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Carlo Ricciardi is a Full Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, where he serves as Coordinator of basic subjects for the 2nd year of Engineering and is a member of the Interdepartmental Center CWC - CleanWaterCenter@PoliTo. His research focuses on nanomechanical sensing and memristive nanodevices, with applications spanning biomedical engineering, environmental monitoring, and brain-inspired computing systems. His research interests center on the intersection of nanotechnology and biological systems, particularly in developing bio-inspired nanodevices for sensing applications. Ricciardi's work bridges fundamental nanoscience with practical implementations in memristive devices , nanomechanical sensors , and brain-inspired computing architectures . His research group explores how nanoscale phenomena can be harnessed for biomedical applications, environmental monitoring, and next-generation computing paradigms that mimic neural processing. The recent publications reveal a strong trend toward neuromorphic computing using nanowire networks, with significant work on self-organizing systems that exhibit brain-like computational properties. His research spans multiple disciplines including nanotechnology, materials science, electronics, and biophysics, with a particular emphasis on creating sustainable and efficient computing systems inspired by biological principles. The work often combines experimental fabrication with theoretical modeling to understand complex phenomena at the nanoscale. Young Scientist Award (European Materials Research Society, 2002) Keynote Paper Finalist, Biosensors 2010 (2010) Premio Giovedì Scienza (2012) National Scientific Qualification as Associate Professor Sector 02/B1 (MIUR, 2013) National Scientific Qualification - Second Band - Sector 02/B3 (MIUR, 2013) Ricciardi actively mentors doctoral students and serves on multiple PhD program committees across Physics and Engineering disciplines. He has secured substantial research funding through competitive national and international projects including the EU-funded GreenChips-EDU (2023-2027), NEURONE (2023-2025), and MEMQuD (2021-2024) projects. His collaborations span academia and industry, with partnerships including the University of California Berkeley and various European research institutions. As Principal Investigator of the NaMeS research group, Ricciardi leads investigations into two interconnected research domains: nanomechanical sensing and memristive nanodevices. The group operates specialized laboratories including the CHILAB Laboratory in Chivasso and the Nanoscience Vibrometric Lab, focusing on developing innovative sensor technologies and neuromorphic computing architectures that draw inspiration from biological systems.

• Nanomechanical sensing
• Memristive nanodevices
• Biosensors
• +6 more

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

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

Egidio Falotico is a Tenure Track Assistant Professor (RTD-B) at the BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy. He leads the BRAin Inspired Robotics (BRAIR) Lab and holds roles such as Principal Investigator (PI) for the PROBOSCIS project and co-leader of Sub-Project 10 (Neurorobotics) in the Human Brain Project (HBP). His research focuses on brain-inspired motor control, soft robotics, and neurorobotics, integrating computational neuroscience with robotic systems. Education: Dual PhD in Biorobotics (Scuola Superiore Sant’Anna) and Cognitive Science (University Pierre et Marie Curie). Master’s in Computer Science (University of Pisa). Research interests include control mechanisms for soft robots using AI, bio-inspired motor control, and neuroscientific principles applied to robotics. He has contributed to projects like HBP, where he developed the Neurorobotics Platform, and PROBOSCIS, aiming to create elephant-trunk-inspired robots. Teaching includes leading PhD courses on Brain-Inspired Motor Control and Robotics at the University of Pisa. He has supervised EU-funded students and managed interdisciplinary teams in neurorobotics and soft robotics. Key projects involve HBP’s Neurorobotics Platform, soft robot control (e.g., PROBOSCIS), and collaborations in sensorized systems and adaptive learning algorithms. His work bridges neuroscience, AI, and robotics to advance soft robotic systems and bio-inspired models.

