Maurizio Ramanzin is a Full Professor at the University of Padova , affiliated with the School of Animal Science and Department of Agronomy, Animals, Food and Natural Resources (DAFNAE) . His research focuses on Agricultural Sustainability , Environmental Impact Assessment , and Precision Livestock Farming . Academic Field : AGR/19 Email : maurizio.ramanzin@unipd.it Address : Agripolis - Viale dell'università, 16 - Legnaro (Padova) – ITALY His work explores the interactions between livestock systems and ecosystem services in mountainous regions, with emphasis on: Grazing Management and biodiversity conservation Life Cycle Assessment (LCA) of dairy and beef systems Climate Change Adaptation in Alpine ungulates Animal Welfare in small-scale farms Technological Tools (GPS, NIRS) for monitoring grazing behavior Key trends in his recent publications include: Quantifying environmental drivers of wolf predation on livestock Developing low-cost biologging systems for dairy cows Analyzing social-ecological trade-offs in mountain agriculture Assessing microbial dynamics in alpine soils
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
Guido Masera is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he has been actively involved in teaching and research for over two decades. He serves as a Member of the Board of Directors, Member of the GEDI Observatory for Gender Equality, Diversity and Inclusion, and Member of the Permanent University Observatory for monitoring the academic supply chain. His research interests span across channel decoders, circuits for communications, cryptography, deep learning, digital integrated circuits, field programmable gate arrays (FPGA), and hardware design. His work focuses on VLSI architectures for image and video coding, digital architectures for error correcting codes, application specific approximate computing, VLSI architectures for machine learning, digital architectures for bio-inspired processing, digital architectures for post-quantum cryptography, bio-inspired electronics for robotics and biomedical applications, RISC-V extensions and hardware accelerators, and circuit architectures for efficient machine learning and artificial intelligence. His recent publications (2025) demonstrate a strong focus on RISC-V architecture, particularly in the context of cryptographic implementations, hardware security, and post-quantum cryptography. His research group VLSILAB is actively engaged in cutting-edge research in hardware security, efficient processor design, and specialized computing architectures. Among his notable recognitions are the Premio Francesco Carassa awarded by the Telecommunications and Information Technologies Group Association (gtti) in 2010, and his recognition as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) since 2007. He also serves as an Associate Editor for several prestigious journals including ELECTRONICS (2019-present), IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS (2015-2019), and IET CIRCUITS, DEVICES & SYSTEMS (2013-2016). Professor Masera has advised numerous PhD students working on advanced topics in VLSI design, post-quantum cryptography, hardware accelerators, and machine learning implementations. His current research projects include ISOLDE (2023-2026) and TRISTAN (2022-2025), both EU-funded projects focused on RISC-V technology and domain-specific ecosystems. He leads the VLSILAB research group at the Department of Electronics and Telecommunications, which focuses on cutting-edge research in VLSI architectures, hardware security, and specialized computing systems. The group collaborates with industry partners and participates in major European research initiatives.
Luigi Bruno is an Associate Professor of Machine Design at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria. He has held this position since 2014, following 12 years as an Assistant Professor at the same institution and Visiting Professorships at IIT Gandhinagar (2012), University of Alabama at Birmingham (2013-2017), and Free University of Bozen-Bolzano (2021). 1999 : Master's in Mechanical Engineering, University of Calabria (110/110 cum laude) 2003 : PhD in Mechanical Engineering, University of Pisa His research interests span: Experimental Mechanics : Pioneering speckle interferometry for micro-displacement measurement and residual stress analysis. Materials Science : Elastic characterization of anisotropic materials, biomedical applications of soft substrates, and 3D-printed composites. Biomedical Engineering : Mechanical behavior of biological tissues, ocular biomechanics, and dental implant material testing. Recent research trends focus on: Integrating artificial muscles into rehabilitation devices Advancing full-field optical measurement via microCT/DVC Optimizing 3D printed polymer adhesion for industrial components Exploring neuronal biomechanics on soft surfaces Scientific contributions include: CS2007A00010 patent for dual-focus speckle interferometers Deputy Editor of Optics and Lasers in Engineering (2019-present) Guest Editor for special issues on optical methods in experimental mechanics and nanobiotechnology Academic leadership extends to coordinating Mechanical Engineering committees (2021-present), serving on editorial boards, and organizing international conferences like AIAS National Conference (2018). He has secured multiple MIUR research grants and industry collaborations with Alfagomma, 3DNA, and Ferrovie della Calabria. His laboratory, Mechanics of Materials and Structures , supports both research and teaching activities with advanced optical measurement systems and computational tools for mechanical design.
