جستجوی استاد راهنمای دانشگاهی

• Software Engineering
• Formal Methods
• Software Architectures
• +۷ مورد دیگر

Patrizia Scandurra is an Associate Professor at the Department of Management, Information and Production Engineering, University of Bergamo, Italy. Her academic appointment in Computer Science (01/B1) spans from 2022 to 2033. She previously held roles as a researcher at the University of Bergamo (2009-2017) and postdoctoral fellow at the University of Milan (2006-2008). She earned her PhD in Computer Science (2006) and Bachelor's degree (2002) from the University of Catania. Research Focus : Software architectures and formal methods for modeling, validation, and verification of software-intensive systems. Specializations : Runtime analysis of self-adaptive, autonomous, and uncertain systems including IoT-Edge-Cloud applications, embedded systems, and system-on-chip. Collaborations : STMicroelectronics, Atego, Bialetti, and ENEA. Conference Involvement : Program/organizing committees for ICSE, ASE, ISSRE, ICSA, ECSA, SEAMS@ICSE, ABZ, SA-TTA@SAC, FAACS@ECSA. Research Projects : Model-driven development for robotics, adaptive architectures for pervasive systems, big data in smart cities, and digital twins for medical systems. Notable Contributions : Development of the ASMETA formal method community tools and frameworks for rigorous system design. She has published over 100 peer-reviewed works in international journals and conferences.

• Computer Networks
• Edge Computing
• Internet of Things (IoT)
• +۵ مورد دیگر

Paolo Bellavista is a Full Professor of Distributed and Mobile Systems at the Department of Computer Science - Science and Engineering, Alma Mater Studiorum – University of Bologna. His research focuses on edge computing, federated learning, IoT, digital twins, and blockchain applications. With over 140 journal articles and 200+ conference papers, his work appears in top venues such as ACM Computing Surveys and IEEE Transactions. He serves as Editor-in-Chief of the MDPI Computers Journal and holds editorial roles in IEEE Communications Surveys&Tutorials and ACM Computing Surveys. His contributions span network optimization, cybersecurity, and smart cities, with notable achievements in citation metrics (h-index 46 on Google Scholar). Research interests include distributed systems, vehicular networks, AI-driven security, and QoS-aware edge infrastructures. He has organized major conferences like IEEE Mobile Cloud and ACM ICDCN. Current projects explore federated learning unlearning, digital twin entanglement, and blockchain-based data spaces. His work bridges theoretical foundations with real-world deployments in smart manufacturing and healthcare. Editorial Roles : MDPI Computers (Editor-in-Chief), IEEE Communications Surveys&Tutorials (Associate Editor), ACM Computing Surveys (Editor) Conference Leadership : Technical Program Chair for IEEE Mobile Cloud 2015, General Co-Chair for SCNS 2018 Key Contributions : Over 140 journal papers, 15 special issues as guest editor, and 200+ conference publications His lab develops middleware for edge-cloud continuum applications and collaborates internationally on projects like InAbled Cities. Office hours are held weekly at the University of Bologna’s DISI department.

• Functional Safety
• Functional Testing
• Microprocessor Testing
• +۹ مورد دیگر

Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.

Luigi Pomanteمشاهده پروفایل

استادیار

• Electronic System-Level HW/SW Co-Design
• Heterogeneous Parallel Systems
• Embedded Systems
• +۵ مورد دیگر

Luigi Pomante is a tenured Assistant Professor at the University of L'Aquila, Italy, where he is affiliated with the Department of Engineering and Information Science and Mathematics (DISIM) and the DEWS Center of Excellence. His academic career focuses on research and teaching in embedded systems and hardware-software co-design methodologies. Dr. Pomante's primary research interest is Electronic System-Level Hardware-Software Co-Design of heterogeneous parallel dedicated systems. He is the principal developer of the HEPSYCODE framework, which provides comprehensive methodologies and tools for system-level design space exploration. His work addresses critical challenges in embedded systems development, including handling functional and non-functional requirements, heterogeneous architectures, and mixed-criticality constraints. He has published extensively in journals like IEEE Transactions on Computers and IET Computers & Digital Techniques, as well as at major international conferences. Analysis of Dr. Pomante's publication record reveals a consistent research trajectory focused on hardware-software co-design methodologies, with increasing attention to real-time constraints and mixed-criticality systems in more recent work. His publications demonstrate expertise in design space exploration techniques, system modeling using CSP-like approaches, and the development of metrics for evaluating hardware-software partitioning solutions. The HEPSYCODE framework represents his most significant contribution to the field. Dr. Pomante actively supervises student projects and theses related to electronic design automation and embedded systems. He has contributed to European research projects including EMC2 (Embedded Multi-Core systems for Mixed Criticality applications), where he was responsible for deliverables related to design methodologies, implementation approaches, and validation frameworks. His work has practical applications in aerospace and other safety-critical domains through collaborations with industry partners. He leads the HEPSYCODE research group at DEWS, which focuses on developing methodologies and tools for hardware-software co-design of heterogeneous parallel dedicated systems. The group's current work includes extensions for real-time and mixed-criticality systems, frameworks for embedded system monitoring, and techniques for handling approximate computing and energy/power constraints within the design space exploration process.

