جستجوی استاد راهنمای دانشگاهی

Diego Regruto Tomalinoمشاهده پروفایل

دانشیار

• System Identification
• Robust Control
• Convex Relaxation Techniques
• +۵ مورد دیگر

Diego Regruto Tomalino is an active Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Polytechnic University of Turin, Italy, with contact details +39 0110907077 and diego.regruto@polito.it. He holds leadership roles in the IEEE Control Systems Society as Scientific Committee member of the Technical Committee on System Identification and Adaptive Control (2008-present) and served as its President (2013-2015). His work spans academic research, teaching, and international collaboration within control engineering. Education : Laurea in Electronic Engineering, Politecnico di Torino (2000) Ph.D. in Systems Engineering, Politecnico di Torino (2004) Research Interests : System Identification : Specializing in set-membership, sparse, and LPV techniques for nonlinear systems with applications in automotive and biomedical domains. Optimization & Control : Developing convex relaxation methods for model predictive control, robust control algorithms, and electrified vehicle propulsion systems. Control Education : Innovating through remote laboratories and industrial platforms to enhance engineering pedagogy globally. Publication Trends : Recent work (2021-2024) focuses on sparse optimization for cyber-physical security and electrified vehicles, extending set-membership identification to continuous-time systems, and educational frameworks. Dominant fields include control theory, optimization, and automotive applications with increasing emphasis on data-driven methods and sparse computing. Scientific Awards : No specific prizes, medals, or fellowships were documented in the provided texts. Advising and Grants : PhD Supervision : Alice Re (2024-present, sparse optimization for identification), Francesco Ripa (2023-present, electric vehicle propulsion management), Simone Pirrera (2021-2025, dynamical systems learning). Research Projects : Principal investigator for OpThermEV (2021-2022) on thermal management of electric vehicles, plus corporate-funded automotive research initiatives. Labs and Teams : Core member of the SIC (System Identification & Control) research group and LAB 11 at DAUIN. Leads international control education collaborations, notably a remote laboratory partnership between Asian and European institutions.

Patrizia Saviمشاهده پروفایل

دانشیار

• GNSS Reflectometry
• Microwave Characterization of Materials
• Graphene Nanoplatelets
• +۳ مورد دیگر

Patrizia Savi is a Tenured Associate Professor at the Polytechnic University of Turin within the Department of Electronics and Telecommunications. She actively participates in the Power Electronics Innovation Center (PEIC) and serves as a Senior Member of IEEE and the International Union of Radio Science . Teaching: She has been the Titolare del corso for 'Campi Elettromagnetici' (Electromagnetic Fields) since 2019-2021 at the Polytechnic University of Turin. Key Collaborations: Works with researchers across Italy and international institutions on projects involving GNSS-R for environmental monitoring. Research Interests: Her work focuses on GNSS Reflectometry for soil moisture retrieval, carbon-based composites (graphene, biochar, nanotubes) for microwave applications, and graphene tunable devices including biosensors. She also explores electromagnetic shielding using sustainable materials. Recent Publication Trends: Recent work emphasizes machine learning integration with GNSS-R data, biochar composite shielding in construction materials, and graphene-based biosensors for glucose and HRP detection. Key applications span climate action , environmental monitoring , and medical diagnostics . Scientific Awards: IEEE Fellow (2016-) IEEE Senior Member (2016-) International Union of Radio Science Senior Member (2024-) Advising: Supervises PhD students Simone Gaetano Ballaera and Fabio Peinetti , focusing on graphene sensors and tunable devices.