• Robotics
• Biorobotics
• Computational Neuroscience
• +4 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

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

Giovanna Citti is a Full Professor in the Department of Mathematics at the University of Bologna. Her research focuses on sub-Riemannian geometry, mathematical analysis, and neurogeometry, with a particular emphasis on modeling the functional architecture of the visual and motor cortices. She develops geometric frameworks to understand neural processing in the brain, including models of visual perception and motor control. Her work integrates concepts from differential geometry, partial differential equations (PDEs), and Lie group theory to analyze sub-Riemannian structures. She explores regularity properties of subelliptic PDEs and applies these to biological systems, such as the cortical organization of the visual cortex and motor pathways. Recent efforts include developing brain-inspired neural networks and studying neurogeometric models of stereo vision and 3D perception. Key contributions include sub-Riemannian models of perceptual completion, cortical-based optimal transport frameworks, and analysis of geometric optical illusions. Her research bridges pure mathematics and neuroscience, addressing challenges in both fields through innovative interdisciplinary approaches.

• Sub-Riemannian Geometry
• Mathematical Analysis
• Neurogeometry
• +3 more

Massimo Melucci serves as Associate Professor of Computer Science at the University of Padua's Department of Information Engineering, maintaining an active research and teaching profile with office location in Building DEI/G, Room 312, Padova, Italy. His instructional responsibilities include undergraduate Information Retrieval and Databases courses, alongside graduate-level Computing Methods for Data Science instruction, complemented by freely available lecture notes on information retrieval fundamentals. His research program centers on two pioneering domains: Quantum-inspired Information Retrieval , where he develops mathematical frameworks applying quantum probability to model contextual relevance and interference effects in search systems, and Algorithmic Fairness , investigating trade-offs between ranking effectiveness and equitable outcomes. These threads converge in his exploration of fairness-effectiveness optimization through eigensystems and variation modeling, while his interdisciplinary work extends into diving medicine neurophysiology , analyzing EEG-based brain connectivity disruptions in professional divers under hyperbaric conditions. Recent publication analysis (2020-2025) reveals three dominant trajectories: quantum-inspired neural architectures for multimodal sentiment analysis, rigorous fairness-effectiveness quantification in ranking algorithms, and biomedical applications of signal processing in extreme environments. He actively fosters academic collaboration through initiatives like the BIRDS workshop series and CIRCLE conference, which bridge information science, retrieval, and data science communities. His work demonstrates consistent innovation in applying non-classical probability models to information access challenges while maintaining strong connections to real-world applications in both search technology and human safety.

• Information Retrieval
• Data Science
• Quantum-inspired Information Retrieval
• +2 more

Gianvito Urgese is an Associate Professor at the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) at Politecnico di Torino, where he is also a member of the EDA research group and the SmartData@PoliTO Big Data and Data Science Laboratory. His academic and research activities are deeply integrated into the Department of Control and Computer Engineering (DAUIN), reflecting his interdisciplinary focus on computer engineering and data science. His research spans artificial intelligence, bioinformatics, neuromorphic computing, edge computing, embedded systems, and Industry 4.0. He investigates optimized task-specific algorithms, designs heterogeneous software-hardware architectures for bioinformatics acceleration, and develops computational paradigms for neuromorphic platforms. His work also extends to digital lifecycle management in Industry 4.0, aligning with Sustainable Development Goals 9, 11, and 12. His recent publications reveal a strong trend in neuromorphic computing and quantum-inspired optimization, with contributions to benchmarking frameworks (NeuroBench), neuron-based encoding tools (WiN-GUI), and quantum annealing methods. These works are published in high-impact journals such as Nature Communications , IEEE Transactions on Emerging Topics in Computing , and Science Translational Medicine , indicating a multidisciplinary and high-impact research profile. Urgese is actively involved in supervising PhD students and teaching graduate-level courses such as Neuromorphic Computing and Engineering, Applied AI and Machine Learning, and System-on-Chip Architecture. He serves on doctoral colleges and course committees, demonstrating leadership in academic governance. Scientific and Research Leadership: Principal Investigator (Scientific Manager) in multiple commercial research projects on data analytics, fog computing, and firmware design (2019–2025). Supervision of PhD research on neuromorphic systems, bioinformatics algorithms, and AIoT solutions. Active contributor to European-funded initiatives in neuromorphic and Industry 4.0 domains. He collaborates with multidisciplinary teams, including researchers at the Candiolo Cancer Institute and participants in the Telluride Neuromorphic Cognition Engineering workshop, highlighting the collaborative and applied nature of his work.