Claudia Rinaldiمشاهده پروفایل

پژوهشگر

• Telecommunications
• Signal Processing
• Wireless Sensor Networks
• +۴ مورد دیگر

Claudia Rinaldi is a Post Doctoral Researcher at the Faculty of Engineering , University of L'Aquila , with a focus on telecommunications and signal processing. She contributes to projects involving Wireless Sensor Networks (WSN) , Software Defined Radio , and Cognitive Radio applications in both engineering and artistic domains. Doctorate in Wireless Communications (2009, University of L'Aquila) Master's in Electronic Engineering (cum laude) with thesis work at KTH Stockholm Trumpet graduate from Conservatory of Music "A. Casella", L'Aquila (2006) Her research spans physical layer protocol design , WSN applications in electronic music , and MAC layer optimization for WiMax. Key projects include: RFSounding : Interactive installation converting radio frequencies to audible sound Homeland Security : Wireless perimeter monitoring systems SMILING : Home automation sensor technologies VISION : 3D video sensing with UWB radios She has taught Signal Analysis , Wireless Communications , and Electrical Communications , and contributed to book chapters in Technological Innovation and Springer Verlag publications.

Egidio Faloticoمشاهده پروفایل

استادیار

• Robotics
• Biorobotics
• Computational Neuroscience
• +۴ مورد دیگر

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.

Riccardo Rosatiمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Deep Learning
• Biomedical Engineering
• +۵ مورد دیگر

Riccardo Rosati (born 1992) is a Research Fellow and Ph.D. student at the Polytechnic University of Marche, where his work focuses on Machine Learning and Deep Learning applications in biomedical engineering and Industry 4.0. He holds a Master of Science in Biomedical Engineering (cum laude, 2018) from the same institution and completed an internship at the Image Processing Division of Leiden University Medical Center (2018-2019). His current Ph.D. scholarship, funded by the Marche Region, supports research in "Embedded Automation and Edge Computing for Industry 4.0". Research Areas: Deep learning for biomedical imaging (e.g., facial liveness detection, lung ultrasound analysis) AI-driven predictive maintenance in industrial systems Augmented reality frameworks for industrial design Steganalysis and biometric-based security systems Human-centered AI applications Key Publications Trends: His recent work spans facial liveness detection, wastewater sensor forecasting, excavation monitoring, and predictive maintenance of ATMs. The research combines convolutional neural networks, LSTM architectures, and transformer models with applications in healthcare, industrial automation, and cybersecurity. Contact: Email r.rosati@univpm.it , Office: +39 071 2204465, Room: Q165_121.

• Performance Analysis
• Network Systems
• Industrial Real-Time Communications
• +۴ مورد دیگر

Federico Tramarin is an Associate Professor at the Enzo Ferrari Engineering Department of the University of Modena and Reggio Emilia , Italy. He holds a Dr. Eng. in Electronic Engineering and a Ph.D. in Information Engineering from the University of Padova (2008 and 2012, respectively). Previously, he served as an Assistant Professor at the University of Padova's Department of Management and Engineering and held a post-doctoral position at the National Research Council of Italy (CNR) from 2013 to 2018. His research focuses on performance analysis and measurements of network systems , with emphasis on industrial real-time wired/wireless communications, cyber-physical systems, real-time embedded systems, Time Sensitive Networks (TSN), and IoT. He actively contributes to standards and protocols for industrial communication through memberships in IEEE committees (e.g., IEEE Industrial Electronics Society and Instrumentation and Measurement Society). Prof. Tramarin has authored/co-authored over 60 peer-reviewed publications in top conferences and journals, emphasizing real-time wireless LANs, industrial IoT, and networked control systems . His work spans topics like 5G-enabled PMU systems, TSN integration with SDN, and reliability in industrial wireless networks. He serves on editorial and program committees of major international journals and conferences, furthering the advancement of networked measurement systems. He is a member of the IEEE and the Italian Group of Electrical and Electronic Measurements (GMEE), reflecting his commitment to metrology and industrial automation. His interdisciplinary research bridges theoretical foundations with practical applications in smart manufacturing, automotive systems, and healthcare monitoring.

Gianluca CAIAZZAمشاهده پروفایل

پژوهشگر

• Cybersecurity
• Robotics
• Software Engineering
• +۳ مورد دیگر

Gianluca Caiazza is a Researcher at the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. He is affiliated with the Research Institute for Complexity and the Temporary Center for the Innovation Ecosystem Project. His work focuses on cybersecurity within robotics and software systems, particularly in the Robot Operating System (ROS) framework. He teaches courses such as 'Operating Systems - MOD.1' and 'Software and System Verification' at both undergraduate and doctoral levels. His research interests span cybersecurity for robotic systems, static analysis techniques, blockchain applications in robotics, and secure middleware development. He has conducted extensive work on enhancing ROS security through tools like SROS2 and static analysis frameworks like LiSA, addressing vulnerabilities in DDS systems and penetration testing methodologies. Caiazza's recent publications emphasize automated policy extraction, microservice security, and IIoT system scalability. His work bridges theoretical computer science with practical applications in robotics, contributing to both academic journals and industry-oriented conferences. He collaborates actively with institutions like IEEE and Springer, focusing on advancing secure robotic technologies. His teaching activities include laboratory modules for software project development and advanced verification techniques for software systems. Despite no listed awards, his contributions to ROS security frameworks are recognized within academic and industrial robotics communities.

