جست‌وجوی استاد و پژوهشگر

• Electromagnetic Compatibility
• Power Electronics
• Signal Processing
• +۳ مورد دیگر

Markeljan Fishta is a Researcher at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin. His roles include teaching assistance in courses such as PCB Design for PhD students, Analog Electronics for Master’s students, and Foundations of Electronics for Aerospace Engineering undergraduates. His research focuses on electromagnetic compatibility (EMC), power electronics, and wireless communication systems, particularly in reducing electromagnetic interference (EMI) in power converters and developing acoustic-based communication for smart water networks. His recent work emphasizes EMI mitigation techniques in wide bandgap (WBG) inverters, GaN-based DC-DC converters, and sigma-delta modulators. Additionally, he explores in-pipe acoustic communication for urban water infrastructure, addressing challenges in channel modeling and data transmission reliability. Fishta collaborates with researchers like Franco Fiori and Erica Raviola on these topics, contributing to both theoretical advancements and applied solutions. His publications reflect a multidisciplinary approach, spanning IEEE Transactions on Electromagnetic Compatibility and international workshops. His research trends show a strong emphasis on source-based EMI reduction strategies, robust modulator design, and innovative communication methods for infrastructure monitoring. Fishta’s teaching contributions span multiple engineering programs, demonstrating his commitment to both academic instruction and cutting-edge research in electronic systems and communication technologies.

• 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.

• Cryptography
• Coding Theory
• Algebra
• +۳ مورد دیگر

Alessio Meneghetti is a Professor at the Department of Mathematics, University of Trento. His research focuses on cryptography, coding theory, and information security, with applications to post-quantum cryptography, blockchain protocols, and secure distributed systems. He teaches courses such as Coding Theory and Applications, Cryptography, and Programming Lab, emphasizing practical implementations in Java and theoretical foundations. His work spans cryptographic primitives like threshold signatures, quantum-resistant algorithms, and consensus mechanisms. Key contributions include protocols like COB for Byzantine agreement and frameworks for group action-based multi-signatures. He has also explored quantum random number generation and linear codes' weight distributions. Publications highlight advancements in threshold cryptography, distributed key generation, and post-quantum signature schemes. His teaching integrates programming practices with mathematical rigor, preparing students for applied cryptography and computational mathematics.

Maurizio Valleمشاهده پروفایل

استاد

• Electronic Engineering
• Embedded Systems
• Machine Learning
• +۴ مورد دیگر

Maurizio Valle serves as Full Professor and PhD Program Coordinator at the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) of the University of Genoa. His teaching portfolio includes graduate-level courses such as Digital Systems and Electronic Devices for the Master's program in Electronic Engineering, with active instruction scheduled through the 2025-2026 academic year. His research program centers on embedded machine learning systems for tactile sensing applications, with particular emphasis on FPGA implementations of neural networks for real-time sensor data processing. Key focus areas include neuromorphic engineering approaches to tactile texture classification, PVDF sensor analysis for slippage detection, and hardware-efficient implementations of convolutional networks for hand-gesture recognition in prosthetic systems. This work bridges electronic engineering, robotics, and biomedical applications through the development of electronic skin technologies and sensor fusion methodologies. Analysis of his 15 most recent publications (2024-2025) reveals a concentrated research trajectory in real-time embedded solutions for tactile perception systems. Dominant themes include hardware acceleration of neural networks on FPGA/microcontroller platforms, biomimetic sensor design inspired by cutaneous mechanoreceptors, and practical implementations for the Hannes prosthetic hand. The publications demonstrate methodological rigor in sensor characterization while prioritizing computational efficiency for resource-constrained embedded deployment. As PhD Program Coordinator at DITEN, Professor Valle oversees doctoral research in electronic engineering disciplines, mentoring students in specialized areas including embedded AI systems and tactile sensor development. His academic leadership extends to curriculum development for graduate engineering programs at the University of Genoa. His laboratory work focuses on integrated electronic skin systems for prosthetic applications, featuring custom sensor arrays, embedded processing units, and neuromorphic computing architectures. Current projects involve multimodal sensory feedback systems for upper-limb prostheses and real-time object recognition frameworks using wearable sensor gloves, indicating active collaboration with biomedical engineering and robotics research groups.

