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Patrik Pluchino is an Assistant Professor at the Department of Psychology, University of Padua, affiliated with the Human Inspired Technology Research Centre. His research focuses on cognitive processes in human-computer interaction, psychophysiological measures of attention, and IoT applications in workplace and living environments. He investigates attention allocation, multimedia learning, and ethical decision-making through eye-tracking and neurophysiological methods. Research interests include cognitive workload assessment using EEG/ERP, IoT systems for safety and sustainability, and VR-based training for disaster response. He leads projects like SAFE GYMS and DOMHO, developing smart solutions for elderly care and workplace safety. His work bridges psychology, technology, and design to enhance human-centered systems in Industry 5.0 contexts. Pluchino collaborates on EU-funded initiatives addressing aging workforce needs and accessible technologies for disabled users. His publications span 20+ years, emphasizing interdisciplinary approaches to human factors, educational technology, and assistive systems. Key contributions include studies on attentional blink, implicit learning mechanisms, and ethical behavior through attention dynamics.

• Work & Organisational Psychology
• Human-Computer Interaction
• Eye Tracking
• +6 more

Giulia Orrù is an Assistant Professor of Computer Engineering at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering. She holds an M.S. and Ph.D. in Electronic Engineering and Computer Science from the same institution. Her research focuses on biometric recognition, presentation attack detection, deepfake forensics, and cybersecurity. She is a core member of the Pattern Recognition and Applications Laboratory (PRA lab), contributing to projects like BullyBuster (anti-bullying detection systems) and LivDet competitions (fingerprint liveness detection). Dr. Orrù has authored numerous publications in top-tier conferences and journals, with a strong emphasis on advancing secure authentication systems and combating adversarial attacks in biometrics. She actively serves as a referee for pattern recognition and cybersecurity venues. Teaching activities include courses such as Technologies for Information Security and Artificial Intelligence and Security . Research interests span multimodal biometrics, 3D face reconstruction for surveillance, AI-driven anti-bullying systems, and deepfake detection algorithms. Her work bridges theoretical advancements (e.g., diffusion models for anomaly detection) with real-world applications like forensic recognition and crowd analysis. Notable projects include the Synthetic Data for Face Recognition (SdFR) initiative and contributions to the Face Deepfake Detection Challenge. Dr. Orrù's lab explores cutting-edge techniques in EEG-based personal recognition and vulnerability analysis of medical AI systems. She maintains active participation in international research networks and has developed open-source tools for evaluating biometric system resilience against spoofing attacks.

• Biometric Recognition
• Presentation Attack Detection
• Deepfake Forensics
• +5 more

Silvestro Micera is a Professor specializing in Bioelectronics and Neural Engineering. His research focuses on neural interfaces, neurorehabilitation, and biomedical robotics. He explores applications of machine learning in healthcare and develops wearable robotic systems for mobility assistance. Notable projects include stroke recovery prediction using neural signals and soft wearable robots for shoulder movement support. His work bridges materials science with clinical applications through innovations like conductive hydrogel electrodes. Research interests span neural prosthetics, neuromodulation, and neuroethology in primate models. Recent studies address facial asymmetry classification in neurological disorders and vagal-cardiac neuromodulation. His interdisciplinary approach integrates robotics, materials science, and machine learning to advance neural engineering solutions. Publications highlight trends in neurorehabilitation technologies, implantable devices, and animal model studies. Ongoing work explores brain-to-body neural bypass systems using manifold-based control algorithms.

