جستجوی استاد راهنمای دانشگاهی

• Machine learning
• Artificial intelligence
• Big data analytics
• +۸ مورد دیگر

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).

Enzo Mastinuمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Prosthetics and Neuroprosthetics
• Embedded Systems
• +۴ مورد دیگر

Enzo Mastinu is an electronic engineer specialized in embedded systems for biomedical applications, holding an Associate Professor qualification in Bioengineering. He earned his bachelor's and master's degrees in electronic engineering from the University of Cagliari and a PhD in biomedical signals and systems from Chalmers University of Technology, Sweden. His research focuses on advanced prosthetics and neuroprostheses for upper limb amputations, incorporating embedded systems design, control algorithms, sensory feedback, signal processing, AI, and osseointegration. Key projects include the HAND and HAND2 initiatives, funded by the EU and the Italian Ministry of Research, aiming to develop semi-autonomous prosthetic hands. He has published 25 journal articles (75% in Q1) and 21 conference papers, contributing to a PCT patent. Mastinu is a Senior Member of IEEE EMBS and RAS, reviews for ~90 journals/conferences, and edits Transactions on Medical Robotics and Bionics (IEEE) and Scientific Data (Nature). He has supervised ~40 students across PhD, master's, internships, and postdocs, and teaches courses in biomedical engineering and STEM education. His scientific awards include the Marie Skłodowska-Curie Fellowship (2021), National Qualification as Associate Professor (2024), and a Young Researcher Grant (2025). Research emphasizes clinical implementation of prosthetics with neural feedback and intuitive control, as highlighted in high-impact journals like the New England Journal of Medicine.

Corrado Loglisciمشاهده پروفایل

استادیار

• Temporal Data Mining
• Temporal Learning
• Textual Data Mining
• +۱۳ مورد دیگر

Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).

Massimo Orazio Spataمشاهده پروفایل

پژوهشگر ارشد

• Deep Learning
• Biomedical Engineering
• Computer Science
• +۳ مورد دیگر

Massimo Orazio Spata is a Research Fellow in Computer Science at the University of Catania's Department of Mathematics and Computer Sciences, specializing in deep learning applications for biomedical, audio, and biometric systems. He has held roles at STMicroelectronics since 1999, focusing on system integration, image processing, and biomedical device R&D. He teaches courses such as Mobile Programming and Computer Architecture at secondary schools and has advised numerous students on grid computing and middleware projects. Education: PhD in Computer Science (University of Catania, 2008), MSc in Computer Science (University of Catania, 2013), and a teaching certification in Computer Science (University of Catania, 1998). Research interests include deep learning algorithms, biomedical device development, grid scheduling, and cybersecurity. He has authored patents on lab-on-chip systems, bio-computer analysis, and scheduling methods, and his work has been recognized with STMicroelectronics Innovation Awards (2016–2014) and a Cisco CCNA certification. Key collaborations include projects with Google (Mediapipe Objectron for robotics), Huawei (video deblurring), and involvement in the PNRR Horizon HiCONNECTS project (2024–present). He serves on conference committees (e.g., ICAETA 2023) and has developed e-learning systems and CAD tools for STMicroelectronics.

Angelo Taibiمشاهده پروفایل

استاد

• Medical Imaging
• Biomedical Engineering
• X-ray Physics
• +۳ مورد دیگر

Angelo Taibi is a Full Professor at the Department of Physics and Earth Sciences, University of Ferrara (Italy). His research focuses on advanced medical imaging techniques, particularly in X-ray physics, phase-contrast imaging, and biosignal monitoring. He develops novel sensors for physiological measurements, computational models for hemodynamic and radiation studies, and optimization protocols for imaging systems. Research Areas: Medical Imaging (X-ray, Phase-Contrast, Spectral CT) Biomedical Sensors and Wearable Devices Computational Modeling of Hemodynamics Inverse Compton Scattering Applications Recent Publications demonstrate expertise in radiation detection, diagnostic systems, and tissue characterization. His work bridges physics, engineering, and clinical applications, with projects related to space medicine and cancer diagnostics.

