Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.
Giorgio Grisetti is a Full Professor at Sapienza University of Rome within the Department of Systems and Computer Science, maintaining active research roles in the RoCoCo lab at Sapienza since November 2010 and the Autonomous Intelligent Systems Lab at Freiburg University where he previously served as a Post Doc under Wolfram Burgard starting in 2006. His educational background includes a M.Sc. in Computer Engineering from the University of Rome (2001) and a Ph.D. from Sapienza University of Rome's Intelligent Systems Lab (2006), supervised by Daniele Nardi. His doctoral thesis focused on SLAM using Rao-Blackwellized particle filters. Dr. Grisetti's research centers on mobile robotics with emphasis on robust solutions for autonomous navigation systems. His work spans theoretical and practical advancements in Simultaneous Localization and Mapping (SLAM), robot localization, path planning, and sensor fusion, particularly leveraging LiDAR and multi-sensor configurations. Recent publications demonstrate strong focus on optimization techniques, sensor calibration, and real-time performance for autonomous systems operating in complex environments. His publication trends reveal deep specialization in LiDAR-based SLAM (7 of 15 recent articles), bundle adjustment methods (4 articles), and sensor calibration/perception (3 articles), with consistent contributions to top robotics venues like IEEE Robotics and Automation Letters and ICRA. Key recognitions include: Nomination for the best IROS paper award (2010) Open Source achievement award from Willow Garage (2010) Best paper award at the International Conference and Exhibition on Unmanned Areal Vehicles (2010) Best Paper award at ICRA 2009 (2009) His research is conducted through the RoCoCo lab at Sapienza University of Rome and the Autonomous Intelligent Systems Lab at Freiburg University, focusing on developing foundational algorithms for mobile robot autonomy. Current projects emphasize robust perception systems, optimization frameworks for sensor fusion, and practical implementations for real-world navigation challenges.
Battista Biggio is a Full Professor at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering under the Faculty of Engineering and Architecture. His research focuses on machine learning security, adversarial attacks, and cybersecurity. He co-founded the cybersecurity firm Pluribus One and has pioneered foundational work in poisoning attacks and adversarial robustness. Education: MSc (2006), PhD (2010). He holds editorial roles as Associate Editor-in-Chief for Elsevier's Pattern Recognition Journal and serves on IEEE TNNLS and IEEE CIM editorial boards. His awards include the 2022 ICML Test of Time Award and the 2021 Pattern Recognition Medal. He chairs IAPR TC1 and organizes conferences like S+SSPR and AISec. Research interests span adversarial machine learning, malware detection, and secure AI systems. He leads initiatives such as the sAIfer Lab and co-develops the SecML-Torch library. Teaching includes courses on Machine Learning Security and Industrial Software Development. Notable contributions include seminal papers like 'Poisoning Attacks against Support Vector Machines' and 'Wild Patterns.' He manages over 10 research projects and advises on AI security for industrial applications. His work bridges academic research with practical cybersecurity solutions.
Mauro Conti is a Full Professor at the University of Padua, Italy, where he serves as Editor-in-chief of IEEE TIFS, UniPD Academic Advisor for Entrepreneurship Development, Study Program Coordinator of the MSc degree in Cybersecurity, Head of the SPRITZ Security and Privacy Research Group, and Director of the UniPD node of CINI Cybersecurity National Lab. He also maintains affiliations with TU Delft (NL) and the University of Washington (USA). Additionally, he is the CEO and co-founder of CHISITO and co-founder of DYALOGHI. His research focuses on security and privacy for wireless resource-constrained mobile devices (WSNs, RFIDs, and smartphones), computer system security, computer forensics, access control, and distributed and networked systems. Professor Conti has published extensively in top security venues including ACM CCS, IEEE S&P, NDSS, and USENIX Security, with recent work covering topics such as battery authentication, federated learning privacy, private set intersections, USB peripheral fingerprinting, and ATM PIN inference. He has received numerous prestigious awards including IEEE Fellow, Young Academy of Europe Fellow, EU Marie Curie Fellow, and DAAD Fellow. Professor Conti has advised over 100 students at various levels including PhD, MSc, and BSc, many of whom have gone on to successful careers in academia and industry. His research has been supported by multiple European Commission projects, university grants, and industry collaborations with companies like Cisco and Intel.
