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Maurizio ValleView profile

Professor

• Electronic Engineering
• Embedded Systems
• Machine Learning
• +4 more

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.

Francesco ZanichelliView profile

Associate Professor

• Distributed Systems
• Service-Oriented Peer-to-Peer Middleware
• Cloud Systems for IoT
• +10 more

Francesco Zanichelli is an Associate Professor at the Department of Engineering and Architecture, University of Parma, where he teaches Information Systems for Master's in Computer Engineering and Operating Systems for Bachelor's in Computer, Electronics, and Telecommunications Engineering. He also teaches Industrial Software Development Technologies in Information Systems Engineering. PhD in Information Technology (University of Parma, thesis: Programming Autonomous Robots) Industrial Robotics experience (IBM Fellow) Mobile Robotics research (University of Florida) His research spans: Intelligent robotic systems: software architectures, sensor-based interaction, real-time scheduling algorithms Distributed systems: peer-to-peer middleware, cloud-IoT integration, predictive maintenance Location-based services: blockchain-secured privacy, network-aware distribution Performance evaluation via simulation, PlanetLab testbed, and prototyping He leads the DSG distributed systems research group and participates in national/international projects (FP7, NATO, CNIT). He co-founded spin-offs for vehicle multimedia systems (Etheria Srl) and digital payment solutions (Simplycity Srl).

Davoli LucaView profile

Assistant Professor

• Internet of Things
• Telecommunications
• Machine Learning
• +6 more

Luca Davoli is a Fixed-term Assistant Professor at the University of Parma , Department of Engineering and Architecture. His research focuses on the integration of Internet of Things (IoT) technologies with Machine Learning and Smart City applications.

• Hydraulic Engineering
• Flood Risk Management
• Hydrology
• +3 more

Susanna Dazzi is a Fixed-term Researcher at the Department of Engineering and Architecture, University of Parma, Italy. Her work focuses on hydraulic engineering, flood risk management, and computational modeling, leveraging advanced techniques like physics-informed neural networks and GPU acceleration for real-time flood prediction. Key Research Areas: Flood hazard estimation, levee breach dynamics, dam-break scenarios, 2D hydraulic modeling, and sediment transport analysis. Teaching: Delivers courses on Hydraulic Infrastructures and Hydraulic Protection of the Territory for Master's Degree programs in Civil Engineering. Publications: Develops data-driven models (e.g., FloodSformer) for real-time flood forecasting and investigates hydrodynamic interactions with infrastructure. Contact: Email: susanna.dazzi@unipr.it ; Office: Science Area Park, 181/A, 43124 Parma, Italy.

• Neuropsychology
• Cognitive Neuroscience
• Physical Activity and Cognitive Efficiency
• +4 more

Patrizia Turriziani is a Full Professor at the University of Palermo in the Department of Psychological, Pedagogical, Physical Exercise and Training Sciences . She serves as the Delegate for Supporting Neurodiversity and contributes to institutional initiatives like CE.N.DIS (University Center for Disability and Neurodiversity) and the ARTEMISIA Center for Gender Studies. Her research is centered in Neuropsychology and Cognitive Neuroscience , with a focus on sensory processing, memory, and physical activity's cognitive effects. Institutional Roles: Delegate for Neurodiversity, CE.N.DIS, ARTEMISIA Center, NeuroTeam srl Labs: Neuropsychology Lab Research Interests include cognitive rehabilitation, sensory-motor integration, neurodevelopmental disorders, and neuromodulation techniques like rTMS and tDCS. Her recent publications highlight stroke recovery , Alzheimer's interventions , and sensory processing in neurodiverse populations. She also investigates spatial cognition and memory enhancement through prism adaptation and digital therapeutics. Key Collaborations involve the Neuropsychology Lab and translational research with the NeuroTeam srl initiative. Her work spans both clinical and developmental neuropsychology , integrating applied neuroscience with educational and rehabilitation frameworks.

