled Alamin (EV Battery Twins), reflecting her leadership in smart systems design.

• Battery simulation
• Cyber physical system
• Design simulation
• +12 more

Matteo Nardello is a researcher affiliated with the Department of Industrial Engineering at the University of Trento. His work focuses on embedded systems, IoT, and energy harvesting technologies for sustainable applications. Current academic affiliation: Department of Industrial Engineering, University of Trento Research interests: IoT, embedded systems, energy harvesting, machine learning, cyber-physical systems Contact: matteo.nardello@unitn.it His research integrates hardware-software co-design for batteryless IoT systems, with applications in smart agriculture, industrial monitoring, and autonomous vehicles. Recent work explores deep learning at the edge, energy-efficient sensor networks, and microbial fuel cells for self-powered devices. Key article trends highlight a focus on sustainable power solutions, wireless sensor networks, and machine learning optimization for constrained environments. He contributes to courses on embedded systems, IoT, and AI-powered industrial applications at the University of Trento.

• Integrated Circuits
• Pervasive Computing
• Electronics
• +14 more

Marco Picone is an Associate Professor at the Department of Sciences and Methods for Engineering (DISMI) of the University of Modena and Reggio Emilia. He leads the Distributed and Pervasive Intelligence (DIPI) Group and holds a PhD in Information Technology from the University of Parma. His postdoctoral research at the University of Parma (2012-2015) and a visiting scholar position at the University of Cambridge (2011) further enriched his expertise. He is nationally qualified as an Associate Professor by MIUR (2020). Education: PhD in Information Technology, University of Parma (Italy) M.Sc. (cum Laude) in Computer Engineering, University of Parma Visiting Researcher, NetOS Group, University of Cambridge (UK) His research focuses on Distributed Systems , IoT , Edge Computing , and Digital Twins , emphasizing their applications in smart industries and cities. He has supervised postdocs (e.g., Matteo Martinelli) and PhD students (e.g., Enrico Rossini) on topics like Digital Twin Continuum and Edge-Cloud Systems. Teaching spans courses on Intelligent IoT , Distributed IoT Software Architectures , and Edge Computing , with a focus on lab-based learning and industry-relevant projects. He actively contributes to open-source frameworks like the White Label Digital Twin (WLDT) and collaborates on initiatives such as the Web of Digital Twins (WoDT). Research collaborations include projects on smart city data fusion, livestock waste management, and Industry 5.0 human-centric systems. His work bridges theoretical advancements with practical implementations in cyber-physical environments.

• Distributed Systems
• Internet of Things
• Edge Computing
• +3 more

Dr. Laurence T. Yang is a Professor at the School of Computer Science and Technology, Huazhong University of Science and Technology, China, and Department of Computer Science of St. Francis Xavier University, Canada. He maintains active research and professional service commitments across both institutions with significant contributions to computing disciplines. His research spans parallel and distributed systems, embedded platforms, ubiquitous/pervasive computing environments, sensor networks, supercomputing infrastructure, and scalable computing methodologies. These interests drive his extensive publication record and leadership in advancing computational theory and applications. Dr. Yang has received numerous accolades including: Honorable Mention, PROSE Awards for "Mobile Intelligence" (2010) Best Paper Award at IEEE AINA-06 (2006) Best Paper Nomination Distinguished Achievement Awards (2005, 2011) Canada Foundation for Innovation Award (2003) Multiple Best Paper Awards at international conferences His professional service includes chairing the IEEE Technical Committee of Scalable Computing (2008-2011), leading the IEEE Task Force on Ubiquitous Computing and Intelligence (2009-present), and serving on Compute Canada's National Resource Allocation Committee (2009-present). As editor-in-chief for multiple journals and author/editor of over 25 books, he has shaped scholarly discourse while delivering approximately 20 keynote addresses globally.

