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Luigi Gianpio Di Maggio is a Fixed-Term Assistant Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Politecnico di Torino, specializing in artificial intelligence applications for mechanical systems. He has held visiting researcher positions at Universitat Politècnica de Catalunya (2025) and Universidad Politécnica de Valencia (2025), and serves on the teaching council for Mechanical Engineering programs. Research Focus: Industrial bearings, AI-driven fault detection, signal processing, and predictive maintenance Collaborations: Active in the ISED research group (Industrial Systems Engineering and Design) His recent work applies deep learning and generative models to mechanical diagnostics, with recognition including the Premio 'A. Capocaccia' (2023) and Applied Sciences Best Paper Award (2025). He serves on editorial boards and teaches advanced courses in machine design and structural mechanics. Selected Awards Premio 'A. Capocaccia' (2023) Applied Sciences Best Paper Award (2025) Teaching contributions include collaborative roles in Politecnico di Torino's Mechanical Engineering programs since 2019, covering topics like machine construction and structural mechanics.

• Artificial Intelligence
• Bearings
• Deep Learning
• +7 more

Giuseppina Ambrogio is an Associate Professor at the Department of Mechanical, Energy and Management Engineering of the University of Calabria, Italy. She has been Coordinator of Management and Industrial Engineering courses since 2020 and serves as Scientific Responsible of the "Technology and Sustainable Manufacturing Lab Section" within MechLab. With habilitation as Full Professor since 2022, her academic career spans 19 years at the same institution. Research Interests focus on: Incremental sheet forming and superplastic forming Sustainable manufacturing technologies FEM-AI hybrid optimization techniques Biomedical prostheses manufacturing Lightweight material characterization She has coordinated multiple EU/IT-funded projects like ISIDE and FORMAE-BIO , and co-supervised numerous Marie Curie researchers. Her 20-year scientific production includes 119 SCOPUS-indexed papers (H-index 22) and 120+ master thesis supervisees. International Collaborations include Adjunct Professor at Brandenburg University of Technology and visiting researcher at RWTH Aachen University. She serves as Program Chair for ISM conference tracks and CoChair for ESAFORM symposia.

• Incremental sheet forming process
• Manufacturing design by innovative approaches
• Lightweight design and material characterisation
• +2 more

Roberto Pierdicca is a Researcher in Geomatics (scientific sector CEAR-04/A) at the Department of Civil, Building and Architectural Engineering, College of Engineering, Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. His academic career focuses on the intersection of geospatial technologies, artificial intelligence, and cultural heritage documentation, with a strong emphasis on practical applications in environmental monitoring and preservation. Dr. Pierdicca's research interests center around advanced geomatics techniques including LiDAR technology, UAV-based remote sensing, and 3D modeling for cultural heritage preservation and environmental applications. His work demonstrates a strong interdisciplinary approach, bridging geospatial sciences with computer vision, machine learning, and environmental engineering to develop innovative solutions for complex documentation and monitoring challenges. Analysis of his publication record from 2023-2025 reveals a clear research trajectory focused on integrating artificial intelligence with traditional geomatics techniques. His work spans multiple domains including cultural heritage documentation (particularly for sites in Syria, Uzbekistan, and Italy), environmental monitoring (floodplains, vegetation recovery, olive groves), and forestry management. A notable trend is the increasing sophistication of AI applications in his work, moving from basic classification to complex generative models and context-aware systems. Dr. Pierdicca is actively involved in multiple research projects that combine geospatial data acquisition with advanced computational methods. His work frequently appears in interdisciplinary contexts, suggesting strong collaborations across engineering, computer science, and cultural heritage disciplines. The practical applications of his research are evident in numerous case studies addressing real-world challenges in heritage preservation, environmental monitoring, and precision agriculture.

• Geomatics
• Remote Sensing
• Cultural Heritage Documentation
• +5 more

Dr. Domenico Potena is an Associate Professor at the Department of Information Engineering within the College of Engineering at Università Politecnica delle Marche (UNIVPM), Italy. His academic work spans interdisciplinary research at the intersection of data science, semantic modeling, and educational systems. He actively contributes to advancing knowledge through publications in high-impact venues.