• Embedded Systems Design
• Low-Power Design
• VLSI Architecture for Image Processing
• +4 more

Pasquale Corsonello is a Professor of Electronics at the Department of Informatics, Modeling, Electronics and System Engineering (DIMES) , University of Calabria. He has held academic positions at the University of Reggio Calabria and the University of Rochester (Adjunct Associate Professor). His career spans over three decades in digital electronics, VLSI design, and low-power systems. Education: Master's in Electronic Engineering, University of Naples “Federico II” (1988) Key Roles: Editor-in-Chief (Journal of Low Power Electronics), Senior Area Editor (IEEE Transactions on Circuits and Systems II), Steering Committee Member (IEEE Transactions on VLSI Systems) Research interests include: Embedded systems and low-power design for IoT VLSI architectures for image processing and neural networks FPGA-based accelerators for real-time applications Quantum-dot cellular automata (QCA) circuits His recent publications focus on energy-efficient FPGA implementations, approximate computing for imaging, and QCA-based arithmetic circuits. He has co-authored over 180 technical articles and holds three patents. Awards : BEST ASSOCIATE EDITOR IEEE CASS AWARD (2016) GOLDEN LEAF Certificate (PRIME 2019) Multiple BEST PAPER AWARDS at ICECS, CENICS, and PRIME Top 25 Downloaded Articles (IEEE Transactions on VLSI Systems) Leadership : Coordinated PhD programs in Information and Communication Technologies Directed research units in projects exceeding €8M in funding Member of editorial boards for IEEE Transactions and Electronics journal He leads the Nanoelectronics and Microsystems research group , which integrates material characterization, IC design, and system-level electronics for applications in power systems and photovoltaics.

• Robotics
• Automatic Control
• Human-Robot Interaction
• +5 more

Prof. Cesare Fantuzzi is a Full Professor at the Department of Engineering Sciences and Methods , University of Modena and Reggio Emilia. His expertise lies in robotics, automatic control, and human-robot interaction , with a focus on Industry 4.0/5.0 applications . He teaches courses in Industrial Robotics, Automatic Control, and Industrial System Control , emphasizing practical implementation in real environments. His research spans collaborative robotics, fault diagnosis systems, adaptive interfaces, and digital twin technology . Notable projects include IOT-enabled diagnostics for welding cobots , high-velocity robotic programming architectures , and smart AGV traffic management . Publications cover control barrier functions, passivity-based interaction methods, and universal design for industrial HMIs , often in collaboration with European research teams. Recent work explores self-configuring BLE networks , adaptive training systems , and natural gesture-based robot control . He employs Microsoft Teams for teaching materials and open-source IoT platforms in research implementations.

Siqi WuView profile

Assistant Professor

• Computational Social Science
• Web Data Analysis
• Social Media Research
• +7 more

Siqi Wu is an Assistant Professor of Information and Library Science in the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington. Previously, they were a postdoc research fellow in the Center for Social Media Responsibility at the University of Michigan School of Information. Dr. Wu is a computational social scientist who collects, models, and analyzes web data at scale, with research focusing on understanding social phenomena through large-scale empirical measurements and designing next-generation sociotechnical systems via data-driven policies and interventions. Dr. Wu's educational background includes: Ph.D. in Computer Science from the Australian National University M.S. in Information Technology from the University of Melbourne B.E. in Electronics Engineering from Tianjin University Dr. Wu's research spans computational social science, large-scale web data analysis, and social media systems. Their work examines YouTube recommendation networks, Twitter data analysis, prevalence estimation techniques, and cross-platform attention dynamics. Recent projects investigate user control over recommendations, harmful content detection, and cross-partisan communication patterns, combining computational methods with social science theories to understand algorithmic influence on online experiences and develop practical interventions. Dr. Wu's publications demonstrate consistent excellence in social media analysis, with particular expertise in measuring attention dynamics across platforms, estimating class prevalence using black box classifiers, and understanding recommendation systems. Their work bridges technical innovation with social science questions, resulting in practical implications for platform design and policy across YouTube, Twitter, and other social media ecosystems. Notable recognitions include: Google PhD Fellowship (2018) ICWSM Best SPC (2022-2024) CSCW 2019 Best Paper Honorable Mention (top 5%) ICWSM 2021 Spotlight Paper selection (top 8) Dr. Wu actively mentors students interested in computational social science, seeking those with strong programming skills, data analysis experience, and passion for understanding social phenomena through computational methods. They serve on program committees for ICWSM, CSCW, and CHI, and their research has practical applications for social media platform design, content moderation policies, and understanding information ecosystems. Dr. Wu has developed several software tools including pyquantifier for prevalence estimation and tools for Twitter and YouTube data collection. Dr. Wu leads research on social media analysis with focus on YouTube and Twitter ecosystems, developing methods to understand recommendation systems, user engagement patterns, and cross-platform dynamics. Their work involves collecting and analyzing large-scale datasets to inform platform design and policy decisions related to algorithmic transparency and user control.