• parallel and distributed computing
• ubiquitous and pervasive computing
• embedded computing
• +3 more

Gian Pietro Picco is a Full Professor at the Department of Information Engineering and Computer Science (DISI) at the University of Trento, Italy. His research focuses on wireless networks, particularly ultra-wideband (UWB) technology, wireless sensor networks, and cyber-physical systems. He teaches courses including Distributed Systems, Low-power wireless networking for the Internet of Things, and Programming 2. Professor Picco's research interests span several interconnected domains in pervasive computing and networking: Ultra-wideband (UWB) technology for precise localization and communication Wireless sensor networks and Internet of Things (IoT) systems Cyber-physical systems and networked control Energy-efficient networking protocols Distributed systems and middleware Software engineering approaches for networked embedded systems His recent publications demonstrate a strong focus on ultra-wideband technology applications, particularly in localization, ranging, and concurrent transmissions. His work bridges theoretical foundations with practical implementations, often addressing real-world challenges in human-robot interaction, contact tracing, and infrastructure monitoring. A notable trend is the increasing application of UWB technology for precise positioning in complex environments, with significant contributions to understanding and mitigating human occlusion effects on ranging accuracy. Professor Picco has received numerous prestigious awards for his research contributions: Best Paper Award at IPSN'23 for "Network On or Off? Instant Global Binary Decisions over UWB with Flick" Best Paper Award at IPIN 2019 for "TALLA: Large-scale TDoA Localization with Ultra-wideband Radios" Best Paper Award at EWSN 2018 for "Concurrent Ranging in Ultra-wideband Radios" Best Paper Award at IPSN 2015 for "Geo-referenced Proximity Detection of Wildlife" Best Paper Award at IPSN 2011 for "Wireless Sensor Networks for Adaptive Lighting in Road Tunnels" Best Paper Award at IPSN 2009 for "Monitoring Heritage Buildings with Wireless Sensor Networks" Mark Weiser Best Paper Award at PerCom 2012 Professor Picco actively advises numerous PhD and Master's students, with several of his advisees becoming prominent researchers in wireless networking. His laboratory has secured significant funding for research projects in wireless sensor networks, IoT systems, and cyber-physical systems. His work has practical applications in heritage building monitoring, wildlife tracking, road tunnel lighting systems, and pandemic contact tracing. His research group maintains the Cloves large-scale ultra-wideband testbed and has developed several middleware systems for wireless sensor networks, including Lime and TeenyLIME. The group collaborates extensively with international research institutions and has made significant contributions to standardization efforts in IoT networking protocols.

• Building Automation
• Pervasive Computing
• Software Engineering
• +12 more

Laura Emilia Maria Ricci is a Full Professor at the University of Pisa's Department of Computer Science, leading the Pisa Distributed Ledger Laboratory (Pisa DLT Lab). Her research focuses on blockchain technology, layer-2 solutions, cryptographic techniques, and self-sovereign identity frameworks. She coordinates the National PhD program in Blockchain and Distributed Ledger Technologies and leads the PRIN research project 'AWESOME' (2023-2025). Ricci serves as an associate editor for the ACM Distributed Ledger Technologies: Research and Practice journal and the Springer Nature SN Computer Science section on blockchain innovations. Her research emphasizes blockchain scalability, transaction analysis, and social network dynamics. Recent work includes studies on NFT architectures, post-quantum cryptography in Ethereum, and query authentication protocols. She co-organized the 7th IEEE International Conference on Blockchain and Cryptocurrencies (2025) and actively participates in global blockchain initiatives. Ricci has been awarded Best Paper Awards for her contributions to decentralized cloud scheduling, hybrid architectures for online games, and distributed virtual environments. She advises numerous PhD students and oversees grants like the H2020 'HELIOS' project. Ricci's academic roles include teaching blockchain, peer-to-peer systems, and web scraping at the University of Pisa. Her lab collaborates on projects such as the AQuSDIT grant (2024-2025) and the Ethereum Foundation's 'Cross Chain Authenticated Queries.' She also chairs conferences like IEEE Blockchain and co-edits special issues on blockchain-based pervasive systems and social media analysis.