Diana Gratiela Berbecaru is an External Collaborator and External Lecturer at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, where she contributes to teaching and research in cybersecurity and digital identity. She is affiliated with the TORSEC Security Group and actively participates in EU-funded research projects such as Q-FENCE, focusing on quantum-resistant cryptography. She teaches core courses including Security and Privacy for Digital Identity Frameworks and Information Systems Security , and has been recognized with the Italian national scientific habilitation as Associate Professor in 2025, affirming her academic standing. Full Name: Diana Gratiela Berbecaru University: Politecnico di Torino Department: Department of Control and Computer Science (DAUIN) Academic Rank: Associate Professor (habilitated) Teaching Status: Part-time External Lecturer Email: diana.berbecaru@polito.it Her research focuses on cybersecurity, identity management, and trusted computing, with specific interests in authentication, authorization, data privacy, network security, and trusted computing in distributed and IoT environments. She investigates practical implementations of digital identity systems using the eIDAS infrastructure, certificate validation, TLS security, and post-quantum cryptography. Her work bridges theoretical security models with real-world deployment challenges. Her recent publications (2022–2025) reflect a strong focus on TLS security, X.509 certificate analysis, anomaly detection using AI, remote attestation for IoT, and post-quantum migration strategies. These works are published in high-impact venues such as IEEE Access, IEEE ISCC, and ARES, indicating active and influential contributions to the cybersecurity research community. The research trend shows a consistent emphasis on practical tools and frameworks for enhancing trust and security in digital systems. Scientific Awards and Recognition: Italian National Scientific Habilitation as Associate Professor (Abilitazione Scientifica Nazionale, II fascia), 2025 She serves as an Associate Editor for IEEE Transactions on Network and Service Management and IEEE Access , and as a Guest Editor for Electronics and Computer Networks . She chairs and co-chairs international workshops such as TrustAICyberSec and IMTrustSec, and is a frequent member of program committees for major conferences including ARES, IDC, and ISCC. These roles demonstrate her active engagement in academic leadership and knowledge dissemination. Labs and Research Groups: TORSEC - Security Group (DAUIN): Core research group focusing on cybersecurity, trusted systems, and digital identity.
Federico Silvestro is a Full Professor at the University of Genoa , affiliated with the Naval, Electrical, Electronic and Telecommunications Engineering Department . His academic roles include being a Course Coordinator, Department Council Member, and Deputy Director of DITEN. His research focuses on Power systems stability and control Cybersecurity in energy networks Electric propulsion for marine applications Optimal energy storage and microgrid design Integration of renewable energy in maritime contexts Recent publications highlight trends in data-driven power system analysis , DC microgrid modeling , cybersecurity for virtual power plants , and advanced energy management strategies for maritime and port systems. Email: federico.silvestro@unige.it He leads the ENET-RT Lab , focusing on real-time power systems simulation and co-simulation platforms for marine and grid applications.