Corrado De Sio is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN) , Politecnico di Torino , affiliated with the College of Computer, Film, and Mechatronics Engineering . His academic roles include course instruction and collaboration for Reconfigurable Computing , High Performance Computing (HPC) , and Operating Systems for High-Performance Supercomputers across multiple academic years (2020-2025). Research Interests focus on: Reliability of reconfigurable systems and FPGAs under radiation effects Hardware-software co-design for fault tolerance Embedded systems in aerospace and safety-critical applications Machine learning acceleration on reconfigurable hardware Radiation effects on real-time operating systems and CNN implementations Recent publications address: 2025: Selective hardening of RISCV soft-processors for space applications 2025: Real-time 'signal for help' gesture recognition systems 2024: Reliability analysis of RISC-V processors and CNN placement algorithms 2023: Fault tolerance in FPGA-based CNNs and radiation effects on RTOS Patents include: PyXEL - Python Toolkit for Reconfigurable Hardware Surveillance Software for Real-Time Violence Detection Academic Supervision : Co-supervisor for PhD candidate Arash Amini Bardpareh in Computer and Systems Engineering .
Sara Vinco is an Associate Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy. She specializes in battery simulation, digital twins, and energy-efficient design automation for heterogeneous embedded systems, aligning with Industrial and Information Engineering (Area 0009) and ERC sectors including Computer Architecture and Machine Learning . Her research focuses on advancing cyber-physical systems through simulation frameworks like SystemC-AMS, enabling holistic modeling of analog, digital, and thermal domains. Key projects include data-driven digital twins for EV batteries and low-area digital circuits in industrial/medical applications, supported by commercial contracts such as C-based virtual prototyping. Her recent publications (2022-2023) emphasize machine learning for battery SOH/SOC estimation , energy monitoring in production lines , and multi-domain fault modeling . These works span journals like IEEE Transactions and conferences including DATE and ISLPED. Awarded the FFABR 2017 grant and IEEE FDL Best Paper Award 2011 , she also chairs editorial boards for IEEE Transactions on CAD and DATE Conference. She supervises PhD students Giovanni Pollo (Digital Circuits) and Khaled Alamin (EV Battery Twins), reflecting her leadership in smart systems design.
Matteo Nardello is a researcher affiliated with the Department of Industrial Engineering at the University of Trento. His work focuses on embedded systems, IoT, and energy harvesting technologies for sustainable applications. Current academic affiliation: Department of Industrial Engineering, University of Trento Research interests: IoT, embedded systems, energy harvesting, machine learning, cyber-physical systems Contact: matteo.nardello@unitn.it His research integrates hardware-software co-design for batteryless IoT systems, with applications in smart agriculture, industrial monitoring, and autonomous vehicles. Recent work explores deep learning at the edge, energy-efficient sensor networks, and microbial fuel cells for self-powered devices. Key article trends highlight a focus on sustainable power solutions, wireless sensor networks, and machine learning optimization for constrained environments. He contributes to courses on embedded systems, IoT, and AI-powered industrial applications at the University of Trento.