• Blockchain Technology
• Layer-2 Solutions for Blockchain
• Cryptographic Techniques
• +3 more

Marcello Pietri is a Researcher (td art. 24 c. 3 lett. A) and Contract Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia. His work focuses on Information Processing Systems, with expertise in IoT, Edge Computing, and Digital Twins. He teaches courses like 'Sistemi Informativi' (Information Systems) for the Engineering Management program, emphasizing database design, SQL, and web application development with Python. His research explores advanced topics including Digital Twin integration in Industry 5.0, Fluid Computing in IoT ecosystems, and Smart City data fusion using 5G MEC architectures. He collaborates with institutions like the DIPI Lab (Distributed and Pervasive Intelligence Group), contributing to projects on telecom security, energy forecasting, and human-centric manufacturing systems. Recent publications highlight innovations in operator digital twins for workplace well-being, distributed data mesh models for IoT-edge-cloud systems, and adaptive monitoring algorithms for large-scale cloud environments. His work bridges theoretical advancements with practical implementations, addressing challenges in scalability, real-time data processing, and interdisciplinary collaboration.

• Information Processing Systems
• Internet of Things (IoT)
• Edge Computing
• +4 more

Antonio Corradi is a Full Professor of Computer Networks and Infrastructures supporting Cloud and Big Data at the University of Bologna's School of Engineering, within the Department of Computer Science - Science and Engineering. His roles include President of the regional CLUSTER RER for service innovation, President of the Alma Mater FAM Foundation, and Director of the UNIBO High Studies Center in Buenos Aires. He previously served as Director of the DISI department (2018–2021) and International Delegate for Latin America (2014–2018). His research focuses on distributed systems, middleware for pervasive computing, cloud solutions, mobile systems, smart cities, Industry 4.0/5.0, and 5G communication standards. Education: Laurea cum laude in Electrical Engineering (University of Bologna, 1979) and a Master's in Computer Engineering from Cornell University (1981, supported by a Fulbright-Hayes grant). He joined the University of Bologna as a Researcher in 1983 and became Full Professor in 2000. Research interests span distributed/parallel systems, middleware for mobile agent systems, cloud computing, smart city monitoring, and Industry 4.0 protocols. He emphasizes QoS-aware solutions, edge computing, and IoT integration. His work includes designing frameworks for big geospatial data and novel architectures for serverless and fog computing environments. Selected scientific awards include the 1980 'Cavalieri del Lavoro' prize for his thesis. He actively contributes to institutional duties, including the CCIB (Computer Services Centre of the Engineering School) and CINI Bologna University Section (Italian Interuniversity Consortium). In advising and grants: He coordinates PhD programs and has led projects funded by MIUR, CNR, and European initiatives. Notable collaborations include industry grants with Jakala, OTConsulting, ENAV-Sicta, and the Zefiro Consortium. His projects address challenges in energy efficiency, smart manufacturing, and healthcare management during crises. Labs/Teams: Developed platforms like SOMA and REDMAN middleware. Involved in initiatives such as ParticipAct (mobile crowdsensing), COLOMBO (vehicular traffic monitoring), and the Audit4Cloud platform for cloud performance auditing.

• Distributed Systems
• Computer Networks
• Middleware
• +13 more

Franco ZAMBONELLI is a Full Professor in the Department of Engineering Sciences and Methods at the University of Modena and Reggio Emilia. He holds positions in both the Reggio Emilia and Modena campuses, offering courses such as Software Engineering and Distributed Artificial Intelligence. His research focuses on IoT, pervasive computing, multiagent systems, and self-organization in distributed systems, with applications in smart cities, healthcare, and mobility. He leads projects like FLUIDWARE (PRIN 2017) and CONNECARE (H2020), exploring adaptive IoT systems and integrated healthcare solutions. ZAMBONELLI is an IEEE Fellow, ACM Distinguished Scientist, and member of the Academia Europaea. His work bridges theory and practice, emphasizing software engineering methodologies for IoT and agent-based systems. Education: Not explicitly detailed in provided texts. Research Grants: FLUIDWARE (2019-2022), CONNECARE (2016-2019). His research interests include causal discovery in pervasive environments, reinforcement learning for cybersecurity, and digital twin technologies. He contributes to editorial boards of journals like ACM Transactions on Autonomous and Adaptive Systems and IEEE Technology and Society Magazine. His teaching spans software engineering, distributed AI, and IoT-oriented methodologies. The Agents and Pervasive Computing Lab (agentgroup.unimore.it) is a focal point for his experimental work. Professional memberships include IEEE, ACM, and the Italian Association for Artificial Intelligence. Recent achievements include successful final reviews for CONNECARE and advancements in fluidware programming paradigms.