Marco Ghislieri is an Assistant Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy. He is a member of the Interdepartmental Center PolitoBIOMed Lab and teaches in the Biomedical Engineering program, including courses like Neuroengineering and Design of Programmable Biomedical Devices . His research spans Artificial Intelligence, Biomedical Signal Processing, Neuroscience, and Rehabilitation Engineering . PhD in Bioengineering and Medical-Surgical Sciences (2017-2021) at Politecnico di Torino Thesis: Muscle Synergy Assessment during Cyclic and Non-Cyclic Movements His research focuses on muscle synergy analysis in Parkinson’s Disease (PD) patients post- Deep Brain Stimulation (DBS) , AI-driven gait analysis for fall prevention, and wearable sensor applications for stress-cognitive decline monitoring. He leads the S-CoDe and OMNIA-PARK projects, and contributes to PRIN as a team member. Recent publications highlight advancements in machine learning for intraoperative DBS targeting , statistical gait analysis , and neurorehabilitation tools . He serves as Associate Editor for Scientific Reports and Applied Bionics and Biomechanics , and Guest Editor for Frontiers in Neural Circuits . Awards include the Carlo J. De Luca Award (2022) , GNB Doctoral Award (2022) , and the Best Poster Award at M. Grattarola Summer School (2022) . He supervises Fabrizio Sciscenti (PhD candidate) and collaborates on neuroengineering and biomedical device design courses. His work addresses Goal 3 (Good Health) and Goal 4 (Quality Education) of the UN SDGs.
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.
Alfio Grillo is a Full Professor at the Department of Mathematical Sciences (DISMA) of Politecnico di Torino, with research interests in biomechanics, continuum mechanics, and mathematical physics. His expertise spans classical mechanics and multiscale modeling of biological tissues. Research Focus: Grillo's work integrates analytical mechanics with nonholonomic constraints, fractional calculus applications, and multiscale modeling of growth/remodeling phenomena in biological systems. Recent articles emphasize poroelasticity, viscoelastic composites, and bi-phasic material behavior. Scientific Contributions: Editorial roles in leading journals since 2014 Member of INdAM-GNFM since 2009 Recipient of National Scientific Qualification in 2017 €128,609 PRIN grant for multiscale biological modeling Academic Leadership: Supervises PhD students in Civil Engineering, Mathematics, and Mathematical Engineering. Teaches advanced courses in Differential Varieties, Variational Methods, and Porous Media Mechanics.
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.
Jost-Diedrich Graf Von Hardenberg is a Full Professor in the Department of Environmental, Land and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. He serves as the Energy and Climate Change Area Coordinator and is a Scientific Advisor of the HPC-AI Advisory Council. His research focuses on climate science and geophysical fluid dynamics, with significant contributions to understanding climate change impacts and Earth system modeling. Professor Von Hardenberg's research interests span multiple areas of climate science, including climate dynamics, geophysical fluid mechanics, hydrological cycle analysis, numerical climate modeling, and precipitation downscaling. His work particularly emphasizes climate tipping points and extremes, Rayleigh-Bénard convection in geophysical contexts, high-resolution Earth-system climate modeling, and stochastic approaches to precipitation downscaling. His research integrates theoretical, computational, and observational approaches to address fundamental questions about climate system behavior and change. His recent publications demonstrate a strong focus on Atlantic Meridional Overturning Circulation (AMOC) dynamics, climate extremes in Alpine regions, urban climate effects, and interdisciplinary applications of climate science to ecological and conservation challenges. His work bridges fundamental climate dynamics with practical applications for climate adaptation and environmental management. Among his notable recognitions are the Research in Paris award from the Maire de Paris (2009) and Fellowships at the London School of Economics and Political Science (2001-2002, 2004-2006). He has participated in numerous research networks including the European Geosciences Union section 'Nonlinear Processes in Geophysics' (2004-2012), the EC-Earth Consortium (2012-present), and COST Action ES0805 TERRABITES 'The terrestrial biosphere in the earth system' (2010-2014). Professor Von Hardenberg actively supervises PhD students including Marianna Albanese, Maria Clara Corda, Sara Filippini, and Jacopo Grassi, among others. He leads multiple significant research projects such as ROTurb (Resolving Ocean Macroscale Turbulence), LocClima (Impact of LOCal conditions on Italian microCLIMAtes), CRAWL (Carbon Release in A Warming cLimate), and CliMOC (Climate Impacts of the Atlantic Meridional Overturning Circulation), with funding from EU, national programs, and commercial contracts. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, where he contributes expertise in climate data analysis and modeling. His collaborative work extends to multiple institutions through non-commercial agreements with the National Research Council and various international research consortia focused on climate system understanding.