Ilaria De Munariمشاهده پروفایل

استاد

• Electronics
• Digital Systems
• Microcontroller-based Systems
• +۸ مورد دیگر

Ilaria De Munari is a Full Professor at the Department of Engineering and Architecture of the University of Parma, specializing in Electronics. She has been with the University of Parma since 1997, progressing from Researcher to Associate Professor in December 2004, and finally to Full Professor on February 1, 2024. Her research interests span multiple areas of electronics engineering with particular focus on digital systems, sensor design, and applications for healthcare and agriculture. She has developed expertise in microcontroller-based systems, FPGA development, and electrochemical applications. Her work has significant applications in Ambient Assisted Living technologies, food fraud detection systems, and precision agriculture. De Munari has coordinated multiple research projects including the PNRR METROFOOD-IT project since 2022, focusing on e-tongue and e-nose devices for detecting food fraud. Her recent publications demonstrate strong activity in sensor development for agricultural and healthcare applications. Senior Member of IEEE Associate Editor of the IEEE ACCESS journal Throughout her career, De Munari has secured funding for numerous research projects including European AAL projects (FOOD, HELICOPTER, ENSAFE, NOAH), regional projects (PRRIITT), and national research initiatives. She has been instrumental in quality assurance initiatives at the University of Parma, serving in various leadership roles including Deputy Director of the Department of Information Engineering (2014-2016) and member of the University Quality Committee since 2017. De Munari co-founded multiple spin-off companies including I-Cubo srl (2008), SiliS srl (2002), and Reloc srl (2008), demonstrating her commitment to translating academic research into commercial applications. Her current research unit focuses on developing electronic systems for agrifood applications, particularly in food safety and quality assessment.

Laura Falaschettiمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Neural Networks
• Biomedical Engineering
• +۳ مورد دیگر

Prof. Laura Falaschetti is a Researcher at the Department of Information Engineering, Polytechnic University of Marche (Ancona, Italy). Her work focuses on embedded systems, neural networks, biomedical engineering, and signal processing. She develops lightweight machine learning models for resource-constrained devices, with applications in healthcare monitoring, environmental sensing, and wearable technology. Key projects include real-time gesture recognition systems, EEG-based disease classification, and low-power IoT devices for disaster early warning. Her research integrates hardware-software co-design (e.g., QEMU/GHDL) and emphasizes practical deployment of AI algorithms on microcontrollers. She holds office hours every Friday 10:00-13:00 at Ufficio docente Q165 DII/Microsoft Teams. Contact: l.falaschetti@staff.univpm.it Publications highlight contributions to embedded vision systems, wearable sensor networks, and multimodal signal fusion for clinical applications. Her work bridges theoretical machine learning with practical embedded system constraints, addressing challenges in energy efficiency, real-time processing, and medical accuracy.

Francesco Bellottiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Embedded Systems
• Automated Driving
• +۳ مورد دیگر

Francesco Bellotti is an Associate Professor at the University of Genoa's Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN). He teaches advanced courses including Computational Intelligence, Cyber Physical Systems, and Machine Learning for Automated Driving across master's programs in Electronic Engineering and Engineering Technology for Strategy and Security. His institutional role includes membership in the steering committee of the Italian Excellence Center for Logistics, Transport, and Infrastructure (CIELI). Bellotti's research focuses on artificial intelligence and embedded systems , with applications in automotive technology, edge computing, and TinyML. Key areas include real-time driver distraction detection, deep reinforcement learning for autonomous parking, neural architecture optimization for microcontrollers, and cross-domain activity recognition. His work bridges theoretical machine learning with resource-constrained hardware implementations. Recent publications (2024-2025) demonstrate a strong emphasis on optimizing deep learning models for edge deployment, particularly in automotive and IoT contexts. Dominant themes include real-time neural network inference on microcontrollers, adversarial training for robust autonomous agents, video preprocessing for driving scenarios, and benchmarking lightweight vision models. The research consistently targets efficiency-critical applications, reflecting Bellotti's focus on scalable embedded AI solutions.

• Embedded Systems
• Neural Networks
• Hardware-Aware Neural Architecture Search
• +۷ مورد دیگر

Rodolfo Zunino serves as a Full Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) at the University of Genoa. His teaching portfolio includes core electronics courses across multiple degree programs including Master's in Electronic Engineering and undergraduate programs in Electronics Engineering and Information Technology. His research focuses on the intersection of embedded systems and neural networks, with particular emphasis on hardware-aware optimization for resource-constrained environments. Key areas include traffic classification for cybersecurity, affordance segmentation for robotics, energy-efficient structural health monitoring, and in-sensor computing architectures. His work consistently addresses the Pareto optimization between computational efficiency and accuracy in embedded AI applications. Analysis of his recent publications (2023-2025) reveals a strong trend toward hardware-software co-design for neural networks, with increasing specialization in wearable robotics and structural monitoring systems. The research demonstrates consistent innovation in neural architecture search techniques specifically tailored for microcontrollers and sensor-embedded systems. Professor Zunino maintains active research supervision with multiple advisees (though specific names aren't listed in available materials) and collaborates on projects involving hardware implementation of neural networks for security and monitoring applications. His work receives consistent publication in relevant engineering venues. His laboratory activities center around embedded electronic systems development, with focus areas in neural network acceleration for microcontrollers, sensor data processing, and real-time system implementation for robotics and infrastructure monitoring applications.