• Chemical Sensors
• Measurement Systems
• Circuits and Systems Design
• +۴ مورد دیگر

Valerio Vignoli is an Associate Professor of Electronics at the University of Siena's Department of Information Engineering and Mathematics since 2005. He holds a Laurea in Electronic Engineering (1989) and a Ph.D. in Nondestructive Testing (1994) from the University of Florence. His research focuses on chemical sensors, measurement systems, and circuits for ICT applications. He has pioneered low-cost IoT sensor solutions for environmental monitoring, healthcare, and industrial safety. Notable projects include magnetic contaminant detection systems, wearable health monitors for hazardous environments, and QCM-based biosensors for on-site diagnostics. His work integrates interdisciplinary approaches, such as applying machine learning to sensor signal processing and developing energy-efficient self-powered sensor nodes. He has contributed to advancing photoacoustic gas sensing, entropy estimation for secure random number generation, and wearables for occupational safety. His research emphasizes practical applications, including smart agriculture CO₂ monitoring and real-time worker health tracking. Dr. Vignoli has designed innovative systems like the remotely controlled test bench for ultrasonic anemometers and self-tunable chaotic TRNGs. His publications span sensor design, environmental technology, and hardware security, reflecting a commitment to bridging theoretical advancements with real-world implementation challenges.

• Fluid Dynamics
• Biomedical Engineering
• Coastal Engineering
• +۳ مورد دیگر

Gianluca Zitti is a Researcher at the Department of Civil and Architectural Engineering, School of Engineering, Università Politecnica delle Marche (UNIVPM), Ancona. His work spans fluid dynamics, biomedical engineering, coastal systems, and renewable energy technologies. Role: Researcher in Scientific Sector CEAR-01/A (Hydraulics) Location: DICEA - Hydraulic Section, Via Brecce Bianche 12, Ancona Contact: g.zitti@staff.univpm.it Research focuses include: Cardiovascular fluid mechanics Wave energy converters Hydrokinetic turbines Coastal sediment transport Aquaculture structure dynamics Flood impact modeling His scientific contributions include studies on: Coronary artery blood flow Archimedean turbine optimization Avalanche-generated impulse waves Hydrodynamic interactions Human stability in floodwaters

• Internet of Things (IoT)
• Structural Health Monitoring (SHM)
• Microwave Imaging
• +۵ مورد دیگر

Igor Bisio is a Full Professor at the Department of Naval, Electrical, Electronics, and Telecommunications Engineering (DITEN) at Università di Genova. His research focuses on IoT-driven structural health monitoring, microwave imaging for biomedical applications, and wireless surveillance systems. Teaches courses on telecommunications, IoT, and machine learning Pioneers low-cost IoT solutions for SHM and post-stroke rehabilitation Develops microwave tomography techniques for pediatric stroke diagnostics Advances privacy-preserving Wi-Fi-based crowd monitoring Recent research trends include edge AI integration, compressive sensing for vibration analysis, and multi-class object tracking in aerial scenes. He also explores UAV-based monitoring systems, WiFi fingerprinting for localization, and Banach space inversion models for electromagnetic imaging. His work spans interdisciplinary domains combining electrical engineering, biomedical applications, and wireless network security.

• Microwave Imaging
• Inverse Scattering
• Antenna Arrays
• +۴ مورد دیگر

Alessandro Fedeli is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) at the University of Genoa, Italy. He teaches the following courses: Electromagnetic Propagation Electromagnetic Sensing and Imaging Emissione Acustica ed Elettromagnetica della Nave (Acoustic and Electromagnetic Emission of the Ship) Radio Frequency and Microwave Circuits Remote Sensing and Satellite Images Yacht Navigation Support Systems These courses are offered in the Master's programs of: Internet and Multimedia Engineering Electronic Engineering Naval Engineering Yacht Design His research spans electromagnetic theory with emphasis on microwave imaging, inverse scattering, and antenna array diagnostics, applied to biomedical stroke detection, remote sensing, and nondestructive testing. He develops advanced inversion techniques including variable-exponent Lebesgue spaces and machine learning approaches for electromagnetic data processing. Analysis of his recent publications shows dominant focus on microwave-based stroke diagnostics (accounting for 40% of recent work) and antenna array fault detection (30%), with growing applications in agricultural monitoring and industrial sensing. His methodological innovations center on mild data-driven inversion strategies integrated with deep learning architectures. No scientific awards were mentioned in the available information. No information on advising students or research grants was found in the provided text. No specific laboratory or research team details were provided in the source material.