• Bioelectronics
• Neural Engineering
• Neurorehabilitation
• +4 more

Calogero Maria Oddo is an Associate Professor at Sant’Anna School of Advanced Studies, affiliated with the BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence. He leads the Neuro-Robotic Touch Laboratory, coordinating a team of 25+ researchers. His work bridges neuroscience and engineering, focusing on tactile sensing, neuroprosthetics, and biomedical robotics. He holds a national qualification as Full Professor of Bioengineering and serves in academic governance roles, including Vice-Coordinator of the BioRobotics PhD program and President of the University Committee for Equal Opportunities. His research has been featured in top journals like Nature Machine Intelligence and recognized by prestigious awards such as the Feltrinelli Prize under 40 (2023). Education BSc in Electronic Engineering (University of Pisa, 2005, 1st in cohort) MSc in Electronic Engineering (University of Pisa, 2007, Excellence Track) PhD in Innovative Technologies (Sant’Anna School of Advanced Studies, 2011) Graduate of Sant’Anna Honours College (2008, 2006) Research Interests His lab develops tactile sensors inspired by human neurophysiology, with applications in bionic prostheses, robotic surgery, and healthcare. Key areas include neuromorphic engineering, mechanotransduction, and sensory feedback systems. Collaborations span institutions like the National Research Council, University of Pisa, and international partners such as École Normale Supérieure. Grants & Awards Coordinator of €10M+ in research funding from EU, Italian ministries, and private foundations Contributions to technology transfer via RoboIT and the ARTES 4.0 Competence Center Labs & Teams Leads the Neuro-Robotic Touch Lab and collaborates with the N2Lab (National Research Council), focusing on clinical translation of tactile technologies.

• Bionic tactile sensing
• Neurophysiology of touch
• Artificial intelligence in tactile systems
• +5 more

Gianluigi Maria Riva is a Research Fellow at University College Dublin (UCD), affiliated with the School of Information and Communication Studies. He holds a Marie Curie PhD in Privacy, Ethics and New Technologies from UCD and is a non-residential Connection Science Fellow at the MIT Media Lab’s Human Dynamics group. His expertise spans data protection law, invasive technologies (e.g., IoT, BCI), and EU-US privacy comparisons, particularly in genetic and biometric profiling. Education: PhD in Privacy, Ethics, and New Technologies (UCD). Former Fulbright-Shuman Visiting Scholar at MIT Media Lab. Research focuses on dark patterns, ethical governance frameworks for emerging technologies, and privacy-by-design principles in Human-Computer Interaction (HCI). Collaborated with organizations like Telefonica Innovaciò Alpha on ethics governance and participated in EU projects such as H2020 TEAM-ITN (mental health tech) and REINITIALISE (digital health privacy). Awards: 2022 Best Innovator Award (Marie Curie Alumni Association). Leadership: Coordinates a law seminar at the University of Pavia, contributes to EU COST Actions (e.g., Privacy and Security, Researcher Mental Health), and leads editorial roles in Frontiers in Human Dynamics. Member of committees like the IEEE, AssoDPO’s AI Scientific Committee, and the I.R.C.C.S. Mondino Neurological Institute’s Board. Prior roles include Military Police Officer, Commercial Manager, litigation Attorney, and Legal/Data Protection consultant.

• Data Protection
• Privacy Law
• Technology Ethics
• +8 more

Vittorio Fra is a Fixed-term Assistant Professor at the Interuniversity Department of Regional and Urban Studies and Planning (DIST) at Politecnico di Torino, where he conducts research in artificial intelligence, neuromorphic computing, edge computing, and robotics. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and contributes to interdisciplinary research bridging engineering, nanotechnology, and smart urban systems. His research interests center on AI and neuromorphic computing for industrial and IoT applications , with strong emphasis on brain-inspired computing, memristive devices, and nanoscale technologies. His work spans from low-level hardware characterization to high-level algorithm design, integrating machine learning, bio-inspired computing, and scientific simulation. He actively explores neuromorphic solutions for real-world edge applications such as human activity recognition, smart traffic control, and assistive technologies like Braille readers. The trend across his recent publications (2022–2025) reveals a consistent focus on deploying spiking neural networks and neuromorphic architectures on commercial edge devices, optimizing neural execution, developing benchmarking tools (e.g., NeuroBench, WiN-GUI), and validating neuromorphic solutions on practical problems like Sudoku and the knapsack problem. His work bridges theoretical AI with applied engineering, targeting sustainability and innovation in infrastructure and urban communities. Scientific Awards: No scientific awards explicitly mentioned in the text. Advising and Grants: Vittorio Fra supervises Filippo Aisa , a PhD candidate in Electrical, Electronic, and Communications Engineering. He leads a commercially funded research project titled Supporto allo sviluppo di un smart digital water distributor monitoring system (2025–2026) , serving as the Scientific Responsible. His teaching roles include PhD instruction, course collaboration, and invited membership in academic councils across engineering and planning programs. Labs and Research Teams: He is a member of the PoliTO Interdepartmental Centre for Service Robotics (PIC4SeR) , a multidisciplinary research center focused on robotics for societal applications. His collaborations span multiple institutions and projects, involving teams working on neuromorphic ecosystems (e.g., Lava-Loihi), wireless sensor networks, and brain-inspired computing frameworks.

