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Daniele Ielmini is a Professor at the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy, where he leads research in non-volatile memory technologies and neuromorphic computing. He received his Laurea (with merit) and Ph.D. in Nuclear Engineering from Politecnico di Milano in 1995 and 2000, respectively, and has held visiting positions at Intel Corporation (2006), Stanford University (2006), and the University of Illinois at Urbana-Champaign (2010). His research focuses on the modeling and characterization of non-volatile memories, including nanocrystal memory, charge trap memory, phase change memory (PCM), resistive switching memory (RRAM), and spin-transfer torque magnetic memory (STT-MRAM). He has co-edited the book 'Resistive switching – from fundamental redox-processes to device applications' and published over 300 papers with more than 10,000 citations and an H-index of 69 (Scopus, September 2023). Prof. Ielmini's recent publications demonstrate a strong trend toward in-memory computing and neuromorphic applications, with particular emphasis on closed-loop analog computing architectures, reservoir computing with 2D materials, and hardware security implementations using emerging memory technologies. His work bridges fundamental device physics with practical computing applications, especially for energy-efficient AI acceleration. Intel Outstanding Researcher Award (2013) ERC Consolidator Grant (2014) IEEE-EDS Paul Rappaport Award (2015) Fellow of the IEEE Prof. Ielmini leads multiple ERC-funded projects including SHANNON (Secure Hardware with Advanced Nonvolatile memories), NEURO2D (neuromorphic systems based on reservoir computing in MoS2), and ANIMATE (closed-loop in-memory computing). His research group includes post-doctoral researchers, PhD students, and M.Sc. students working on various aspects of emerging memory technologies and their applications. He serves as Associate Editor for IEEE Trans. Nanotechnology and Semiconductor Science and Technology (IOP), and has served in several Technical Subcommittees of international conferences including IEEE-IEDM, IEEE-IRPS, and IEEE-ISCAS. His laboratory at Politecnico di Milano is equipped with advanced semiconductor device testing equipment including probe-stations, semiconductor parameter analyzers, high-speed waveform generators, and other specialized instruments for nano-electronic research. The lab collaborates with major semiconductor companies including Micron Technology Inc. and STMicroelectronics, as well as participating in national and international research projects.

• Non-volatile memory technologies
• Resistive switching memory (RRAM)
• Phase change memory (PCM)
• +5 more

Fernando Corinto is a Research Fellow at the Department of Electronics and Telecommunications (DET) , Polytechnic University of Turin , and a member of the SmartData@PoliTO Big Data and Data Science Laboratory. He holds a European Doctorate in Electronics and Communications Engineering (2005) and was a Marie Curie Fellow (2004) at University College Dublin, focusing on cardiac fibrillation modeling and chaotic systems. Education : Laurea (2001) and Ph.D. (2005) in Electronics and Communications Engineering from Politecnico di Torino His research spans nonlinear dynamical systems , memristor devices , and complex network modeling , with over 50 publications. Key projects include RECOMMEND (2024–2027) and COSMO (2020–2024), where he served as Scientific Director . His recent work involves memristor-based neuromorphic systems and nonlinear circuit applications in biomedical and industrial contexts. He supervises PhD students Rosanna Cavazzana and Davide Rossetti and teaches Nonlinear Systems for Engineering (Mathematical Engineering) and Memristor-based Neuromorphic Systems (Electrical Engineering). His scientific contributions include the Flux-Charge Analysis Method and Bifurcations without Parameters in memristor circuits. He holds a national/international patent for skin ulcer classification algorithms and has led commercial research projects in biomedical and packaging systems.

• Artificial Neural Networks
• Chaotic Oscillators
• Circuit Analysis and Modeling
• +9 more