Eleonora Vacca is a PhD student and Research Fellow in the Department of Automatic Control and Computer Science (DAUIN) at the Polytechnic University of Turin. She holds a B.S. in Electronic Engineering from the University of Palermo (2018) and an M.S. in Electronic Engineering-Embedded Systems from Politecnico di Torino (2021). Her research focuses on digital hardware design, reliability engineering, reconfigurable devices, and AI applications in aerospace and safety-critical systems. She is a member of the Aerospace and Safety Computing Lab and the CAD - Electronic CAD & Reliability Group (DAUIN). Her work addresses challenges such as radiation effects mitigation in space missions, fault-tolerant AI accelerators, and real-time anomaly detection in satellite telemetry. She has contributed to projects like the RAMSES CubeSat-1 Development (2025-2026), funded by commercial contracts. In 2024, she won the Best Student Paper Award at the NEWCAS Conference for her research on radiation effects in space missions. Vacca collaborates on teaching, including assisting in the course 'Electronic Calculators' for Computer Engineering students. Her recent publications explore AI resilience in RISC-V ecosystems, radiation environment analysis for space missions, and gesture recognition systems for smart cities. She actively contributes to conferences such as the ACM International Conference on Computing Frontiers and the IEEE International Smart Cities Conference.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Luciano Lavagno is a Full Professor at the Department of Electronics and Telecommunications, Polytechnic University of Turin, with over two decades of academic and research contributions. His work bridges hardware acceleration, low-power electronics, and intelligent system design. Research Focus: Hardware-accelerated machine learning, high-level synthesis (HLS) for FPGA/ASIC, heterogeneous CPU/GPU/FPGA platforms Key Projects: SPACE (predictable acceleration), REBECCA (secure AI acceleration), HPC-National Center (quantum computing), and oral history preservation via "Ti racconto una storia" initiative His recent publications analyze CNN inference optimization, subgraph isomorphism, and superword-level parallelism exploitation. Lavagno supervises multiple PhD students working on FPGA acceleration, neural network hardware, and embedded systems. As Principal Investigator for national and EU-funded projects (PRIN, JTI-ECSEL, PNRR), he drives advancements in sustainable computing infrastructure. His patented technologies include MIx&Latch timing methodology, capacitive sensing innovations, and 5G acceleration frameworks.
Maurizio Martina is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. He is a member of the Interdepartmental Center PEIC - Power Electronics Innovation Center and serves as an Associate Editor for the IEEE Transactions on Circuits and Systems I (2018-2023). His research focuses include: Digital circuits and signal processing Machine learning hardware architectures RISC-V extensions and post-quantum cryptography VLSI design for edge computing and IoT Recent publications emphasize cryptographic hardware implementations (CHIMERA, Keccak co-processors), RISC-V integration methodologies, and privacy-preserving neural network frameworks. His work spans VLSI architectures for video processing, bio-inspired electronics, and error correcting codes, with applications in cybersecurity, robotics, and biomedical systems. Scientific Recognition : Premio Nazionale Innovazione (2013) Premio dei Premi (2014) He supervises 12 PhD students across cycles 35-40 in Electrical, Electronics and Communications Engineering, including: Valeria Piscopo (2024-in progress) Alessandra Dolmeta (2022-in progress) Luigi Giuffrida (2022-in progress) Walid Walid (2019-2023) As part of the VLSILAB Group , his research explores hardware accelerators for machine learning, post-quantum cryptography on RISC-V, and bio-inspired embedded systems. Teaching activities include courses on Integrated Systems Architecture and Hardware & Wireless Security at Politecnico di Torino and Università di Pavia.