Andrea Garzelli is a Full Professor at the University of Siena's Department of Information Engineering and Mathematical Sciences. His research focuses on remote sensing image processing, particularly in optical and SAR sensor technologies, image fusion, and spatial resolution enhancement. He holds teaching roles in 'Fundamentals of Signal Processing and Telecommunications' and 'Statistical Signal Processing.' He earned his Ph.D. in Computer Science and Telecommunication Engineering from the University of Florence. Notably, he was recognized as a World's Top 2% Scientist by Stanford University for 2019–2023 and his career-long contributions. He served as President of the University of Siena's Quality Assurance Committee (2016–2021) and currently coordinates the graduate program in Computer and Information Engineering. Research interests include satellite data analysis (e.g., Sentinel-2, PRISMA), hypersharpening techniques, and environmental monitoring. His work bridges theoretical advancements (e.g., pansharpening algorithms) and practical applications like urban land classification and vegetation index enhancement. Recent articles emphasize reproducibility, meta-analysis, and synthetic data generation through GANs. Awards: World's Top 2% Scientists (2019–2023 & career). Grants/Advising: Supervises remote sensing theses; no specific grants mentioned. Labs/Teams: Leading research in the department's remote sensing and signal processing groups.
Giovanni Mento is an Associate Professor at the Department of General Psychology, University of Padova. His research focuses on cognitive neuroscience, developmental psychology, and clinical neurology, with a particular emphasis on neural mechanisms underlying cognitive control, emotional processing, and neurodevelopmental disorders. He employs advanced neuroimaging techniques like high-density EEG to investigate topics such as temporal prediction, decision-making in children, and the impact of preterm birth on brain development. His work integrates interdisciplinary approaches, combining machine learning with electrophysiological data analysis to address challenges in epilepsy forecasting and predictive brain activity. Key research areas include implicit learning, motivational contexts influencing cognition, and the application of EEG to study socio-emotional and behavioral disorders in clinical populations. Recent studies explore the effects of yoga-mindfulness interventions on cognitive control in children, dynamic brain states in preschoolers, and methodological rigor in EEG-based machine learning models. His contributions span both theoretical frameworks (e.g., re-examining top-down control models) and applied clinical research (e.g., neonatal intensive care practices). Mento’s articles highlight trends in understanding developmental trajectories, predictive neural mechanisms, and translational applications of neuroscientific findings to real-world contexts like education and healthcare.
Maria Chiara Fiorentino is a Research Fellow at the Department of Information Engineering, Polytechnic University of Marche, Italy. Her work focuses on applying deep learning techniques to medical image analysis, particularly in ultrasound, MRI, and CT imaging. Education Master’s in Biomedical Engineering, Università Politecnica delle Marche (Honors) Ph.D. in Information Engineering, Università Politecnica delle Marche (Laude) Research Interests: Dr. Fiorentino specializes in deep learning for medical imaging, with applications in diagnosing neurodegenerative diseases like Parkinson’s, cardiovascular conditions, and musculoskeletal disorders. Her recent work includes federated learning for fetal ultrasound analysis, AI-driven vocal fold pose estimation, and domain adaptation in MRI segmentation. Scientific Awards: Paolo Marziali Thesis Prize for her Master’s research Gruppo Nazionale di Bioingegneria award for her Ph.D. thesis Publications: Dr. Fiorentino’s work spans fetal brain image synthesis, zero-shot learning robustness, and machine learning for catheterization management and stenosis detection.