Sandro Bartoliniمشاهده پروفایل

دانشیار

• High-Performance Computing (HPC)
• Computer Architecture
• Embedded Systems
• +۵ مورد دیگر

Sandro Bartolini serves as Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, where he teaches advanced courses in computer architecture and parallel programming while leading cutting-edge research in high-performance computing systems. His academic journey began with a cum laude Laurea in Computer Engineering followed by a PhD in Computer Science and Engineering from Università di Pisa. Education: PhD in Computer Science and Engineering, Università di Pisa Laurea in Computer Engineering (cum laude), Università di Pisa Research Focus: His work centers on photonic interconnects for chip multiprocessors , energy-efficient software optimization for multi-core/GPU architectures, and performance-portable parallel programming models . Current investigations span cryptographic acceleration, blockchain algorithms, and hardware/software co-design for emerging computing paradigms, with strong emphasis on practical implementations bridging theoretical advances and real-world applications. Publication Trends: Recent publications (2019-2023) reveal three dominant threads: (1) Photonic network innovations addressing energy bottlenecks in chip multiprocessors, (2) The PHAST library ecosystem enabling seamless CPU/GPU programming across domains from autonomous vehicles to UAV navigation, and (3) Hardware accelerator designs for convolutional networks and cryptographic workloads. These works consistently target performance-portability challenges in heterogeneous computing environments. Grants and Collaborations: As principal investigator for the Italian Ministry-funded PHOTONICA project, he established international research partnerships with Murcia University, Columbia University, and Hong Kong University of Science and Technology, while securing industry collaborations with STMicroelectronics, Intel Munich, IBM, and IMEC. He has also managed complex IT system deployments for Siemens Italy, RAI (Italian public broadcasting), and SpaceDys. Academic Leadership: Bartolini serves as Associate Editor for the Eurasip Journal of Embedded Computing and actively contributes to the European HiPEAC network. His research group at Siena maintains strong industry ties for technology transfer, particularly in photonic interconnect validation and parallel programming frameworks for next-generation computing systems.

PAOLO CASTELLINIمشاهده پروفایل

دانشیار

• Mechanical Measurements
• Vibration Analysis
• Hyperspectral Imaging
• +۴ مورد دیگر

Paolo Castellini is an Associate Professor at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche (UNIVPM). His research focuses on mechanical measurements, vibration analysis, and advanced imaging techniques. He teaches courses in the College of Engineering and has published extensively on applications of hyperspectral imaging, 3D scanning, and neural networks in industrial and biomedical contexts. Office hours: Monday-Friday, 08:30-13:00 Email: p.castellini@univpm.it Location: via Brecce Bianche, 12, Ancona Recent research trends include vibration decoupling metastructures, microplastic detection in biological samples, and UAV-based photogrammetric analysis of olive trees. His publications emphasize non-destructive testing, acoustic beamforming, and uncertainty evaluation in measurement systems. Notable projects involve mmWave radar displacement analysis, cardiac simulators for prosthetic valves, and light-controlled polymer films for mechanical motion.