• Machine Learning
• Semantic Data Modeling
• Process Mining
• +5 more

Raffaella Burioni is a Full Professor of Theoretical Physics in the Department of Mathematics, Physics and Computer Science at the University of Parma. She serves as Chair of the Non-Linear and Statistical Physics Division of the European Physical Society (EPS) and co-founded the Italian Society of Statistical Physics (SIFS), where she holds the position of Vice President. Her academic leadership includes directing the Ph.D. School in Physics and previously managing quality assurance for the Master's program in Physics (2017-2023). Her educational background includes an MS in Physics with distinction from the 2nd University of Rome and a PhD in Theoretical Physics from the University of Rome 'La Sapienza'. Postdoctoral experience spans the Theoretical Physics Laboratory of the École Normale Supérieure in Paris, the University of Milan, and the National Institute for the Physics of Matter (INFM). Prof. Burioni's research centers on equilibrium and non-equilibrium statistical physics, with deep expertise in graph theory, complex networks, random walks, and stochastic processes. She pioneers interdisciplinary applications to biological systems, neuroscience, and machine learning. Her work on rare events and anomalous diffusion has established fundamental principles like the 'single big jump' mechanism in transport phenomena. Recent investigations bridge statistical physics with neural network theory, examining kernel renormalization and feature learning in deep architectures. Analysis of her 15 most recent publications (2022-2025) reveals three dominant trends: (1) Theoretical advances in rare event statistics for jump processes and extreme value theory, (2) Network-based epidemic modeling incorporating adaptive temporal dynamics and simplicial structures, and (3) Machine learning physics connecting neural network theory to statistical mechanics through Bayesian effective actions and kernel methods. Her work consistently demonstrates how statistical physics principles solve complex problems across disciplines. Her scientific accolades include: Two-time recipient of the Enrico Persico Prize from the Accademia Nazionale dei Lincei Fellow of the Institute for Scientific Interchange (ISI) since 2014 American Physical Society Outstanding Referee (2018) Fellow of the European Centre for Living Technology (2020) As Director of the Ph.D. School in Physics, she mentors doctoral candidates while serving on editorial boards for Physical Review E, JSTAT, and Journal of Physics A. Her research is supported by international collaborations with institutions including the Kavli Institute for Theoretical Physics, Max Planck Institute, and Ben-Gurion University, evidenced by frequent keynote invitations at major conferences like StatPhys, ECCS, and APS March Meetings. Prof. Burioni leads collaborative research networks through her EPS division chairmanship and SIFS leadership, fostering cross-institutional projects on statistical physics applications. Her campus-based studies leverage Wi-Fi data from Parma University to model pedestrian dynamics and epidemic spreading in real-world constrained environments.

• Statistical Physics
• Complex Networks
• Random Walks
• +5 more

Pietro Rotondo is an Assistant Professor (Ricercatore a tempo determinato) at the University of Parma , Italy, within the Department of Mathematical, Physical and Computer Sciences . He is actively involved in lecturing the course Principles of Physics to first-year students of the Earth Sciences bachelor programme for the academic years 2023/2024 and 2024/2025. Education & Academic Background: While explicit educational history is not detailed in the text, his faculty rank and research output indicate advanced training in theoretical physics and statistical mechanics, likely culminating in a PhD. Research Interests: Statistical mechanics of deep learning and artificial neural networks Bayesian inference in high-dimensional, disordered systems Phase transitions and replica methods in complex systems Quantum many-body physics and cavity quantum electrodynamics Renormalization group approaches to finite-width neural networks His interdisciplinary work bridges rigorous physics techniques with modern machine-learning challenges, aiming to uncover universal laws governing learning and generalization in artificial systems. Recent Publication Trends: Over the past five years, Rotondo has concentrated on developing analytical frameworks that describe how deep neural networks learn and generalize, particularly beyond the infinite-width limit. Recurring themes include Bayesian effective actions, kernel renormalization, and the statistical mechanics of structured data. Scientific Awards & Honors: No specific awards are mentioned in the provided text. Supervision & Funding: The text does not list current PhD or Master’s students, nor does it detail specific grants or funded projects. Laboratories & Teams: No named laboratories, centers, or research groups are explicitly cited in the scraped material.

• Statistical Physics
• Machine Learning Theory
• Complex Systems
• +3 more

Francesco Morandin is a Researcher (Assistant Professor) in Probability and Statistics at the Department of Mathematical, Physical and Computer Sciences, University of Parma. His research spans theoretical and applied mathematics, focusing on nonlinear PDEs, SPDEs, and stochastic processes like branching and generalized urn models, with applications in medical data analysis, industrial statistics, and computational biology. Education: Mathematics degree from Scuola Normale Superiore di Pisa (1998), PhD program (1999-2000). Collaborations: University of Pisa (microarray analysis), Avio S.p.A. (mechanical failure detection), Parma burial office (cremation dynamics), Heinz-Plasmon (quality control). His recent work in machine learning includes SwitchPath activation functions for exploration enhancement, GloNets for global connectivity, and reinforcement learning applications in healthcare and game theory. He has supervised 4 bachelor's, 13 master's, and co-supervised 15 theses, with a focus on industrial and medical statistics education. His publications integrate probability theory with applications in cancer therapy prediction, single-cell RNA analysis, and stochastic modeling of turbulence.

