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Barbara Caputo is a Full Professor at Politecnico di Torino, leading the VANDAL Laboratory and directing the AI@PoliTo Interdepartmental Lab. She holds a double affiliation with the Italian Institute of Technology (IIT) and has held roles at Idiap-EPFL and Sapienza University. Her research focuses on AI, computer vision, domain adaptation, and federated learning. She contributes to national AI policy, including the Italian Strategy on AI and the National PhD on AI for Industry 4.0. She is an ERC Laureate and ELLIS Fellow, co-founding ELLIS society. Her work spans visual place recognition, action recognition, and cross-domain learning. Education: PhD in Computer Science from KTH Royal Institute of Technology (2005). Major roles include Rector’s Advisor on AI at PoliTo, Board Member of ELLIS, and coordinator of the AI & Industry 4.0 vertical in the National PhD program. Awards include ERC Laureate (2017), ELLIS Fellow (2019), and Inspiring Fifty Italy (2018). Her research emphasizes federated learning, domain adaptation, and AI ethics. Recent articles explore domain generalization, resource-efficient federated models, and AI-environment interactions. She collaborates with institutions like MUR, CNR, and the European Commission on AI policy and tech initiatives.

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +3 more

Giorgio Grisetti is a Full Professor at Sapienza University of Rome within the Department of Systems and Computer Science, maintaining active research roles in the RoCoCo lab at Sapienza since November 2010 and the Autonomous Intelligent Systems Lab at Freiburg University where he previously served as a Post Doc under Wolfram Burgard starting in 2006. His educational background includes a M.Sc. in Computer Engineering from the University of Rome (2001) and a Ph.D. from Sapienza University of Rome's Intelligent Systems Lab (2006), supervised by Daniele Nardi. His doctoral thesis focused on SLAM using Rao-Blackwellized particle filters. Dr. Grisetti's research centers on mobile robotics with emphasis on robust solutions for autonomous navigation systems. His work spans theoretical and practical advancements in Simultaneous Localization and Mapping (SLAM), robot localization, path planning, and sensor fusion, particularly leveraging LiDAR and multi-sensor configurations. Recent publications demonstrate strong focus on optimization techniques, sensor calibration, and real-time performance for autonomous systems operating in complex environments. His publication trends reveal deep specialization in LiDAR-based SLAM (7 of 15 recent articles), bundle adjustment methods (4 articles), and sensor calibration/perception (3 articles), with consistent contributions to top robotics venues like IEEE Robotics and Automation Letters and ICRA. Key recognitions include: Nomination for the best IROS paper award (2010) Open Source achievement award from Willow Garage (2010) Best paper award at the International Conference and Exhibition on Unmanned Areal Vehicles (2010) Best Paper award at ICRA 2009 (2009) His research is conducted through the RoCoCo lab at Sapienza University of Rome and the Autonomous Intelligent Systems Lab at Freiburg University, focusing on developing foundational algorithms for mobile robot autonomy. Current projects emphasize robust perception systems, optimization frameworks for sensor fusion, and practical implementations for real-world navigation challenges.

• Mobile Robotics
• SLAM
• Robot Localization
• +3 more

Antonia Teresa Spano is a Full Professor at the Department of Architecture and Design (DAD) of Politecnico di Torino, Italy. She serves as Vice Coordinator of the PhD Program in Architectural Heritage and is a member of the Future Urban Legacy Lab (FULL). Her research focuses on geomatics, 3D modeling, and digital documentation for cultural heritage preservation. University: Politecnico di Torino Department: Department of Architecture and Design (DAD) Spano's work integrates advanced geomatic techniques like LiDAR, UAV photogrammetry, and SLAM-based modeling to address challenges in architectural and archaeological heritage documentation. Her expertise spans GIS, digital photogrammetry, and machine learning applications in conservation processes. Her recent publications emphasize multi-sensor 3D surveys for Pier Luigi Nervi's structures, AI-driven decay detection, and semantic classification of LiDAR data. These works align with SDG goals for sustainable cities and quality education. Scientific Awards: Premio Giovani CNR (2005) Miglior Poster at GISTAM (2016) and GEORES (2019) Fellow of CIPA Heritage Documentation (2023-2033), CIRAAS ETS (2020-2030), and ISPRS (2017-2024) Spano supervises PhD students in architectural heritage programs and leads numerous research projects, including collaborations with institutions like the Pompeii Archaeological Park, CRAST, and international universities. She has contributed to editorial boards and program committees of journals and conferences such as Virtual Archaeology Review and ISPRS symposiums.