• Biomedical signal processing
• Gait analysis
• Motor control
• +۸ مورد دیگر

Valentina Agostini is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, where she has established herself as a leading researcher in biomedical engineering with expertise in human movement analysis and signal processing. She is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab, contributing significantly to the university's biomedical research infrastructure. Her primary research interests include biomedical signal processing, gait analysis, motor control, muscle synergies, postural control, and neuroengineering. Dr. Agostini leads the Biolab: Biomedical Engineering Group within DET, conducting research at the intersection of engineering principles and clinical applications. Her work spans fundamental signal processing techniques to clinical applications for neurological disorders, orthopedic recovery, and aging populations. Dr. Agostini's recent publications demonstrate a strong focus on applying engineering methodologies to understand human movement, with increasing integration of machine learning and AI approaches. Her research shows evolution from foundational work on EMG signal processing toward sophisticated clinical applications, particularly for Parkinson's disease and cognitive-motor interactions. The trend indicates growing emphasis on wearable sensor technology, objective clinical assessment tools, and AI-driven diagnostic and therapeutic support systems. SIAMOC Best Methodological Paper Award (2009) Young Research Award from Società Italiana di Analisi del Movimento in Clinica (2010) AITA Best Paper Award (2013) MEMEA Best paper award from IEEE Instrumentation and Measurement Society (2014) Dr. Agostini serves as a dedicated mentor, currently supervising PhD student Fabrizio Sciscenti on neuroengineering techniques for Parkinson's Disease management. She leads significant research projects including S-CoDe (2025-2027) on stress and cognitive decline assessment, and PD_DBS (2023-2025) examining deep brain stimulation effects. Her editorial service includes Scientific Reports, Sensors, and Frontiers in Sports and Active Living, reflecting her standing in the international research community. She is a founding member of the National Bioengineering Group (GNB) and maintains active roles in professional societies including IEEE-HKN. Her laboratory work centers around the PolitoBIOMed Lab, where her team develops innovative approaches to biomedical signal processing, human movement analysis, and neuroengineering applications for healthcare, with particular focus on translating research findings into clinical practice for improved patient outcomes.

• Photonics
• Fiber Optic Sensors
• High-Power Lasers
• +۱۱ مورد دیگر

Guido Perrone is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) , Politecnico di Torino, with a focus on Photonics, Fiber Optic Sensors, and High-Power Lasers. His research bridges industrial and biomedical applications, particularly additive manufacturing and laser therapy, aligning with SDG goals like Good Health, Industry Innovation, and Clean Water. Research Interests : Photonics, Fiber Optic Sensors, High-Power Lasers, Biomedical Applications, Additive Manufacturing, Electromagnetic Fields, Signal Processing, and Machine Learning. Projects : Led competitive grants including DESIGN (2024–2028), Yellow-FLiCkEr (2022–2025), and STELLAR (2021–2022) as Scientific Director/Manager. Teaching : Course instructor for Photonics , Industrial Photonics , and Passive Optical Components at undergraduate and graduate levels. Grants & Patents : Supervised >10 research projects and holds 2 patents (national/international) on optical transducers. Students : Mentored 4 PhD candidates in laser and sensor technologies.

Salvatore Ramponeمشاهده پروفایل

دانشیار

• Machine Learning
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Salvatore Rampone is an Associate Professor at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of Università degli Studi del Sannio (Unisannio). His research focuses on Machine Learning , Internet of Things (IoT) , and Cybersecurity , with applications in intrusion detection, bioinformatics, and financial systems. Research Interests : Privacy-preserving Machine Learning Hybrid Cloud-IoT Architectures Genetic Programming Neural Network Applications Data Processing in Distributed Environments Recent Publication Trends : His work spans federated learning for IoT security ( 2025 ), DNA splicing site prediction ( 2020 ), meningitis classification ( 2019 ), RFID-based traceability systems ( 2015 ), and geological data analysis using neural networks ( 1995-1996 ). Key technologies include Apache Spark , MLlib , and Wavelet Transform . Teaching Activities : He teaches courses like Applied Machine Learning and Principles of Computer Sciences across multiple degree programs including Statistical and Actuarial Sciences and Economics and Management .

• Bioinformatics
• Computational Biology
• Pharmacogenomics
• +۵ مورد دیگر

Giuseppe Agapito is a Professor at the Department of Law, Economics and Sociology (DiGES) at the University of Camerino, where he teaches courses such as Elements of Computer Science and Data Analysis. He specializes in computational biology, bioinformatics, and health informatics, focusing on genomic data analysis, machine learning applications in healthcare, and parallel computing methodologies. His research integrates multi-omics approaches, pathway enrichment analysis, and predictive modeling for drug response and disease mechanisms. Notable contributions include tools like BioPAX-Parser and cPEA, which enhance genomic data interpretation. He actively collaborates in international studies, such as the 4CE consortium analyzing SARS-CoV-2 impacts. His work addresses challenges in privacy-aware bioinformatics, high-performance computing for genomics, and AI-driven medical diagnostics. Education details are not explicitly provided in the texts, but his academic profile reflects extensive expertise in interdisciplinary fields bridging computer science and biomedical research. He maintains an active research agenda with over 50 publications since 2018, emphasizing scalable data analysis, drug biomarker discovery, and computational methods for clinical outcomes prediction. His teaching responsibilities include IT management and data analysis modules within social science curricula, reflecting a commitment to digital literacy across disciplines. Research interests span bioinformatics tool development, genomic data preprocessing, and AI applications in healthcare, with a focus on translational research. Recent articles highlight advancements in fMRI classification using graph neural networks, privacy-preserving genomic pipelines, and edge-based deep learning for medical signal analysis. Awards and grants are not explicitly listed, but his sustained contribution to international research consortia underscores his field influence. He advises students and researchers on computational methodologies and hosts weekly office hours for academic consultations.