• Materials Science
• Food Engineering
• 3D Printing
• +۳ مورد دیگر

Corrado Sciancalepore is a fixed-term researcher at the Department of Industrial and Systems Engineering (DISTI), University of Parma. He teaches materials science and design courses across multiple degree programs, including Sustainable Design for Food Systems and Engineering for the Food Industry. His research interests lie in materials science and engineering, particularly in advanced materials for food industry applications. He focuses on bio-based polymer composites, 3D printing technologies (FDM and VAT systems), and innovative thermal management solutions for power electronics. Recent work includes applying machine learning to optimize 3D printing parameters and developing self-adhesive sericin electrodes for biosignaling. He also investigates dynamic boronate ester networks to improve isotropy in printed components. He contributes to the Lab. of Materials and Technologies for the Food Industry and has published extensively on materials engineering topics in 2025. No scientific awards are mentioned in available data.

• Data Science
• Computer Vision
• Artificial Intelligence
• +۴ مورد دیگر

Giulia Masi is a Ph.D. candidate in Computer and Systems Engineering at Politecnico di Torino, Department of Control and Computer Science (DAUIN), specializing in data science, computer vision, and AI applications for Parkinson’s disease rehabilitation and remote monitoring. She also serves as an external lecturer and teaching assistant, contributing to Computer Science courses in the Aerospace Engineering program. University: Politecnico di Torino Department: Control and Computer Science (DAUIN) Academic Rank: Lecturer Her research integrates life sciences and technology, focusing on neurodegenerative diseases like Parkinson’s. She employs neurophysiological signals, biosignal processing, and serious games to study emotional and motor symptoms, aiming to reduce clinicians' workload through automation. Giulia’s recent publications highlight trends in RGB-D sensor validation, deep learning for hand tracking, and semi-supervised approaches for Parkinson’s assessment. These works span conferences like IEEE EMBC and journals such as Electronics and Artificial Intelligence in Medicine , emphasizing clinical AI and remote monitoring. She is a member of the SMILIES research group, which focuses on resilient computer architectures and life sciences collaborations. Her educational background includes a Master’s in Biomedical Engineering at Politecnico di Torino (2021), where her thesis automated REM sleep without atonia scoring—a critical task for early Parkinson’s detection. Prior to her Ph.D., she worked as a research fellow in the Neuroscience Department at the University of Turin, analyzing neurophysiological signals for quantitative symptom measurements.

• Chaos theory
• Compressed sensing
• Electromagnetic interference
• +۱۴ مورد دیگر

Fabio Pareschi is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino, where he conducts research in circuit architectures, embedded systems, and signal processing with applications in security, AI, and power electronics. He is affiliated with the VLSILAB research group and leads multiple high-impact research projects. Research Interests: Chaos theory and true random number generation for cryptographic applications Compressed sensing for secure and efficient signal acquisition EMI reduction techniques in DC-DC power converters Tiny machine learning and low-power embedded systems Circuit design for IoT and biomedical applications The recent articles highlight a strong trend in integrating compressed sensing with encryption, leveraging chaos-based randomness for security, and optimizing power electronics for EMI reduction. His work bridges theoretical foundations with practical hardware implementations in microelectronics and embedded systems. Scientific Awards: Best Student Paper Award (IEEE, 2005) Best Paper Award (IEEE, 2005) IEEE PRIME Gold Leaf Certificate (2019) BioCAS Transactions Best Paper Award (2019) Best Student Paper Award at EMCCompo (IEEE, 2019) Advising and Grants: He supervises multiple PhD students in the Electrical, Electronics, and Communications Engineering program. He is the Scientific Director of the CESOIA project (Non-EU International Research, 2025–2028) on low-complexity AI models, and leads the ECS4DRES project (EU-funded, 2024–2027) on resilient energy systems. He also heads a commercial research project on high-performance DC-DC converters (2022–2025). His editorial roles include Associate Editor for IEEE Transactions on Circuits and Systems and guest editorships in multiple IEEE journals. Labs and Teams: He is a key member of the VLSILAB Group (DET), which focuses on VLSI systems, embedded signal processing, and secure hardware design.