• Geomatics
• Cultural Heritage Documentation
• 3D Modeling
• +5 more

Nicola Capodieci is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia, specializing in Information Processing Systems (IINF-05/A). He actively teaches multiple courses including Object-Oriented Programming, Web Technologies, and General Computer Science across Computer Science and Mathematics degree programs. His research interests focus on GPU acceleration for embedded systems, autonomous vehicles, and real-time computing. Dr. Capodieci's work addresses critical challenges in heterogeneous computing platforms, particularly for automotive applications and smart city infrastructure. His research bridges theoretical computer science with practical applications in autonomous driving and urban mobility systems. Analysis of his recent publications reveals a strong focus on optimizing GPU performance for latency-sensitive applications, particularly in autonomous vehicles. His work spans path planning algorithms, memory interference management, and real-time scheduling on heterogeneous platforms. A significant portion of his research addresses practical implementation challenges in embedded systems where computational resources are constrained but timing predictability is critical. Dr. Capodieci's teaching portfolio demonstrates expertise in both foundational programming concepts and advanced topics in web technologies. His courses emphasize practical implementation skills while covering theoretical foundations of object-oriented programming, web development frameworks, and computational thinking.

• GPU Acceleration
• Embedded Systems
• Autonomous Vehicles
• +6 more

Filiberto Chiabrando is an Associate Professor at the Department of Architecture and Design (DAD) of Politecnico di Torino, with a secondary appointment as Adjunct Associate Professor at Michigan Technological University (USA). He serves as Deputy Coordinator of the Doctoral College for Architectural and Landscape Heritage and is Secretary of the ISPRS Working Group on UAS & Small Multi-sensor Platforms. His work bridges geomatics, photogrammetry, and cultural heritage preservation. Academic Affiliations Politecnico di Torino (Main Institution) Michigan Technological University (Adjunct Appointment) Research Leadership Coordinator of PIC4SeR Interdepartmental Center Principal Investigator for HERITALISE, Common Grounds, POSEIDON, ARCHIM3DES, and ResCult projects Chiabrando's research focuses on 3D modeling , UAV photogrammetry , underwater cultural heritage documentation , and HBIM-GIS integration . He specializes in SLAM systems , laser scanning , and rapid mapping for architectural conservation. His work aligns with SDGs 9 (Innovation), 11 (Sustainability), and 17 (Partnerships). His recent projects emphasize multitemporal marine vegetation mapping (POSEIDON), cloud-based heritage digitization (HERITALISE), and advanced 3D metric surveying in marine environments (ARCHIM3DES). He has developed open-source education platforms like POSER for underwater photogrammetry training. Scientific Awards Licinio Ferretti Award (ASITA, 2009 & 2010) Best Paper Awards: Sensors (2013), CIPA (2013) Editorial Roles Editorial Board: Geomatics Journal (2021-), ISPRS International Journal (2019-) As a PhD advisor, he has mentored 7 doctoral students in architectural heritage, including Alessio Calantropio (2019-2023) on underwater heritage and Alessandra Spreafico (2019-2023) on the Turin 1911 Exposition. He leads commercial contracts with organizations like DJI GmbH, World Food Programme, and UNICEF for UAV and geospatial applications.