• Pervasive Computing
• IoT (Internet of Things)
• Multiagent Systems
• +7 more

Patrizia Scandurra is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. Her academic appointment in Computer Science (01/B1) spans from 2022 to 2033. She previously held roles as a researcher at the University of Bergamo (2009-2017) and postdoctoral fellow at the University of Milan (2006-2008). She earned her PhD in Computer Science (2006) and Bachelor's degree (2002) from the University of Catania. Research Focus : Software architectures and formal methods for modeling, validation, and verification of software-intensive systems. Specializations : Runtime analysis of self-adaptive, autonomous, and uncertain systems including IoT-Edge-Cloud applications, embedded systems, and system-on-chip. Collaborations : STMicroelectronics, Atego, Bialetti, and ENEA. Conference Involvement : Program/organizing committees for ICSE, ASE, ISSRE, ICSA, ECSA, SEAMS@ICSE, ABZ, SA-TTA@SAC, FAACS@ECSA. Research Projects : Model-driven development for robotics, adaptive architectures for pervasive systems, big data in smart cities, and digital twins for medical systems. Notable Contributions : Development of the ASMETA formal method community tools and frameworks for rigorous system design. She has published over 100 peer-reviewed works in international journals and conferences.

• Software Engineering
• Formal Methods
• Software Architectures
• +7 more

Marco MAMEI is a Full Professor at the Department of Engineering Sciences and Methods (DISMI) of the University of Modena and Reggio Emilia. His research focuses on digital twins, pervasive computing, and smart city technologies. He leads projects like NOUS (European cloud services) and MODENA AUTOMOTIVE SMART AREA, emphasizing Industry 5.0 and human-centric manufacturing. MAMEI teaches courses on Data Science, Pervasive Computing, and Cloud Services in Management and Engineering programs. His work bridges IoT, edge computing, and AI to solve challenges in energy systems, urban mobility, and disaster management. Roles: Full Professor, DISMI Director Affiliations: NOUS Project Lead, MODENA AUTOMOTIVE SMART AREA Research spans: IoT/Edge/Cloud Continuum Digital Twin Entanglement Metrics (ODTE) AI-Driven Telecom Security Smart Grid Optimization Publications (2025): 8+ papers on digital twin applications, accessibility theory, energy forecasting, and pandemic modeling. Recent work emphasizes fluid computing architectures and federated learning in decentralized systems. Teaching includes: Data Science & Management Pervasive Computing Programming Fundamentals Student reception: Mondays 14-17.