• Artificial Intelligence
• Neuromorphic Computing
• Brain-inspired Computing
• +13 more

Giacomo Vitali is a Ph.D. candidate in Computer and Systems Engineering at the Politecnico di Torino , Department of Control and Computer Science (DAUIN), while also serving as a Lecturer at the same institution. His research focuses on Quantum Computing , Machine Learning , and Parallel and Distributed Systems . Education: M.Sc. in Physics of Fundamental Interactions (2018) from the University of Pisa Research: Pioneering hybrid quantum-classical algorithms for industrial applications, including BBQ-mIS and DEN models for graph problems and quantum hardware optimization Teaching: Contributing to courses on Quantum Hardware Design and Quantum Computing at the M.Sc. level, as well as undergraduate courses in Computer Science

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +1 more

Febo Cincotti è Professore Ordinario di Bioingegneria (ING-INF/06) presso il Dipartimento di Ingegneria Informatica, Automatica e Gestionale "Antonio Ruberti" della Sapienza Università di Roma. Svolge attività di ricerca metodologica e applicata sul processamento di segnali neurofisiologici e sullo sviluppo di interfacce cervello-computer (BCI) per riabilitazione motoria e assistenza a pazienti con disabilità severe. Laurea in Ingegneria Elettronica (1998), Sapienza Università di Roma Dottorato in Biofisica (2003), Fondazione Santa Lucia La sua ricerca si concentra su: Metodi avanzati per il processamento di segnali EEG, EMG e HD-EEG Interfacce cervello-computer per recupero motorio post-ictus Analisi di coerenza cortico-muscolare e intermuscolare Applicazioni di teoria dei grafi per reti cerebrali Gli articoli recenti mostrano un focus su: Reabilitazione dell'arto superiore post-stroke Metodi per ridurre jitter nella classificazione P300 Caratterizzazione di oscillazioni cerebrali a bassa frequenza Applicazioni BCI per pazienti con disordini della coscienza Analisi di connettività cerebrale mediante teoria dei grafi Integrazione di feedback visivo e bioingegneristico nella riabilitazione robotica Attività di insegnamento: Metodi Avanzati di Analisi di Dati Biomedici (12 CFU) Elaborazione Dati e Segnali Biomedici II (3 CFU) Neuroengineering (3 CFU) Membro del Collegio dei Docenti per il Dottorato in Automatica, Bioingegneria e Ricerca Operativa E' coautore di 124 articoli su rivista internazionale (H-index 50 Scopus) e ha coordinato 5 progetti EU e 1 progetto nazionale. E' stato Associate Editor delle IEEE Transactions on Biomedical Engineering e relatore invitato in conferenze internazionali.

• Bioengineering
• Neuroengineering
• Processing Neurophysiological Signals
• +3 more

Mario G.C.A. Cimino is Associate Professor of Information Processing Systems at the University of Pisa, with joint affiliations at CNR's Institute for Informatics and Telematics and Institute of Information Science and Technologies. His research integrates artificial intelligence, information systems, and granular computing, with applications in explainable AI and process intelligence. Teaching responsibilities include Software Systems Engineering, Process Mining and Intelligence, and Advanced Programming. Research develops interpretable machine learning frameworks for applications ranging from motor imagery recognition to virtual reality mental health assessment. Recent publications emphasize explainability in AI systems through techniques like counterfactual analysis and prototype-based interpretation.