• Geomatics
• 3D Modeling
• Digital Photogrammetry
• +8 more

Fulvio Rinaudo is a Full Professor in the Department of Architecture and Design (DAD) at Politecnico di Torino, Italy, specializing in geomatics and cultural heritage documentation. With decades of experience in the field, he leads research in Geographic Information Systems (GIS), Historical Building Information Modeling (HBIM), photogrammetry, and the documentation of cultural heritage through advanced metric surveying techniques. His research interests span across multiple domains of cultural heritage preservation, including: Georeferenced databases (GIS) for cultural heritage management HBIM applications for architectural documentation and conservation Automatic digital photogrammetry for objects and contexts of varying scales Metric survey techniques for documenting historical buildings and urban contexts Digital documentation methodologies for cultural heritage preservation Rinaudo's recent scholarly output demonstrates a clear focus on advancing technological approaches to cultural heritage documentation, particularly through HBIM systems, environmental risk assessment for heritage sites, and innovative surveying methodologies. His work increasingly integrates emerging technologies like SLAM systems, 360° imaging, and cloud-based platforms to create more efficient and accurate documentation workflows. A significant portion of his recent research addresses the challenges of documenting and preserving heritage in Central Asia, particularly through the ERAMCA project focused on environmental risk assessment. Among his notable recognitions is the Best Poster Award at the CIPA Symposium awarded by ICOMOS CIPA-HD in France (2013). His leadership in the field is further evidenced by his current role as President of CIPA Heritage Documentation (2024-2027) and previous position as Secretary of ICOMOS Italy (2020-2022). Professor Rinaudo actively supervises PhD students across multiple institutions including Politecnico di Torino and Sapienza University of Rome. He has secured significant research funding through competitive grants including the ERAMCA project (Environmental Risk Assessment and Mitigation on Cultural Heritage assets in Central Asia), the RURITAGE project, and the GAMHER project (Geomatics data Acquisition and Management for landscape and built Heritage in an European Perspective). He serves on editorial boards for journals including VIRTUAL ARCHAEOLOGY REVIEW and APPLIED GEOMATICS, and participates in major international conferences as a scientific committee member for CIPA and ISPRS events. His external teaching engagements include positions at Katholieke Universiteit Leuven (Belgium) and Turin Polytechnic University in Tashkent.

• Geographic Information Systems (GIS)
• Geomatics
• HBIM (Historical Building Information Modeling)
• +5 more

Giulio Fontana is affiliated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. His research spans robotics, artificial intelligence, and their applications in agriculture and healthcare. He contributes to benchmarking frameworks like ACRE and RoCKIn, focusing on standardized evaluation of robotic systems and AI applications. Primary Affiliation: Politecnico di Milano (DEIB) Research Focus: Robotics, AI, Agricultural Engineering, Bioengineering Fontana has pioneered benchmarking competitions such as ACRE (Agri-Food Competition for Robot Evaluation) and RoCKIn, emphasizing quantitative metrics for robotic performance. His work includes AI-driven pesticide reduction in agriculture, SLAM (Simultaneous Localization and Mapping) in autonomous robotics, and assistive devices for hospital logistics. Recent publications highlight AI-sprint for runtime management of AI applications and multimodal interfaces for robotic wheelchairs. Scientific Contributions : Coordinated design of benchmarking competitions (ACRE, RoCKIn) Developed SLAM benchmarking datasets (Rawseeds project) Innovated AI applications for sustainable agriculture Engineered assistive mobility solutions for healthcare

• Robotics
• Artificial Intelligence
• Agricultural Engineering
• +3 more

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.