Alessandro Mengarelliمشاهده پروفایل

پژوهشگر ارشد

• Motion Analysis
• Biomechanics
• Biosignal Processing
• +۳ مورد دیگر

Alessandro Mengarelli is a Research Fellow at the Department of Information Engineering (DII) of Università Politecnica delle Marche. He holds a Ph.D. in Information Engineering (2017) from the same institution, focusing on balance and motor control in dynamic tasks under Prof. Sandro Fioretti's supervision. His research integrates biomechanics, biosignal processing, and wearable technologies, with a focus on neuromuscular control strategies and assistive systems. Key research areas include motion analysis, muscle co-contraction patterns, gait biomechanics, and the application of machine learning to biomedical data. He is actively involved in IEEE societies (EMBS, CTSoc, RAS) and the Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System (IUC BOHNES). His work spans from wearable sensor development to clinical applications in diabetic neuropathy and neuro-rehabilitation. Mengarelli's recent publications emphasize innovations in gait phase recognition, EMG-based intent detection for prosthetics, and IoT-driven health monitoring. His articles highlight advancements in sensor fusion, deep learning models for biomechanical analysis, and minimal setup solutions for practical clinical use. He has contributed as a reviewer and Guest Editor for peer-reviewed journals, reflecting his engagement in advancing the field. His research bridges theoretical models (e.g., intermittent control theory) with practical applications, aiming to improve human-machine interfaces and assistive technologies.

Maria Elena Laiمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Engineering
• Neuroengineering
• Biomedical Signal Processing
• +۶ مورد دیگر

Maria Elena Lai is a Research Fellow in Biomedical Engineering at the Department of Electrical and Electronic Engineering (DIEE) of the University of Cagliari, Italy, working on the STOPme project focused on Rett syndrome stereotypy recognition through ambient intelligence. Education: B.Sc. in Biomedical Engineering from the University of Cagliari M.Sc. student in Bioengineering (Neuroengineering and bio-ICT) at the University of Genoa Her research integrates biomedical signal processing, wearable systems, and machine learning to analyze motor/respiratory patterns in Rett syndrome, building on prior work with biosignal analysis in autistic children and 3D pediatric thoracic imaging. This demonstrates her commitment to engineering-driven healthcare innovation for neurodevelopmental disorders. Scientific Awards: None mentioned in source material. Advising and Grants: Currently engaged in the EU-funded STOPme project (PNRR MUR – M4C2 Investment 1.5) under the RAISE initiative. No student advising details provided. Research Team: Core member of the STOPme project team developing ambient intelligence solutions for Rett syndrome stereotypy termination within the RAISE framework.

• Condensed Matter Physics
• Spintronics
• Semiconductor Physics
• +۳ مورد دیگر

Dominique Persano Adorno is an Associate Professor in the Department of Physics and Chemistry at the University of Palermo's School of Basic and Applied Sciences, specializing in physics education and materials science. She teaches courses like Physics I , Physics II , and Lab of Physical Characterization and Biosignal Processing to engineering students across multiple academic years. Her research focuses on semiconductor physics, spintronics, and educational methodologies, particularly inquiry-based and 5E models. Recent publications highlight her work on: Molybdenum trioxide thin films for infrared photonics Thermo-optical properties of doped materials Monte Carlo simulations of noise-influenced systems Physics-driven interdisciplinary project learning Eco-conscious education strategies integrating sustainability She maintains active teaching evaluations and coordinates lab activities, with office hours held in Room 112 of the Physics and Chemistry department building (Viale delle Scienze, Building 18).