• Artificial Intelligence
• Neuromorphic Computing
• Brain-inspired Computing
• +۱۳ مورد دیگر

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.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +۱ مورد دیگر

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

• Optical Sensors
• Aerospace Engineering
• Additive Manufacturing
• +۲ مورد دیگر

Alessandro Aimasso is a PhD student in Aerospace Engineering (38th cycle, 2022-2025) at the Polytechnic University of Turin's Department of Mechanical and Aerospace Engineering (DIMEAS), where he also serves as an external lecturer and teaching assistant. He contributes to research activities at the ASTRA group (Additive Manufacturing for Systems and Structures in Aerospace) and the interdepartmental Center for Photonic Technologies PhotoNext. His research focuses on optical sensors for aeronautical and space applications, particularly Fiber Bragg Grating (FBG) technology for system lifecycle management. Specific interests include: Augmented reality visualization of sensor data Thermal and structural monitoring of aerospace systems Smart composites manufacturing with embedded sensors Lunar habitat construction technologies Real-time monitoring systems for spacecraft Analysis of his recent publications shows strong focus on experimental validation of FBG sensor applications in extreme environments, development of real-time monitoring systems, and integration of augmented reality for data visualization. His work frequently involves rapid prototyping and multidisciplinary approaches to aerospace challenges. He holds two patents: USE AND INTEGRATION OF SENSORS IN THE STRUCTURE AND EQUIPMENT OF COMPLEX MACHINES FOR THE DEVELOPMENT OF INTELLIGENT MONITORING SYSTEMS AND CREATION OF MULTIFUNCTIONAL VIRTUAL SENSORS Gas-dynamic nozzle for an end-jet engine, specifically a launcher As a teaching assistant, he contributes to courses on Modeling, Simulation, and Testing of Aerospace Systems, and Photonics in the Digital Revolution. His laboratory work involves the ASTRA group's facilities focusing on additive manufacturing and photonic technologies.

Stefano Querمشاهده پروفایل

دانشیار

• Computer Science
• Electrical Engineering
• Formal Methods
• +۷ مورد دیگر

Stefano Quer is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He holds a PhD in Electronic Engineering from the same institution and has been affiliated with DAUIN since 1996. Researcher (1996-2000) Associate Professor (2000-present) Visiting Faculty at UC Berkeley (1994-1995) Research Interests His work spans Formal Verification BDD/SAT Techniques Embedded Systems Hardware/Software Co-Verification Parallel Computing with applications in VLSI CAD, industrial IoT, and energy-efficient systems. Recent articles focus on GPU-accelerated graph algorithms, wireless sensor calibration, and AI-driven test optimization. Scientific Awards Best Paper Award, IEEE EURO-DAC'94 Academic Contributions Supervised PhD students Lorenzo Cardone and Andrea Calabrese Member of DATE, ICSOFT Technical Program Committees Topical Advisor for Sensors MDPI 60+ publications in IEEE/ACM venues

• Numerical Analysis
• Machine Learning
• Computational Mathematics
• +۴ مورد دیگر

Elena Toscano is a researcher in the Department of Mathematics and Computer Science at the University of Palermo. She specializes in numerical analysis, machine learning, and computational mathematics, with a focus on mesh-free methods like Smoothed Particle Hydrodynamics (SPH) and applications to physics, engineering, and interdisciplinary fields. Teaching: Numerical Analysis (Master's in Informatics and Mathematics, 2025/2026) Research Areas: Signal/image processing, SPH consistency restoration, genetic algorithms for tomography, and mathematical-literary collaborations (e.g., Oulipo). Her publications span computational physics, machine learning, and mathematical modeling, emphasizing numerical stability and interdisciplinary innovation.

• Embedded Systems
• Internet of Things
• Cyber-Physical Systems
• +۱۷ مورد دیگر

Kasim Sinan Yildirim is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, where he conducts research at the intersection of embedded systems, Internet of Things (IoT), and wireless communication technologies. His work focuses on developing innovative hardware and software solutions for resource-constrained and energy-limited environments. His research interests include: Hardware and software design for batteryless and intermittently powered embedded systems Energy harvesting and transient computing Wireless sensor networks and self-organizing networks Backscatter and visible light communication Edge learning and inference Distributed algorithms and real-time computing The absence of published articles in the provided text prevents analysis of publication trends. However, his research direction emphasizes sustainable, low-power computing paradigms essential for next-generation IoT deployments. There are no listed scientific awards in the provided information. Dr. Yildirim advises students and contributes to academic training, though specific advisees are not listed. There is no mention of external grants or funded projects in the provided text. He is involved in research related to advanced embedded and cyber-physical systems, particularly focusing on novel computing models for batteryless devices and sustainable IoT infrastructures.