• High-Performance Computing (HPC)
• Computer Architecture
• Embedded Systems
• +5 more

Ivano Malavolta is an Associate Professor in Software Engineering at the University of Urbino , focusing on energy-efficient software, software architecture, and model-driven engineering (MDE). His research bridges robotics, mobile systems, and sustainability, emphasizing empirical methods and industrial applicability. Key Research Areas: Energy-efficient software, microservices, robotics systems, collaborative modeling, mobile application performance. Affiliations: Department of Software Engineering, University of Urbino. His recent publications highlight empirical studies on energy consumption patterns in robotics, mobile apps, and AI systems. He has contributed to frameworks like the Green Software Measurement Model (GSMM) and tools for architectural technical debt analysis. Notably, he has co-authored 15+ peer-reviewed articles in venues such as Journal of Systems and Software , Information and Software Technology , and ACM/IEEE conferences . His work often involves cross-platform comparisons (e.g., Electron vs. Web, Pandas vs. Polars) and systematic mappings of software engineering practices.

• Software Engineering
• Energy-Efficient Systems
• Software Architecture
• +4 more

Riccardo Zaccone is a Ph.D. candidate in Computer and Systems Engineering at Politecnico di Torino’s Department of Control and Computer Science (DAUIN), specializing in machine learning and computer vision. He also serves as an external lecturer and teaching assistant, contributing to courses in Machine Learning, Deep Learning, and Algorithms and Data Structures for Computer Science Engineering. Education : Ph.D. in Computer and Systems Engineering (2022–2025), Politecnico di Torino. His research focuses on Federated Learning and Visual Place Recognition, addressing challenges in communication efficiency, distributed training, and cross-domain adaptation. Recent work includes Communication-efficient Federated Learning with Heavy-Ball Momentum (2025) MeshVPR for 3D-based Urban Navigation (2025) Distributed CosPlace Training for Large-Scale Localization (2024) He collaborates with the VANDAL laboratory on multimodal learning applications and has co-authored publications in top-tier venues like ECCV, Frontiers in Robotics and AI, and ICPR.

• Machine Learning
• Computer Vision
• Federated Learning
• +3 more

Francesco Ragusa is a Research Fellow at the University of Catania, Italy, holding an Industrial Doctorate in Computer Science (2021). He spent part of his PhD at the University of Hertfordshire, UK. His work focuses on First Person (Egocentric) Vision, including Human-Object Interaction, Industrial Applications, and Augmented Reality. He co-founded NEXT VISION s.r.l., an academic spin-off from the University of Catania since 2021. Key projects include the MECCANO dataset for industrial human-object interactions and the EGO-EXO4D initiative analyzing skilled human activity from multi-perspective views. Research interests span Computer Vision, Pattern Recognition, and Machine Learning. He contributed to seminal datasets like MECCANO and ENIGMA-51, advancing understanding of human behavior in industrial settings. His work emphasizes practical applications, such as wearable assistive systems and visual navigation solutions. Ragusa has delivered tutorials at major conferences (e.g., ICIAP, VISIGRAPP) on First Person Vision’s history, challenges, and trends. He actively promotes industrial collaborations and has secured grants including PNRR MUR (Code E63C22001940006) and EU funding under Next Generation EU. His teaching and professional activities include organizing workshops on egocentric vision for AI-driven assistants and industrial safety systems. Current research directions involve multimodal synthetic data utilization, gaze-based interaction analysis, and cross-modal fusion for human-robot collaboration.