Federico Becattini is a Tenure-Track Assistant Professor at the Department of Information Engineering and Mathematics (DIISM), University of Siena, Italy. He is an active member of the Siena Artificial Intelligence Lab (SAILab), where he contributes to cutting-edge research in computer vision, deep learning, and artificial intelligence. His work spans multiple interdisciplinary domains, including autonomous driving, human behavior understanding, cultural heritage, neuromorphic vision, and fashion recommendation. His research interests center on memory-based neural networks , which he has applied in numerous publications at top-tier venues such as CVPR, ECCV, IEEE TPAMI, and ACM TOMM. He has also delivered tutorials on this topic at international conferences including ICIAP 2022 and ACM MM 2022, and taught a Ph.D. course at the University of Florence. His recent work is aligned with the Collectionless AI paradigm, which emphasizes continual learning and interaction with dynamic environments. The recent publications highlight a strong trend in human-centric AI , focusing on understanding people through multimodal analysis of face, body, and clothing, as well as generating 3D virtual avatars. There is also a clear emphasis on memory-augmented architectures for temporal reasoning, explainability, and adaptive learning. His editorial role as Associate Editor of the International Journal of Multimedia Information Retrieval further underscores his standing in the research community. Associate Editor, International Journal of Multimedia Information Retrieval (IJMIR) Organizer, Workshop on Facial and Body Expressions (ICPR2020) Co-organizer, T-CAP Workshop (ICIAP2021, ICPR2022) Co-organizer, MCFR Workshop (ACM MM 2022) Co-organizer, WCPA Workshop and Challenge (ECCV 2022) Federico Becattini actively advises students and researchers within SAILab, particularly in the context of Ph.D. theses and research projects related to Collectionless AI and memory-based models. While specific grants are not mentioned, his extensive publication record and leadership in workshops and editorial roles suggest involvement in funded research initiatives. He collaborates with both academic and international research communities, serving as a reviewer for top-tier conferences and journals. He is a core member of the SAILab research group, which is pioneering the Collectionless AI initiative—a framework for continual learning over time, interacting with humans and agents without relying on pre-built static datasets. This lab serves as a hub for innovation in adaptive and sustainable AI systems.

• Computer Vision
• Deep Learning
• Artificial Intelligence
• +7 more

Enrico Macii is a Full Professor at the Politecnico di Torino, affiliated with the Interuniversity Department of Regional and Urban Studies and Planning (DIST) and the Department of Control and Computer Engineering (DAUIN). He leads the Electronic Design Automation (EDA) research group and holds key roles as Scientific Advisor for the Politecnico-STMicroelectronics partnership and Scientific Contact for the European Chips Joint Undertaking. Research Interests: His work spans digital circuits and systems, energy efficiency, smart cities, Industry 4.0, and smart manufacturing. He focuses on embedded and cyber-physical systems, low-power design, neuromorphic computing, AIoT, and sustainable urban development. Recent Publications: His recent research demonstrates strong trends in edge AI, neuromorphic computing, and smart energy systems. Articles highlight innovations in low-power hardware acceleration, federated learning, physics-informed AI, and digital twin applications for urban and industrial systems. There is a clear emphasis on deploying AI efficiently on constrained devices and integrating physical models with machine learning. J. William Fullbright Fellowship (1993) Best paper award IEEE European Design Automation Conference (1996) Best paper award ACM/IEEE Great Lakes Symposium on VLSI (2008) DAC Service Award (2014) IEEE Fellow (2006) DATE Fellow (2014) Advising and Grants: He has supervised over 25 PhD students in computer engineering, AI, and urban systems. His research is funded by major EU programs (Horizon 2020, PNRR, KDT JU), national (PRIN, FAR), and regional grants, as well as industrial contracts with STMicroelectronics, Michelin, and Cefriel. He leads numerous high-impact projects in smart manufacturing, energy efficiency, and digital twins. Labs and Teams: He is a core member of the EDA Group, an interdepartmental research team at Politecnico di Torino focusing on VLSI-CAD, bioinformatics, smart cities, and Industry 4.0. He also contributes to IAM@PoliTo (Integrated Additive Manufacturing) and leads multiple EU and national research consortia.

• Digital Circuits and Systems
• Energy Efficiency
• Smart Cities
• +13 more

Giuseppe PAGNONI is an Associate Professor at the Department of Biomedical, Metabolic and Neurosciences of Università di Modena e Reggio Emilia . His research spans neuroscience , computational modeling , meditation , and brain network analysis . He teaches courses such as Neural Systems Modeling for Bioengineering students and Human Physiology and Pathophysiology in Medicine programs, with a focus on predictive coding , default mode network , and emotional valence processing . Pagnoni has contributed to ENIGMA-Meditation , a global initiative exploring meditation's neuroscientific basis, and developed sparse Bayesian models for analyzing brain network individual differences. His work on Alzheimer's disease investigates anosognosia mechanisms through resting-state fMRI, while other studies examine ghrelin's role in obesity-related reward processing and oxytocin's effects on social anxiety . He employs dynamic causal modeling and predictive processing frameworks to study cognitive effort, mind wandering, and neuromorphic learning. His methodological expertise includes functional MRI , independent component analysis , and computational simulations .