Gianluca Setti is a Full Professor at the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, where he has been serving since 2017. He previously held positions at the University of Ferrara from 1997 to 2017. His institutional roles include being the Contact Person for the Research Quality Evaluation process, Member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, and Member of the University Quality Assurance Committee. He serves as Editor-in-Chief of the Proceedings of the IEEE, the first non-US editor to hold this position. Dr. Setti's research spans multiple interdisciplinary fields including machine learning, artificial intelligence, big data analytics, Internet of Things, biomedical signal processing, power electronics, and electromagnetic compatibility. His work bridges theoretical foundations with practical applications, particularly focusing on compressed sensing, neural networks, and circuit design for specialized applications. His research has significant implications for healthcare, sustainable infrastructure, and next-generation electronics. His publication record reveals a consistent trajectory from foundational work in chaotic systems and neural networks to contemporary applications in AI, IoT, and edge computing. The most recent publications demonstrate his focus on anomaly detection at the edge, neural oracles for biosignal processing, and power electronics innovations. His work shows strong integration between theoretical signal processing and practical circuit implementation. 1998 Caianiello prize (best Italian Ph.D. thesis on Neural Networks) IEEE Fellow (2006) IEEE Circuits and Systems Society Distinguished Lecturer (2004, 2015) 2004 IEEE CAS Society Darlington Award 2013 IEEE CAS Society Meritorious Service Award 2013 IEEE CAS Society Guillemin-Cauer Award 2019 IEEE Transactions on Biomedical Circuits and Systems best paper award Multiple best paper awards at major conferences including ECCTD2005, EMCZurich2005, ISCAS2011, PRIME2019, and EMCCOMPO2019 Dr. Setti has supervised numerous PhD students across various research domains including electromagnetic compatibility, signal and power integrity, communication networks, mechatronics and robotics. His research is supported by significant funding including national PRIN projects, EU-funded JTI-ECSEL initiatives, and commercial contracts. He leads the VLSILAB Group at DET, focusing on circuit architectures, embedded systems, and AI applications. His current projects include DECORI (anomaly detection), StorAIge (embedded storage for AI), PROGRESSUS (energy infrastructure), CONNECT (smart grid), and CONVERGENCE (wearable healthcare applications).
Giovanna Turvani is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino, with affiliations in both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Scientific Branch: IINF-01/A - Electronics ERC Sectors: PE7_4, PE7_11, PE6_1, PE6_14, PE7_3 SDG Goals: Quality Education, Gender Equality, Affordable Energy, Industry Innovation Her research focuses on advanced electronics and quantum technologies, including: Logic-in-memory computing Quantum computing architectures Microwave imaging for medical and agricultural applications CAD tools for emerging nanotechnologies Embedded systems for bee health monitoring IoT solutions for bio-waste valorization Publications show strong expertise in quantum computing, nanocomputing, and microwave imaging, with recent trends emphasizing quantum optimization frameworks, in-memory architectures, and IoT-based agricultural technologies. She supervises PhD students in areas like quantum machine learning algorithms, predictive on-board systems, and quantum hardware design. Collaborations span multiple disciplines, including medical device development and agricultural electronics. Patents include innovations in microwave imaging, racetrack memory logic functions, and in-memory computing devices.
Alberto Macii is a Full Professor in the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin. He is also a member of the Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing and serves on two colleges: College of Computer, Film and Mechatronics Engineering and College of Mechanical, Aerospace and Automotive Engineering. His research interests include: Digital circuits and systems Electronic systems, modeling, and simulation Energy-efficient circuits and systems Energy management and battery systems Embedded systems and cyber-physical systems Low energy building technologies His work aligns with several Sustainable Development Goals including affordable and clean energy (Goal 7), industry innovation and infrastructure (Goal 9), and sustainable cities and communities (Goal 11). His publication record shows a consistent focus on energy efficiency in electronic systems spanning over two decades, with particular emphasis on battery modeling and power management. Recent work has expanded into environmental applications with transformer neural networks for flood forecasting, demonstrating the evolution of his research into new application domains while maintaining core expertise in energy optimization. His scientific awards include: Best paper award ACM/IEEE Great Lakes Symposium on VLSI (2008) IEEE Fellow (2007-) Senior Member IEEE He has served as Editor-in-Chief for the Journal of Embedded Computing (2005) and as Program Chair for EUC2005: Embedded & Ubiquitous Computing. Professor Macii has advised PhD students including Alberto Bocca (2019-2023) whose thesis focused on compact modeling techniques for energy analysis and optimization of complex systems. He has led numerous research projects including CANP (2018-2020), R3-PowerUP (2017-2021), SERENA (2017-2020), AMable (2017-2021), and STAMP (2016-2019), demonstrating sustained research leadership across multiple funding mechanisms. He is active in the EDA - Electronic Design Automation research group and LAB 4 research laboratory at DAUIN, with research spanning VLSI-CAD, Smart City technologies, and Industry 4.0 applications. His work bridges theoretical computer engineering with practical applications in energy conservation across multiple domains.
Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.