PAOLO CRIPPAمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Embedded Systems
• Neural Networks
• +۵ مورد دیگر

Prof. Paolo Crippa is an Associate Professor at the Department of Information Engineering (DII) of the University of Ancona (Università Politecnica delle Marche), Italy. His research focuses on biomedical signal processing, embedded systems, and wearable technology for healthcare applications. He specializes in neural networks, sensor design, and nanoelectronics, with notable contributions to graphene-based biosensors and real-time gesture recognition systems. His work bridges electronics, machine learning, and healthcare, addressing challenges in disease diagnosis, activity monitoring, and assistive living technologies. Prof. Crippa’s publications emphasize the development of low-power, high-accuracy systems for applications such as EEG-based disease classification, wearable sensors for activity recognition, and SARS-CoV-2 detection using advanced materials. His recent work includes optimizing LSTM neural networks for embedded platforms and integrating multimodal sensors (PPG, IMU, sEMG) for health monitoring. His research trends reveal a strong emphasis on applying machine learning to biomedical signals, improving sensor synchronization, and leveraging nanotechnology for diagnostic tools. He also explores open-source hardware/software co-design frameworks for system-on-chip (SoC) development. Prof. Crippa’s contributions extend to international collaborations and interdisciplinary projects, reflecting his role in advancing both theoretical and applied aspects of information engineering.

Silvia Liberata Ulloمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Silvia Liberata Ullo is a Researcher at the Department of Engineering (DING) of Università del Sannio . Her work spans Remote Sensing , Machine Learning , and Telecommunications , with a focus on Environmental Monitoring and Public Health Applications . Key research areas: Deep Learning for Land Cover Mapping Speckle Noise Reduction in SAR Data Machine Learning for Pandemic Response Mixed Reality in Military Systems Her recent publications highlight advancements in 2025 : Deep Learning for Land Cover Classification using Sentinel-1 2024 : Ensemble ML models for Dengue Outbreak Forecasting in Brazil/Peru 2023 : SAR Image Enhancement via Residual Neural Networks She collaborates with international institutions on climate-health services and geospatial AI projects.

• Power Electronics
• Embedded Systems
• Software Testing
• +۳ مورد دیگر

Davide Piumatti is a Lecturer and Technical Services Coordinator at the Department of Control and Computer Science (DAUIN) , Polytechnic University of Turin . He actively contributes to teaching in Computer Engineering , Automotive Engineering , and Aerospace Engineering programs. Specializes in Power Electronics and Embedded Systems Focuses on Software Testing and Automotive Engineering Key interests: Digital Transformation and Public Administration Technologies His recent publications emphasize thermal modeling for power devices, multi-core testing in automotive systems, and reliability engineering . He contributes to IEEE conferences and journals like Microelectronics Reliability and Electronics . Piumatti is affiliated with the LABINF - Advanced Computer Science Teaching Laboratory (DAUIN) and collaborates with researchers such as Matteo Sonza Reorda and Francesco Angione . His work addresses fault detection , test library development , and cyber-physical system validation .

• Analog electronics
• Electromagnetic compatibility (EMC)
• Power electronics
• +۲ مورد دیگر

Francesco Musolino is a Tenured Assistant Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin. He serves as a member of the Power Electronics Innovation Center (PEIC) and leads the Microwave and Optoelectronics Group (MOG) . His research focuses on analog and power electronics, electromagnetic compatibility (EMC), and digital control techniques for energy-efficient systems. Doctoral Supervision: Neha Dalal (Power Management ICs), Stefano Cerutti (Power Optimizers), Ahmed Abdullah (Digital PWM), Roberto Rubino (Low-Power ICs) Key Research Areas: Analog electronics, Power electronics, Electromagnetic compatibility, Digital-to-Analog conversion, Renewable energy integration Recent publications highlight advancements in hybrid digital PWM for power converters, EMC attack mitigation in smart speakers, self-calibrating DACs, and photovoltaic power optimizers. His work spans ultra-low-power IC design , resonant converter topologies , and EMI resilience in mixed-signal systems. Selected Teaching: Advanced electronic drives, Power electronics (2019-2025) Research Leadership: VirtEM project (2024-2026) on EM simulation for sustainable vehicles

Daniele Mazzeiمشاهده پروفایل

پژوهشگر

• Robotics
• Bioengineering
• Human-Robot Interaction
• +۳ مورد دیگر

Daniele Mazzei is a postdoctoral researcher at the Interdepartmental Research Center "E.Piaggio" at the University of Pisa. He coordinates the FACETeam, focusing on social robot control systems for empathic human-robot interaction, and leads a collaboration between the "E.Piaggio" Center and the Department of Computer Science at the University of Pisa. His work extends to embedded wearable systems for physiological monitoring and affective state inference through multivariate signal processing. PhD in Automatic Robotics and Bioengineering (2010), University of Pisa Master Degree in Biomedical Engineering (2006), University of Pisa His research interests include robotics, bioengineering, tissue engineering, and wearable monitoring systems. He developed bioreactor systems for tissue engineering during his PhD and is now advancing social robotics for autism therapy. His work spans embedded systems, microcontroller-based solutions, and cross-cultural robotic platforms. Daniele is a co-inventor of 7 patents and has collaborated internationally, including a visitor researcher role at Carnegie Mellon University's CYLAB in 2011. He partners with Hanson Robotics on robotic autism therapy systems and contributes to European projects on unobtrusive physiological monitoring.

• Embedded Systems
• Fault Tolerance
• Precision Agriculture
• +۵ مورد دیگر

Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.