• Computational Chemistry
• Physical Chemistry
• Materials Science
• +3 more

Alfonso Pedone is an Associate Professor at the Department of Chemical and Geological Sciences , University of Modena and Reggio Emilia. His research focuses on computational chemistry approaches to understanding oxide glasses, including silicates, borosilicates, and nuclear waste materials, through molecular dynamics simulations and machine learning potentials. Research Interests : Computational materials science, spectroscopy, glass structure-property relationships, quantum chemistry of minerals, and machine learning applications in material modeling. Teaching : Offers advanced courses in Physical Chemistry I , Energetics and Chemical Equilibrium , and Molecular Spectroscopy for chemistry and sustainable chemistry degree programs. Technical Expertise : Specializes in Density Functional Theory (DFT) calculations, metadynamics, and reactive molecular dynamics for surface interactions and crystallization studies. Collaborative Work : Co-author on studies involving ceria polishing mechanisms, iron toxicity modeling, and machine learning potential benchmarking for industrial applications. Publications : Recent work examines pressure-induced glass densification, dispersion interactions in machine learning potentials, and predictive modeling of glass crystallization pathways.

• Geometry
• Graph Theory
• Combinatorics
• +2 more

Simona Bonvicini is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences, University of Modena and Reggio Emilia, Italy. Her research focuses on geometry, combinatorics, graph theory, and algebraic structures, with a particular emphasis on cycle decompositions, edge-colorings, and symmetric graph designs. She teaches Geometry for Mathematics students and Mathematics and Computer Science for Geological Sciences students, emphasizing affine/Euclidean geometry, linear algebra, and algorithmic problem-solving. Her work spans topics like Hamilton-Waterloo problems , Kirman Triple Systems , and 1-factorizations , often involving collaborations with researchers such as Marco Buratti and Gloria Rinaldi. She has explored automorphism groups, critical graphs, and applications to DNA self-assembly, though no specific scientific awards are mentioned in the provided data. Her recent publications address even cycle decompositions, palette indices, and structural graph properties. Teaching methods include in-person lectures, digital platforms like Moodle, and problem-solving exercises. She is available for student reception by appointment.

• Evolutionary Game Theory
• Membrane Computing
• Computational Biology
• +4 more

Matteo Cavaliere is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences, University of Modena and Reggio Emilia. His research bridges Evolutionary Game Theory , Membrane Computing , and Computational Biology , focusing on cooperation dynamics in structured populations, algorithmic modeling of biological processes, and network resilience mechanisms. Key Research Themes: Strategic cooperation in social/biological systems, information-driven network dynamics, and synthetic biology applications. Teaching Responsibilities: Courses in Algorithms and Problem Solving , Game Theory , and Digital Communication Tools at graduate and undergraduate levels. His recent publications emphasize evolutionary stability through network rankings, cyber-physical cooperation frameworks , and multi-scale biological modeling using agent-based simulations. Collaborative work spans interdisciplinary domains including epidemiology, tissue morphogenesis, and distributed cellular computing, with no scientific awards explicitly mentioned in the provided texts.

• Computer Architecture
• High Performance Computing
• Parallel Programming
• +5 more

Andrea Marongiu is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specifically affiliated with the Mathematics department. He maintains an active research profile while teaching multiple courses in computer architecture and parallel systems. His research interests span computer architecture, high performance computing, parallel programming, and embedded systems. Marongiu focuses particularly on memory systems, heterogeneous computing architectures, FPGA-based acceleration, and real-time performance analysis. His work bridges theoretical foundations with practical implementation challenges in modern computing systems, with special attention to predictable execution models and quality of service guarantees. Analysis of his recent publications reveals a strong emphasis on memory bandwidth management in heterogeneous systems, particularly focusing on FPGA-based architectures and multicore SoCs. His research trajectory shows consistent work in memory interference analysis, PREM (Predictable Execution Model) scheduling techniques, and fine-grained QoS control mechanisms. The publications demonstrate a progression from general parallel programming concepts toward increasingly specialized techniques for resource-constrained environments like autonomous vehicles and edge computing devices. Marongiu teaches several advanced computer science courses including Computer Architecture I & II, Compilers, High Performance Computing, and Electronic Calculators across multiple degree programs. His teaching approach emphasizes both theoretical foundations and practical implementation, with a focus on RISC-V architecture and modern parallel programming techniques. The course materials indicate he incorporates hands-on laboratory work as an essential component of his pedagogy, particularly in areas like compiler construction and parallel programming.