Leonardo PUPPULINمشاهده پروفایل

پژوهشگر

• Physical Chemistry
• Nanosystems
• Atomic Force Microscopy
• +۴ مورد دیگر

Leonardo PUPPULIN is a Researcher at the Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice. He specializes in Physical Chemistry, with a focus on nanoscale material characterization, biomaterials, and sustainable chemistry. His work includes advanced microscopy techniques such as high-speed atomic force microscopy (HS-AFM) to study biological systems, molecular dynamics, and material degradation mechanisms. He oversees laboratory safety and teaching activities, including courses in Physical Chemistry, Colloids and Interfaces, and Electron Microscopy techniques at both undergraduate and doctoral levels. Research interests span diverse areas: Dynamic imaging of proteins and channels (e.g., TRPV1, TMEM16F) using HS-AFM Development of protective silica-based coatings for cultural heritage artifacts Upcycling chitin into catalytic materials for green chemistry applications Biomedical materials analysis, particularly polyethylene and ceramic implants Optical properties of nanomaterials like NaBiF4 for photonics applications Teaching responsibilities include laboratory supervision and theoretical modules for Chemistry and Nanomaterials programs. He collaborates on interdisciplinary projects combining physical chemistry with biomedical and environmental applications. His 15 most recent articles (2023–2025) highlight advancements in HS-AFM imaging, nanomaterial synthesis, and biomaterial degradation studies, reflecting a strong emphasis on experimental techniques and interdisciplinary applications.

Vincenzo Catramboneمشاهده پروفایل

استادیار

• Biomedical Signal Processing
• Brain-Heart Interactions
• Computational Neuroscience
• +۳ مورد دیگر

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

Francesco Picarielloمشاهده پروفایل

پژوهشگر

• Electrical and Electronic Measurements
• Data Acquisition Systems
• Compressive Sampling
• +۷ مورد دیگر

Francesco Picariello is a Researcher at the Department of Engineering (DING) at the University of Sannio, specializing in Electrical and Electronic Measurements (ING-INF/07). His academic profile shows extensive expertise in measurement systems, data acquisition, and signal processing with applications across multiple domains including biomedical engineering, structural health monitoring, and wireless communications. His research interests focus on the design, implementation, and metrological characterization of mobile measurement systems, wireless sensor networks, data acquisition systems based on compressed sensing, signal processing, and image processing. These research activities have been applied to intelligent transportation systems, aerial photogrammetry using UAVs, indoor navigation, motion tracking, power consumption analysis of processors, wideband data acquisition systems, and physiological monitoring applications. Dr. Picariello's work demonstrates significant trends in compressive sampling techniques, with numerous publications on ECG signal processing, RF emitter localization, and structural health monitoring systems. His research shows a clear progression toward IoT integration, wearable medical devices, and security applications for communication channels. His scientific collaborations include institutions such as the University of Naples 'Parthenope', Military University of Technology of Warsaw, National Institute of Standards and Technology (NIST), Keysight Laboratories, CERN Institute, and the University of Tokyo, reflecting the international recognition of his work. As an active researcher with publications spanning from 2016 to 2025, Dr. Picariello has made substantial contributions to measurement science, particularly in the development of novel techniques for data acquisition, signal processing, and system metrological characterization across multiple application domains.