• Artificial Intelligence
• Bioinformatics
• Neuromorphic Computing
• +12 more

Gigliola Vaglini is Full Professor of Computer Engineering at the University of Pisa's Department of Information Engineering. She teaches Software Systems Engineering and Databases, with research focusing on formal specification and verification of concurrent/distributed systems. Her work integrates model checking methodologies with machine learning techniques for industrial anomaly detection and mobile security applications. She has participated in multiple research projects funded by the Italian Ministry of University and Research, National Research Council, and European Community. Research Focus: Vaglini's work bridges theoretical computer science and practical applications, developing verification frameworks for complex systems while creating AI solutions for real-world problems. Her current investigations span swarm intelligence coordination, structural monitoring via digital twins, and multimodal deep learning architectures. Recent publications demonstrate cross-disciplinary approaches combining formal methods with machine learning, particularly in environmental monitoring, structural engineering, and neural architecture design. This reflects a consistent pattern of translating theoretical computer science concepts into applied technological solutions.

• Distributed Systems Verification
• Model Checking
• Machine Learning Applications
• +2 more

Roberta Bardini is a Fixed-term Assistant Professor at Politecnico di Torino, Department of Control and Computer Science (DAUIN), within the College of Computer, Film, and Mechatronics Engineering. She holds the scientific disciplinary sector IINF-05/A - Information Processing Systems (Area 0009 - Industrial and Information Engineering) and is actively involved in teaching across multiple engineering programs including Computer Engineering, Biomedical Engineering, and Aerospace Engineering. Her research focuses on applied artificial intelligence, bioinformatics, and computational biology , with particular emphasis on systems biology applications. Her work bridges computer science with biological and medical domains, addressing challenges in cancer modeling, neuronal systems, and biomedical applications. She applies computational approaches to understand complex biological phenomena and develop innovative solutions for healthcare and biotechnology. Her recent publications (2024-2025) reveal a strong focus on computational biology tools, AI applications in tumor resistance modeling, neuronal concept transformation, and security for neuromorphic systems. These works demonstrate interdisciplinary research spanning bioinformatics, computational neuroscience, and AI-driven biomedical solutions with practical applications in cancer research and biomanufacturing. Dr. Bardini serves as a supervisor for PhD students Alessio Caviglia and Filippo Marostica in the Artificial Intelligence program (40th cycle, 2024-present). She is actively involved in the BESOS_RP research project (2024-2027), an innovative tool for analyzing welfare and sustainability for Piedmontese cattle breeders, funded through regional research grants. Additionally, she has contributed to the Horizon Europe NEUROPULS Project. She holds two significant patents: a computerized method for generating culture protocols for biomanufacturing, and a method for computer simulation of the ontogeny of biological systems (with optional culture protocol generation), developed with colleagues Alfredo Benso, Stefano Di Carlo, Gianfranco Michele, and Maria Politano. These patents reflect her expertise in computational biology and bio-manufacturing applications.

• Applied artificial intelligence
• Bioinformatics
• Computational biology
• +4 more