• Nonlinear PDEs
• SPDEs
• Shell Models (Dyadic, GOY)
• +10 more

Francesco Marchetti is a fixed-term researcher (RTDa) at the Department of Mathematics "Tullio Levi-Civita" of the University of Padova. He holds a Master's degree in Mathematics and a PhD in Health Planning Sciences, both from the University of Padova (2016 and 2021 respectively). His research spans interdisciplinary areas including mathematical approximation theory, machine learning, and applications in medical imaging and space weather forecasting. Education Master in Mathematics, University of Padova (2016) PhD in Health Planning Sciences, University of Padova (2021) Research Interests Approximation theory and kernel-based methods Machine learning and deep learning applications Magnetic Particle Imaging (MPI) signal reconstruction Space weather forecasting via neural networks He actively collaborates with the MIDA group at the University of Genova and participates in research networks like CAA (Constructive Approximation and Applications) and RITA (Rete Italiana di Approssimazione). Current work focuses on p-Laplacians on hypergraphs and associated machine learning frameworks. Scientific Awards INdAM Postdoctoral Grant (2021)

• Approximation Theory
• Kernel-Based Approximation
• Machine Learning
• +3 more

Riccardo Berta is an Associate Professor at the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN), University of Genoa. His research focuses on TinyML, deep learning on microcontrollers, and embedded systems for automotive and IoT applications. Current Affiliation: Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN), University of Genoa Academic Role: Associate Professor, Electronics (IINF-01/A) His research interests include: Tiny Machine Learning (TinyML) for resource-constrained devices Deep Reinforcement Learning in automated driving and gaming Edge Computing and Structural Health Monitoring IoT frameworks for data management and serious games Recent work explores the application of neural networks, adversarial training, and synthetic dataset generation in automotive scenarios. He is a member of the Scientific Council of the University Service Center for Simulation and Advanced Training (SIMAV) and the Department Board of DITEN.

• Tiny Machine Learning
• Reinforcement Learning
• Deep Learning on Microcontrollers
• +5 more

Silvana Dellepiane serves as an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa's Polytechnic School. Her academic roles include teaching Electrical Communications for Biomedical Engineering and Digital Image Processing across multiple Master's programs including Internet and Multimedia Engineering, Electronic Engineering, and History of Art and Artistic Heritage Valorization. Her research spans interdisciplinary domains with primary focus on Medical Image Processing and Tele-rehabilitation Systems . Key areas include developing exergame-based rehabilitation protocols for systemic sclerosis and multiple sclerosis, lung cancer detection via deep learning, and hepatic disease staging using ultrasound morphological features. She integrates Remote Sensing techniques for flood monitoring through SAR image analysis and contributes to Digital Cultural Heritage Preservation via pigment identification algorithms for artworks. Her work consistently bridges biomedical engineering with telecommunications. Recent publications demonstrate strong trends toward AI-driven healthcare solutions, particularly in markerless telerehabilitation (ReMoVES system) and medical diagnostics (YOLOv8 for lung cancer). Cross-disciplinary applications appear in cultural heritage (digital processing of historical-artistic images) and environmental monitoring (flood risk assessment using satellite data). Over 50 publications since 2002 show consistent output in IEEE/Springer venues with increasing focus on clinical validation studies. As Member of the Joint Teacher-Student Commission, she actively shapes curriculum development. Her technical leadership appears in projects like STORMS (occupational tele-rehabilitation for MS patients) and SPeRA (web portal for Africa-focused health cooperation). Current research involves integrating graph signal processing with Markov modeling for unsupervised image segmentation across medical and remote sensing domains.

• Medical Image Processing
• Tele-rehabilitation Systems
• Remote Sensing
• +4 more

Halar Haleem is a Research Fellow at the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) within the University of Genoa. Their research spans interdisciplinary domains at the intersection of computer vision, robotics, drone technology, and wireless systems. Academic Rank: Research Fellow Affiliation: University of Genoa, Department of Naval, Electrical, Electronic, and Telecommunications Engineering Contact: halar.haleem@edu.unige.it Research interests focus on drone technology , computer vision , and wireless surveillance systems . They explore applications in traffic monitoring, aerial object detection, and energy-efficient drone operations, with recent work on AI-enabled medical IoT and biomechanical monitoring using smart glasses. Key article trends include: Drone-based traffic analysis using deep learning and image segmentation Privacy-preserving Wi-Fi monitoring systems Monocular vision for activity recognition in makerspaces RF/WiFi signal utilization for UAV surveillance Energy-accuracy trade-offs in drone video processing Trimetallic nanoparticle electrocatalysts for hydrogen production