• Multimedia Security
• Multimedia Forensics
• Adversarial Machine Learning
• +7 more

Tiziano Bianchi is a Full Professor in the Department of Electronics and Telecommunications at Politecnico di Torino (Polytechnic of Turin), Italy. He serves as the Course Coordinator for the Master's Degree in ICT Engineering for Smart Societies and is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. Previously, he was an Assistant Professor at the same institution starting in 2012, having joined from the University of Florence where he worked as a Research Assistant from 2005 to 2012. Dr. Bianchi's research focuses on multimedia security technologies, with particular expertise in multimedia forensics, signal processing in the encrypted domain, and security aspects of compressed sensing. His work spans adversarial machine learning, image and video forensics, deep learning for video compression, secure authentication based on deep learning, and satellite image compression. He has made significant contributions to privacy-preserving data processing through compressed sensing techniques. His recent publications demonstrate a strong emphasis on applying deep learning to solve complex problems in image processing, security, and data compression. The research shows a clear trajectory toward efficient, secure, and privacy-preserving processing techniques, particularly for resource-constrained environments like wearable devices and satellite systems. Among his notable recognitions are the Journal of Visual Communication and Image Representation Best Editor of 2022 Award, The SIGMM Test of Time Paper Honorable Mention in Multimedia Security and Privacy, and the 2019 Best Paper Award from IEEE MultiMedia. He has also received multiple editorial awards for his work as Senior Area Editor for the Elsevier Journal of Visual Communication and Image Representation and Associate Editor for the IEEE Transactions on Information Forensics and Security. Dr. Bianchi is the co-founder of ToothPic, a startup offering breakthrough technologies for camera identification, and has co-invented four patents related to cryptographic key obfuscation, user authentication, and camera recognition techniques. He has authored over 100 papers in international journals and conference proceedings, demonstrating sustained scholarly productivity throughout his career.

• Electrical Engineering
• Electromagnetic Compatibility
• Signal Integrity
• +3 more

Ivano Adolfo Maio is a Full Professor at the Department of Electronics and Telecommunications (DET) within the Polytechnic University of Turin's College of Electronic, Telecommunications and Physics Engineering. He holds the Scientific Disciplinary Sector IIET-01/A - Electrical Engineering under Area 0009 (Industrial and Information Engineering). Teaching: Course instructor for Circuit Theory and Applications (2019-2024) and collaborator in Electrical Engineering courses Research: Focused on compact dynamical modeling and electromagnetic compatibility (EMC) through DET's EMC Group Projects: Scientific Director for commercial contracts addressing DSL physical layer design and signal integrity in electronic applications His work combines computational methods for circuit simulation, electromagnetic interference analysis, and signal degradation modeling in transmission systems. Publications span nonlinear dynamics, time-domain analysis, and numerical Laplace transform applications.

• Antennas
• Metamaterials
• Cloaking Technology
• +6 more

Ladislau Matekovits is an Associate Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin, Italy. He holds a PhD in Electronic Engineering from the same university (1998) and has been affiliated with DET since post-doctoral fellowship in 1995. Education: Electronic Engineering (1992) from Institutul Politehnic din Bucuresti, Romania PhD: Electronic Engineering (1998) from Polytechnic University of Turin Research Interests: His work focuses on advanced numerical analysis of printed antennas, metamaterials, cloaking, and reconfigurable antenna systems. He employs integral equation methods for full-wave analysis, optimization techniques, and biosensor development. Recent Publications Trends: Recent works address sub-THz metamaterials, bound states in continuum via Babinet principle, neural network modeling for antennas, and high-gain antenna designs. These span applications in 6G communication, satellite systems, and medical diagnostics. Scientific Recognition: Awardee of the 2018 Motohisa Kanda Award (IEEE EMC Society), 2015 IEEE Access Editor of the Month, and 2013 International Collaboration Award (Australian Research Council). Editorial Roles: Associate Editor for IEEE Antennas and Wireless Propagation Letters (2017-), IET Microwaves Antennas & Propagation (2016-), IEEE Access (2014-) Conference Leadership: General Chair of 11th International Conference on Body Area Networks (2016) Research Projects: Currently leads the CanDia project (Wireless Healthcare for Oral Cancer Diagnosis) funded under PNRR Mission 4 (2025-2028) and commercial projects on environmental monitoring systems.