Salvatore Baglioمشاهده پروفایل

استاد

• Instrumentation and Measurements
• Micro and Nano Sensors
• Nonlinear Dynamics in Measurement Systems
• +۴ مورد دیگر

Salvatore Baglio is a Full Professor in the Department of Electric, Electronic and Computer Engineering at the University of Catania, where he also earned his Laurea and Ph.D. in Electronic and Electrical Engineering. He currently serves as Rector’s Delegate for Scientific and Applied Research and is a member of the Board of the Ph.D. program in Electronic and Automation Engineering. His research focuses on instrumentation and measurement systems , particularly leveraging nonlinear dynamics for enhanced sensing and micro/nano sensors for integrated applications. He also investigates smart materials for transducers and nonlinear energy harvesting for self-powered devices. His work bridges theoretical innovation with practical implementation in sensor systems. The 15 most recent representative articles reflect a strong trend in nonlinear methodologies applied to sensing and energy, with a focus on MEMS/NEMS , energy-efficient IoT nodes , and smart transducer design . These span disciplines including instrumentation, nanotechnology, and sustainable electronics, emphasizing innovation in signal detection, material integration, and power autonomy. Scientific Awards: Fellow of the IEEE Editorial and Professional Leadership: Prof. Baglio has served as Editor-in-Chief of the I&M Video Tutorials and is currently Associate Editor-in-Chief of the IEEE Transactions on Instrumentation and Measurements. He is an active member of the IEEE I&M Society AdCom, having served as VP Education (2016–2017) and currently as Executive VP (2018–2019). He is Principal Investigator on multiple national and international research projects funded by private and public institutions, focusing on innovative sensor development. Labs and Research Teams: While not explicitly named, his research is conducted within the instrumentation and sensors group at the University of Catania, likely involving interdisciplinary teams working on microsystems, nonlinear dynamics, and energy harvesting technologies.

• 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

Mimma Nardelliمشاهده پروفایل

استادیار

• Biomedical Signal Processing
• Wearable Monitoring
• Nonlinear Physiological Dynamics

Mimma Nardelli is an Assistant Professor at the University of Pisa's Department of Information Engineering and Research Center 'E. Piaggio'. Her research focuses on biomedical signal processing, wearable monitoring, and nonlinear analysis of physiological dynamics in clinical and healthy populations. She develops methods for assessing autonomic function, emotional states, and clinical conditions through multimodal biosignal analysis. She coordinates the PRIN project MOONSHINE and collaborates on EU projects including POTION and NEVERMIND. Her teaching includes Biometrics Systems, Affective Computing, and AI in Medicine. Awards include the 2017 GNB Award for her PhD thesis on HRV analysis for mood assessment. Research spans: wearable photoplethysmography validation, autonomic state characterization using multiscale entropy, cardiovascular coupling analysis, and physiological responses to affective stimuli. Applications include neonatal care, mental health monitoring, and human-robot interaction.

Pietro Aricoمشاهده پروفایل

استادیار

• Brain-Computer Interfaces (BCI)
• Bioengineering
• Signal Processing
• +۱۲ مورد دیگر

Pietro Arico is an Assistant Professor at the Department of Computer, Control and Management Engineering, Sapienza University of Rome, and Chief Technology Officer at BrainSigns. He holds a PhD in Bioengineering from University of Bologna (2014) and an M.Sc. in Biomedical Engineering from Sapienza University of Rome (2010). Biomedical Engineering Education Expertise in Brain-Computer Interfaces (BCI) Specializes in biosignal processing and machine learning His research focuses on: Passive BCI Systems: Real-time assessment of mental states (workload, attention, stress) using EEG, ECG, and other biosignals in operational environments like driving and aviation. Signal Processing Innovation: Development of algorithms for artifact removal and feature extraction in non-laboratory settings. Hybrid BCI Applications: Integration of EEG and EMG for rehabilitation systems targeting post-stroke patients. Recent work trends emphasize: Real-time mental workload monitoring in clinical and automotive contexts. Artifact correction techniques for EEG data in naturalistic environments. Neurophysiological characterization of mixed reality embodiment. Scientific awards include: 2024 - MINDTOOTH paper selected for AIIC National Conference 2014 - Award 'Massimo Grattarola' for BCI research 2014 - Scientific Prize 'I Guidoniani' for mental load studies 2013 - Finalist for Scientific Award 'I Guidoniani' He teaches Biosignal Processing , Biological System Models , and Biosignal Processing and Electromagnetic Fields in Sapienza's MSc programs in Biomedical Engineering and Medicine and Surgery HT.