• Data Science
• Pervasive Computing
• Cloud Computing
• +7 more

Davide Bacciu is a Full Professor of Machine Learning at the University of Pisa, where he leads the Pervasive Artificial Intelligence Laboratory (PAILab) and coordinates the EIC-Pathfinder EMERGE project. He is also Director of AI Research at Aptus.AI and founder of ContinualIST and QuantaBrain startups. His academic roles include Vice President of AIxIA (Italian Association for Artificial Intelligence) and former Senior Editor of IEEE Transactions on Neural Networks and Learning Systems. He holds a PhD in Computer Science from IMT Lucca and is affiliated with the Department of Computer Science at the University of Pisa. His research focuses on machine learning fundamentals, graph neural networks, continual learning, and applications in robotics and healthcare. Key projects include the EMERGE initiative exploring collective awareness in AI systems and QuantaBrain’s diagnostic tools for autism spectrum disorders. Bacciu’s work emphasizes interdisciplinary collaboration, integrating AI with cyber-physical systems and societal impact. His contributions span foundational theory (e.g., causal abstractions, graph structure learning) and applied domains (e.g., autonomous systems, medical AI). He has organized workshops on AI for Space exploration and Geometric Deep Learning, showcasing his commitment to advancing AI frontiers. Education: PhD in Computer Science (IMT Lucca), MSc & BSc from University of Pisa. Labs/Teams: PAILab, EMERGE project, QuantaBrain startup. Grants/Projects: EIC Pathfinder EMERGE, TEACHING_H2020, AI for Space initiatives. His recent publications address challenges in dynamic graph learning, continual learning, and causal discovery. Bacciu advocates for a national AI strategy in Italy, stressing long-term vision and ethical AI governance aligned with EU regulations like the AI Act.

• Machine Learning
• Graph Neural Networks
• Continual Learning
• +5 more

Antonio Carta is an Assistant Professor in the Department of Computer Science at the University of Pisa. His primary research focuses on Continual Learning (CL) with deep neural networks, particularly addressing challenges like catastrophic forgetting and knowledge consolidation in online settings. He leads the Computational Intelligence and Machine Learning (CIML) group and contributes to the Pervasive AI Lab (PAILab) . As the lead maintainer of the Avalanche library, he develops end-to-end tools for deep continual learning. His work spans applications in computer vision, NLP, and time series analysis. Research emphasizes distributed CL, efficient knowledge transfer, and replay-free methods. Teaching includes courses on Continual Learning, Collective Machine Intelligence, and Intelligent Systems at the graduate level. Publications highlight adaptive normalization, temporal ensembles, and domain-based Bayesian approaches in CL.

• Continual Learning
• Deep Neural Networks
• Machine Learning
• +4 more

Kasim Sinan Yildirim is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, where he conducts research at the intersection of embedded systems, Internet of Things (IoT), and wireless communication technologies. His work focuses on developing innovative hardware and software solutions for resource-constrained and energy-limited environments. His research interests include: Hardware and software design for batteryless and intermittently powered embedded systems Energy harvesting and transient computing Wireless sensor networks and self-organizing networks Backscatter and visible light communication Edge learning and inference Distributed algorithms and real-time computing The absence of published articles in the provided text prevents analysis of publication trends. However, his research direction emphasizes sustainable, low-power computing paradigms essential for next-generation IoT deployments. There are no listed scientific awards in the provided information. Dr. Yildirim advises students and contributes to academic training, though specific advisees are not listed. There is no mention of external grants or funded projects in the provided text. He is involved in research related to advanced embedded and cyber-physical systems, particularly focusing on novel computing models for batteryless devices and sustainable IoT infrastructures.

• Embedded Systems
• Internet of Things
• Cyber-Physical Systems
• +17 more

Laura Carnevali is an Associate Professor of Computer Science at the Department of Information Engineering, University of Florence, where she leads research in formal methods and performance evaluation as a member of the Software Technologies Lab. She teaches Software Engineering for Embedded Systems, Quantitative Evaluation of Stochastic Models, and Foundations of Computer Programming at the School of Engineering. Her research focuses on formal methods for real-time software development and performance evaluation of non-Markovian models, with significant contributions to the ORIS Tool for quantitative system analysis. Key areas include: Stochastic modeling of critical infrastructure Formal verification of real-time systems Reliability engineering methodologies Performance evaluation of cyber-physical systems Her publications show strong emphasis on applied formal methods, with recent work focusing on workflow analysis, infrastructure reliability, and transportation systems modeling. Research consistently integrates theoretical frameworks with practical applications in engineering domains. Awards include: Best Paper Award at ICPE 2021 She actively contributes to academic service as program committee member for leading conferences including FORMATS, QEST, and EPEW, and serves as reviewer for IEEE Transactions on Software Engineering, Reliability, and other prestigious journals.

• Formal Methods
• Real-Time Systems
• Performance Evaluation
• +4 more