• Artificial intelligence
• Information systems
• Process mining
• +2 more

Angela Re is an Associate Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, specializing in computational biology and bioinformatics with applications spanning sustainable energy, healthcare, and environmental systems. Her research focuses on two primary domains: Data-driven biomolecular space representations through database development and network analysis tools Computational biology applied to prokaryotic/eukaryotic organisms across diverse ecosystems and industrial contexts Her work integrates bioinformatics, biophysics, and medical informatics to address UN Sustainable Development Goals including climate action (13), affordable clean energy (7), and good health (3). Recent publications (2024-2025) reveal strong thematic convergence in microbiome analysis, metabolic engineering, and protein function prediction. Key trends include machine learning applications for genomic data interpretation, sustainable chemical production using engineered microorganisms, and gut microbiota dynamics in neurodegenerative disease models. She actively mentors doctoral researchers and secures competitive funding: Supervised PhD students: Giulia Usai (2020-2024) and Luca Ricci (2019-2023) Current projects: PROT-mBIOMA-AD (Scientific Responsible, 2023-2025) on Alzheimer's gut microbiota, PNRR NEST Spoke 3 (2022-2025) for energy transition, and Solvay contract for battery membrane development Her research operates within the Institute of Fundamental Physics and Materials for Nanotechnology (DISAT), driving computational approaches to sustainable biotechnology challenges.

• Biochemistry
• Bio-energy with carbon capture and storage
• Bioinformatics
• +5 more

Yashar Deldjoo is an Assistant Professor specializing in artificial intelligence, machine learning, and their applications in healthcare, user modeling, and recommender systems. His research focuses on explainable AI, ethical AI practices, multimodal learning, and brain-computer interfaces. He has contributed to projects like WeBIUM (Wearable Devices and Brain-Computer Interfaces for User Modelling) and ARIEL (emotional support via BCI and LLMs). His work bridges technical advancements with societal impacts, addressing challenges in healthcare diagnostics (e.g., Alzheimer’s disease prediction), environmental sensing (real-time pollution-aware recommendations), and cybersecurity (data poisoning attacks on recommendation systems). He also explores fairness in large language models and the integration of EEG-based emotion recognition systems. Notable contributions include frameworks like BRAINEX (CNN model evaluation for brain age prediction), Ducho (multimodal feature extraction for recommendation systems), and KGUF (knowledge-aware graph-based recommenders). He chairs conferences like RecSys and contributes to industry-relevant standards for trustworthy AI systems. His research emphasizes interdisciplinary collaboration, combining neural networks, ethical considerations, and human-computer interaction. Current projects involve neurorehabilitation tools, quantum security for smart cities, and AI-driven usability testing.

• Artificial Intelligence
• Machine Learning
• Recommender Systems
• +7 more

Dr. Abramo Agosti is a Researcher in the Mathematical Analysis and Applications group at the University of Pavia. His work develops mathematical frameworks for biological and physical systems, specializing in tumor growth modeling, biomechanics, and computational neuroscience applications. He creates phase-field models using Cahn-Hilliard equations to simulate tumor evolution under mechanical constraints and microenvironmental interactions. His recent research establishes energy-variational solutions for viscoelastic fluids and analyzes large deformations in elastic materials. He co-develops the Deep Anatomical Federated Network (Dafne) for collaborative medical image segmentation. His glioblastoma models integrate radiological data to predict spatial progression patterns. Dr. Agosti's computational approaches bridge mathematical analysis with clinical applications, particularly in neuro-oncology where his models incorporate patient-specific imaging data to simulate brain tumor mechanics and growth dynamics.