• Neuroscience
• Computational Modeling
• Meditation
• +5 more

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +12 more

Lorenzo Pavesi is a Full Professor of Experimental Physics at the Department of Physics, University of Trento (Italy), where he leads the Nanoscience Laboratory with 25 members. His academic career spans over 30 years, including roles as Assistant Professor (1990), Associate Professor (1999), and Full Professor (2002). He founded semiconductor optoelectronics research at the university and established photonics laboratories focused on growth and advanced treatment of materials. Research Focus: Silicon photonics, quantum optics, nonlinear optics, optical sensors, and neuromorphic computing. Leadership: IEEE Italian Chapter on Nanotechnology founder, editorial board member for Frontiers in Physics , ETRI Journal , and Sensors . His work bridges photonics and electronics, with recent advancements in integrated quantum photonics and neuromorphic systems. He has managed numerous national and international projects, holds 9 patents, authored over 500 papers, and edited 15+ books. Awards include the Cavaliere title (2001), IEEE Distinguished Speaker (2010-2011), and fellowships from IEEE, SPIE, and SIF.

• Integrated optics
• Nanocrystals
• Nanomaterials
• +11 more

Alessio Lugnan is an Assistant Professor at the Department of Physics, University of Trento, specializing in photonic neural networks and neuromorphic computing. His research bridges nonlinear dynamics, silicon photonics, and machine learning. Research Focus: Photonic neural networks, reservoir computing, and biologically plausible learning models. Technologies: Silicon microring resonators, integrated photonics, and all-optical memory systems. Recent publications highlight his work on leveraging nonlinear dynamics in photonic systems for advanced signal processing, image classification, and memory retention. He explores the intersection of optical computing and machine learning to enhance computational efficiency. Collaborations include Lorenzo Pavesi, Stefano Biasi, and Alessandro Foradori, focusing on scalable photonic architectures. No explicit awards, grants, or student advisement details are available in the provided text.

• Photonics
• Neural Networks
• Integrated Photonics
• +3 more

Alberto Del Bimbo is a Full Professor of Computer Engineering at the Department of Systems and Computer Science, University of Florence, Italy. He serves as Director of the Media Integration and Communication (MICC) Center, a National Center of Excellence focused on Artificial Vision, Artificial Intelligence, and Multimedia Technologies. His career spans academia and leadership roles, including Deputy Rector for Research and Innovation Transfer (2000-2006) and Director of the Department of Systems and Computer Science (1997-2000). Education : Master Degree in Electronic Engineering (1977), University of Florence. Research Interests : Artificial Vision, Multimedia, Multimodal Interaction, Image/Video Analysis, Surveillance, and Industry Automation. Academic Leadership : Editorial roles including Editor-in-Chief of ACM TOMM , and leadership in IEEE, IAPR, and ACM conferences. Projects : MICC Center’s work on neuromorphic computing, deepfake detection, and AI-driven surveillance systems, with industrial partnerships (Leonardo SpA, Thales Italia, IARPA). Article Trends : Recent work focuses on neuromorphic event-based vision, multimodal emotion prediction, compatible AI representations, and deepfake detection using local surface frames. Applications span smart environments, cultural heritage, and real-time surveillance. Scientific Awards : ACM Distinguished Scientist (2016) ACM Award for Outstanding Technical Contributions to Multimedia (2016) IEEE Senior Member IAPR Fellow Labs & Teams : Leads the MICC research team at the University of Florence, collaborating with international institutions and companies on vision and AI innovation.

• Artificial Intelligence
• Computer Vision
• Multimedia
• +4 more

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

Dr. Vincenzo Catrambone is an Assistant Professor in the Department of Information Engineering at the University of Pisa and a fellow of the Neuro-Cardiovascular Intelligence Lab. His research focuses on integrative approaches to understanding brain-body interactions using advanced signal processing and computational modeling techniques. His research program investigates functional interactions between cardiovascular dynamics and neural activity in both physiological and pathological conditions. Key areas include neuro-cardiac coupling mechanisms, emotion-time perception relationships in depression, multisensory integration, and brain-computer interface development. His methodological approaches combine EEG analysis, computational modeling, physiological monitoring, and neuromodulation techniques. Recent publications demonstrate increasing focus on clinical applications, particularly in depression, epilepsy, and trauma-related disorders. His work on brain-heart interplay has evolved toward translational studies investigating how psychotherapeutic interventions modulate neuro-autonomic communication pathways.

• Biomedical Signal Processing
• Brain-Heart Interactions
• Computational Neuroscience
• +3 more

Giuseppe Iannaccone is a full Professor at the University of Pisa , Department of Information Engineering. His research focuses on quantum electronics , neuromorphic computing , and 2D materials for advanced applications in analog circuits and high-temperature electronics. Lead researcher in QUEPE Quantum Engineering and QUEFORMAL projects Pioneer in neuromorphic chip design using silicon and 2D materials Active in developing high-temperature integrated circuits for industrial applications His recent work explores twisted transition metal dichalcogenides for spintronics, inkjet-printed 2D electronics on paper substrates, and wireless power transfer systems for medical devices. The Google Scholar articles show consistent contributions to analog neuromorphic engines , quantum transport modeling , and steep-slope transistor architectures . Collaborations include Gianluca Fiori and Benjamin Zambrano in neuromorphic hardware development. He actively promotes student well-being through institutional initiatives like the Ufficio Benessere at University of Pisa and has taught RFID and IoT courses for PhD students. Current research integrates MoS2/graphene heterostructures and van der Waals junctions for next-generation electronics.