Francesco Maria Puglisi serves as Associate Professor of Electronics at the University of Modena and Reggio Emilia since 2018, leading research in semiconductor device physics with emphasis on emerging memory technologies and neuromorphic systems. His expertise spans characterization, physics-based modeling, and reliability analysis of next-generation electronic devices. His research portfolio prominently features: Resistive Random-Access Memory (RRAM) for non-volatile storage and neuromorphic computing Random Telegraph Noise (RTN) mechanisms in FinFETs and memristors Compact modeling frameworks for device simulation Reliability assessment of 2D materials and III-V semiconductor devices Memory-in-logic architectures enabling non-Von Neumann computation Hardware security applications leveraging device physics Analysis of his 2023-2025 publications reveals a pronounced shift toward in-memory computing solutions, particularly SIMPLY architecture implementations using RRAM/STT-MRAM, alongside deep investigations into ferroelectric device dynamics and RTN-based cryptographic primitives. His work consistently bridges fundamental device physics with practical circuit design for energy-efficient computing. Notable scientific recognitions include: IEEE ICICDT 2013 Best Paper Award for Resistive Memories modeling IEEE ESSDERC 2016 Best Paper Award for RTN in FinFETs IEEE ESSDERC 2019 Best Paper Award for advanced memory characterization Dr. Puglisi has additionally received multiple national awards for academic excellence and research impact. While his advisory activities and grant portfolio aren't detailed in available sources, his extensive publication record demonstrates significant contributions to semiconductor device engineering through both theoretical modeling and experimental validation.

• Resistive Memories
• Neuromorphic Computing
• Device Reliability
• +7 more

Danilo Demarchi is Full Professor at the Polytechnic University of Turin's Department of Electronics and Telecommunications (DET). He directs the eLiONS Lab and coordinates PoliTO's Italian Institute of Technology Microelectronics Group. As pioneer in wearable plant sensors and AgriFood electronics, he bridges microelectronics with agriculture and biomedical applications. IEEE Senior Member Founder & Editor-in-Chief: IEEE Transactions on AgriFood Electronics General Chair: IEEE BioCAS (2017), IEEE CAFE (2023) Research spans smart systems for: Precision agriculture (IoT, plant health monitoring) Biomedical devices (implantables, wearables) Low-cost electronics Molecular electronics His 350+ publications focus on bio-inspired architectures integrating microsystems with physiological applications, while leading EU and PNRR projects like FERNS and ATHOS. Scientific leadership includes: Coordinating 5 EU projects Founding 2 IEEE conferences Editorial roles in 4 IEEE journals Current PhD students explore topics from plant bioimpedance to pilot workload monitoring, supported by his 5 granted patents and extensive industry collaborations.

• Electrical and Electronic Engineering
• Microelectronics
• Nanoelectronics
• +7 more

Patrizia Fattori is a Full Professor of Physiology at the University of Bologna's Department of Biomedical and Neuromotor Sciences. She leads research in systems neuroscience focusing on visuomotor processing in posterior parietal cortex. Her lab investigates neural mechanisms of sensory-motor integration using neurophysiological and brain stimulation techniques. Research focuses on: Neurophysiology of reaching and grasping actions Neural coding in parietal cortex during motor planning Role of attention in visuomotor transformations Virtual reality applications in neuroscience Professor Fattori coordinates major research initiatives including the European FET PROACTIVE project MAIA (Multifunctional AI system) and national PRIN projects on biological motion perception. Her work contributes to understanding parietal cortex functions and developing neuro-inspired AI systems. Recent publications examine neural computations for reaching corrections, microsaccade dynamics during attention, and convolutional neural network applications in decoding neural activity. She serves on editorial boards for neuroscience journals and promotes international research collaborations.

• Neurophysiology
• Visuomotor Processing
• Posterior Parietal Cortex
• +3 more

Prof. Gian Luca Foresti is Full Professor of Computer Science at the University of Udine and Director of the Master in Intelligence and Emerging Technologies. His research spans artificial intelligence, computer vision, and cybersecurity with applications in medical imaging, industrial inspection, and aerial surveillance. Research develops novel neural architectures including capsule-enhanced models, physics-informed networks, and bio-inspired systems. Recent innovations address underwater imaging, federated medical AI, anomaly detection, and document analysis for cultural heritage preservation. Publications demonstrate leadership in multi-disciplinary applications, particularly medical imaging (MS segmentation, brain anomaly detection) and industrial automation (defect detection, quality control). Recent work shows emphasis on efficient models for edge deployment and security applications. Directs research initiatives in intelligence technologies, including drone swarm coordination for surveillance tasks and cybersecurity frameworks for containerized environments. Current projects span healthcare diagnostics, environmental monitoring, and heritage preservation.

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +2 more