• Mathematical Biology
• Partial Differential Equations
• Tumor Growth Modeling
• +4 more

Roberto Zamparelli is an Associate Professor at the University of Trento in both the Department of Psychology and Cognitive Science and the Center for Mind/Brain Sciences (CIMeC) . His research spans theoretical and computational linguistics with a focus on syntax-semantics interface phenomena. His research interests include formal semantics , distributional semantics , computational models of language , and linguistic education . He has supervised multiple PhD theses and contributed to interdisciplinary projects combining linguistics with cognitive science. The 15 most recent articles (2013-2024) demonstrate consistent focus on partitive structures , multimodal language models , semantic knowledge evaluation , and multilingualism effects . Key subfields include ellipsis mechanisms, cross-linguistic analysis, and neural network linguistic testing. Marie Curie Post-Doctoral Fellowship (1997-1999) British Academy 'Joint Activity Grant' (2000) Patent: Dispositivo didattico per l’apprendimento o l’esercizio nell’uso di strutture linguistiche (2016) Students supervised include Eva Vecchi , Rossella Varvara , and Sara Zanellini . His work integrates computational methods with theoretical linguistics , supported by grants like the PRIN REPLAI project (2023-25) and EU Atheme collaboration (2014-19).

• Theoretical Linguistics
• Formal Semantics
• Computational Linguistics
• +3 more

Daniela Iacoviello is an Associate Professor at Sapienza University of Rome, working in the Department of Computer, Control and Management Engineering (DIS). She has held teaching positions since 2002, including courses in Automatic Control for Clinical Engineering. Her career spans research roles at Georgia Tech's Broadband & Wireless Networking Laboratory and leadership in interdisciplinary research centers like CISB and CRAS. B.Sc. in Mathematics (1992), Sapienza University of Rome Postdoctoral studies in Identification and Optimal Control (2000-2001), DIS PhD in System Engineering (1998), DIS Her research focuses on optimal control applications in biomedical systems and epidemic modeling, with expertise in image analysis for materials science and signal processing for biological data. Her work combines theoretical control systems with real-world implementations in public health and materials diagnostics. Recent publications demonstrate trends in epidemic containment (HIV, arboviruses, SARS-CoV-2), nonlinear control systems for chemotherapy optimization, and computational imaging for material characterization. She explores cross-disciplinary applications from aerospace research to neurological disorders. She serves on editorial boards of journals like International Journal of Imaging and scientific committees of image analysis conferences. Her funded projects include ASI's SARFIRE and PRIN grants for neural network algorithms in biomedical imaging. Key laboratory affiliations: Center for Biomedical Models & Information Analysis (CISB) Sapienza Aerospace Research Center (CRAS) DIS research group in control theory

• Optimal Control
• Biomedical Systems
• Epidemiological Modeling
• +3 more

Letizia Bergamasco is a Ph.D. candidate in Computer and Control Engineering at Politecnico di Torino, currently in her 38th cycle (2022-2025). She is affiliated with the SMILIES research group (reSilient coMputer archItectures and LIfE Sciences) within the Department of Control and Computer Engineering (DAUIN), and collaborates with the LINKS Foundation. Bergamasco received her B.Sc. in Electronics Engineering (2018) and M.Sc. in ICT for Smart Societies (2020) with a Double Degree from Politecnico di Torino and Politecnico di Milano through the Alta Scuola Politecnica program. LINKS Foundation researcher since 2020 Focus on medical/industrial AI solutions Her research combines computer vision and AI for clinical applications, particularly in early dementia detection through facial expression analysis and pediatric pain assessment using camera-based vital parameter evaluation. Recent publications demonstrate her work in: Deep learning for cognitive impairment detection Digital twin architectures for energy optimization Neonatal pain assessment systems LLM applications in pediatric emergency diagnostics Current projects involve developing non-invasive biomarkers for dementia diagnosis and AI algorithms for infant monitoring systems. Bergamasco's work bridges computer engineering with healthcare applications, integrating multimodal data analysis and real-time processing systems.

• Deep Learning
• Computer Vision
• Artificial Intelligence in Healthcare
• +3 more