• Quantum Electronics
• Neuromorphic Computing
• 2D Materials
• +5 more

Mariagrazia Graziano is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Politecnico di Torino, where she also serves as Director of the Teaching and Language Lab (TLLab). Her academic career spans multiple institutions, including her involvement with doctoral colleges at the University of Palermo for 'Technologies and Methods for University Education' from 2022-2025. Her research interests are at the forefront of nanotechnology and quantum computing, focusing on areas including: Molecular field-coupled nanocomputing Logic-in-memory computing architectures Quantum hardware design and optimization Single-molecule devices for logic and memory applications Nanomagnetism and spintronics Micro-for-Nano (M4N) Systems for Single Molecule Sensors Dr. Graziano's work bridges fundamental physics with practical applications in electronics, with particular emphasis on next-generation computing paradigms that address the memory-wall problem and explore alternatives to traditional von Neumann architectures. Her research has significant implications for fields ranging from molecular electronics to quantum information processing. Her recent publications demonstrate a strong focus on molecular field-coupled nanocomputing, quantum optimization techniques, and single-molecule device modeling. These works reveal a consistent research trajectory toward developing novel computing architectures that leverage quantum effects and molecular-scale phenomena to overcome limitations of conventional semiconductor technology. Dr. Graziano has received notable recognition including the prestigious Marie Curie Intra-European Fellowship for Career Development from the European Commission (2014). She serves as Associate Editor for FRONTIERS IN ELECTRONICS (since 2022) and JOURNAL OF COMPUTATIONAL ELECTRONICS (since 2019), and has participated in program committees for major conferences including the IEEE Design Automation and Test Conference Europe. As an advisor, Dr. Graziano mentors numerous PhD students working on cutting-edge research in quantum computing, molecular electronics, and nanotechnology. Her supervision spans multiple doctoral programs at Politecnico di Torino, with students exploring topics from quantum algorithms for urban traffic optimization to single-molecule junctions for next-generation electronics. Additionally, she leads several research projects including TENS (Toward Excellence in Nanocharacterisation of single-molecule Sensors) and previously served as Scientific Leader for the Quantum Computing e Quantum Networking project. Dr. Graziano is actively involved in the VLSILAB research group, where she contributes to advancing the state-of-the-art in electronic design and nanoscale computing technologies. Her work on patents, particularly the 'Device for Realizing Boolean Logic Functions XOR XNOR Inside Racetrack Memory,' demonstrates her commitment to translating theoretical research into practical technological innovations.

• Molecular electronics
• Nanoelectronics
• Quantum computing
• +8 more

Alon Ascoli is an Associate Professor in the Department of Electronics and Telecommunications at Politecnico di Torino. His scientific disciplinary sector is IIET-01/A - Electrical Engineering (Area 0009 - Industrial and Information Engineering). He previously held research positions at the Technical University of Dresden from December 1, 2012 to November 30, 2018. His teaching responsibilities span multiple engineering programs, including Computer Engineering, Electronic Engineering, and Physics Engineering. For the 2025/26 academic year, he serves as Course Lecturer for Electromagnetism and Circuit Theory and as Course Collaborator for Electrical Engineering and Networks and Complex Systems courses. Dr. Ascoli's research interests include: Memristor technology and modeling Reservoir computing architectures Nonlinear dynamics in electronic systems Circuit theory and mathematical modeling Neuromorphic computing applications Complex networks and systems His recent publications demonstrate expertise spanning from theoretical modeling to experimental implementation of memristive devices, with a current focus on applications in computing architectures. The trend in his work shows progression from fundamental memristor modeling (2013) to advanced applications in neuromorphic systems (2024-2025). He currently leads research activities in the RECOMMEND project (REservoir COMputing with MEmristive Nonlinear Dynamics: Theory, Design and Applications) running from 2024-2027, which involves international non-EU research collaboration. Dr. Ascoli supervises PhD student Rosanna Cavazzana in the Electrical, Electronics, and Communications Engineering program (40th cycle, 2024-present), reflecting his commitment to academic mentoring and research training in specialized electrical engineering fields.

• Memristor technology
• Reservoir computing
• Circuit theory
• +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