• Computer Vision
• Robotics
• Drone Technology
• +3 more

Giuliano Vernengo is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa. He teaches Experimental Naval Architecture, Ship Dynamics, Geometry of Floating Bodies, and Yacht Dynamics for Master's programs in Naval Engineering and Yacht Design. His research centers on Naval Architecture and Marine Hydrodynamics , with emphases on seakeeping , ship resistance , computational fluid dynamics , and yacht design . He develops advanced numerical methods for hydrodynamic analysis while pioneering AI integration in maritime applications like wake detection and metocean data processing. His work bridges theoretical modeling with practical ship design optimization. Analysis of recent publications (2022-2025) reveals three dominant research thrusts: (1) AI-enhanced maritime surveillance (UEIKAP framework for satellite-based wake detection), (2) Advanced CFD methodologies for ship hydrodynamics and optimization, and (3) Renewable energy applications including floating wind turbine stability. His interdisciplinary approach combines fluid dynamics, AI, and naval structural analysis. Dr. Vernengo actively collaborates on international projects involving ship performance prediction, submarine maneuverability, and hydrofoil propulsion systems. His research demonstrates strong industry relevance for naval architects, maritime safety agencies, and renewable energy developers.

• Naval Architecture
• Marine Hydrodynamics
• Seakeeping
• +5 more

Gianmaria Bonari is an Assistant Professor at the Department of Life Sciences , University of Siena (Italy), where he focuses on botany, vegetation science, and conservation biology. His work bridges ecological research with data science, particularly through managing the CircumMed vegetation-plot database for large-scale studies. His research spans plant community classification, habitat monitoring, and ecoinformatics at multiple spatial scales. Key themes include biological invasions , macroecology , and conservation strategies , often involving international collaborations and advanced computational methods. He teaches courses on biodiversity , plant diversity , and habitat conservation , with academic training at the University of Siena (PhD), Masaryk University (postdoc), and Free University of Bozen-Bolzano (junior researcher). His email contact is gianmaria.bonari@unisi.it .

• Botany
• Vegetation Science
• Conservation Biology
• +7 more

Gianfranco Lombardo is a fixed-term researcher (RTD-A) at the Department of Engineering and Architecture of the University of Parma . His academic career spans roles including a contract lecturer for courses such as 'Big Data and Business Intelligence' and 'Introduction to Artificial Intelligence', and a research fellow funded by the SUPER project. He has also been a visiting researcher at the University of Florida 's Center for Applied Optimization. Bachelor's in Computer, Electronics, and Telecommunications Engineering (University of Parma, 2014) Master's in Computer Engineering (University of Parma, 2017) PhD in Information Technology (University of Parma, 2021) Lombardo's research focuses on knowledge extraction from semi-structured data using advanced techniques like Deep Learning , Machine Learning , and Network Science . His work applies to domains including financial data analysis, predictive maintenance, and healthcare optimization. Current projects involve Digital Twins for Location-Based Services and continual learning systems. His recent publications demonstrate trends in applying Natural Language Processing to financial filings, LSTM architectures for bankruptcy prediction, and Digital Twin implementations in healthcare and logistics contexts. Keywords span artificial intelligence, financial modeling, and healthcare systems. As an IT consultant and technical expert in software development, Lombardo bridges academic research with practical applications in Artificial Intelligence and Data Science . He supervises research activities and contributes to educational programs in Data Science for Management and Computer Engineering.

• Deep Learning
• Machine Learning
• Natural Language Processing
• +6 more

Jacopo Aleotti is an Associate Professor at the Department of Engineering and Architecture, University of Parma. His research focuses on robotics, computer graphics, and virtual reality, with significant contributions to robot perception, haptic interfaces, and 3D reconstruction. Graduated in Electronic Engineering (2002), University of Parma PhD in Information Technology (2006), University of Parma From 2003 to 2006, he was a Marie Curie Fellow at Orebro University and a postdoctoral fellow at the University of Parma's Department of Information Engineering. His research interests include robotics , computer graphics , and virtual reality , with applications in industrial automation, haptic teleoperation, and 3D scene understanding. His recent publications explore topics like probabilistic motion planning, sensor fusion for VR tracking, and deep learning for object pose estimation. Notable scientific awards include the MIMOS award (2006) and the Marie Curie Fellowship (2003) . He leads research at the Robotics Laboratory (RimLab) at the University of Parma, contributing to projects involving autonomous systems, augmented reality interfaces, and underwater robotics. His teaching includes courses on object-oriented programming and virtual reality systems.

• Robotics
• Computer Graphics
• Virtual Reality
• +3 more