• Computer Vision
• Pattern Recognition
• Machine Learning
• +5 more

Paolo Dabove is an Associate Professor at the Department of Environmental, Land and Infrastructure Engineering (DIATI) at Politecnico di Torino, where he has served since November 2021. He holds multiple significant roles including Functions aggregated to the Vice-Rector for Education regarding activities related to first and second level teaching and the training offer, and is a Component of the SISCON Interdepartmental Center - Safety of Infrastructures and Constructions. His academic work spans teaching, research, and editorial responsibilities across multiple domains of geospatial technology. Professor Dabove's research interests focus on Geomatics, with particular expertise in GNSS positioning, indoor positioning, and photogrammetry. His work centers on developing algorithms for quality control of GNSS positioning in real-time using both geodetic and low-cost instruments. He has made significant contributions to monitoring techniques with Geomatics instruments, low-cost INS and GNSS systems for mobile mapping, and innovative methodologies for landslides monitoring using networks of GNSS mass-market receivers. His research extends to smartphone-based positioning solutions and atmospheric monitoring through GNSS signal exploitation. His publication record demonstrates a consistent focus on advancing geospatial technologies, with particular emphasis on making sophisticated positioning systems more accessible through low-cost solutions. Recent work shows increasing integration of machine learning techniques with traditional geospatial methods, and expanding applications into diverse fields including transportation systems, museum visitor studies, underground structure monitoring, and climate-related research. His publications reveal strong international collaboration patterns and growing interest in open-source approaches to geospatial technology. Premio giovani autori SIFET (SIFET Young Authors Award) conferred by SIFET: Società Italiana di Fotogrammetria E Topografia, Italy (2015) Fellow - Geographic Free and Open Source Software, Italia (2020-2021) Fellow - Associazione Georisorse e Ambiente (GEAM), Italia (2020-2022) Professor Dabove actively supervises doctoral students, with Milad Bagheri currently working under his guidance in the Civil and Environmental Engineering program. He leads multiple significant research projects including META-MUSEUM (2024-2027), PAIN AND GAIN (2023-2025), and CNMS – Spoke 7 (2022-2025), demonstrating substantial grant acquisition capabilities. His research portfolio spans competitive EU-funded projects, national PRIN grants, and commercial contracts with organizations including ESA. As Editor-in-Chief of Geoengineering Environment And Mining (GEAM) journal and active participation in professional organizations including the International Association of Geodesy (IAG) Working Group and ISPRS Working group V/3 (which he chairs), Professor Dabove maintains strong connections to the international geospatial research community. His leadership of the GFOSS.it association since 2020 highlights his commitment to open-source geospatial technologies.

• Geomatics
• GNSS positioning
• Indoor positioning
• +4 more

Giulia Sammartano is a Fixed-term Tenure-Track Assistant Professor at the Department of Architecture and Design (DAD) of the Polytechnic University of Turin . She is a member of the FUTURE Urban Legacy Lab (FULL) and engages in interdisciplinary research at the intersection of geomatics, cultural heritage, and sustainable architecture. Scientific Branch: Geomatics (CEAR-04/A, Area 0008 - Civil Engineering and Architecture) ERC Skills: PE8_3 (Civil Engineering), PE6_8 (Computer Graphics), SH2_12 (GIS), PE2_15 (Metrology) SDG Contributions: Quality Education, Gender Equality, Cities & Communities, Climate Action Her research interests include 3D modeling , digital cultural heritage , UAV photogrammetry , and SLAM-based mapping . She specializes in applying advanced geomatic techniques for heritage documentation, with a focus on laser scanning , point cloud processing , and HBIM (Heritage Building Information Modeling). Recent publications highlight her work on the REVHEAL and HERITALISE projects, exploring topics like masonry vault simulations , autonomous robotic surveying , and ML/DL classification of LiDAR data . She serves as Guest Editor for journals such as Remote Sensing , Sensors , and Drones . Awards: Polytechnic University of Turin Publications Award (2016, 2018) Best Poster SIFET2017 (2017) Quality of Research Activity (2016) Scientific Memberships: ICOMOS Italia (2023-) CIPA Heritage Documentation (2023-) ISPRS (2020-)

• 3D models
• Digital cultural heritage
• Digital photogrammetry
• +10 more

Salvatore Barba is a Full Professor in the Department of Civil Engineering at the University of Salerno, Italy, where he conducts research and teaching in architectural surveying, cultural heritage documentation, and digital reconstruction. He also serves as a Contract Professor at the Faculty of Architecture, University of Basilicata, Matera. His work bridges engineering, architecture, and heritage science, focusing on advanced digital methodologies. Research interests: His expertise lies in photogrammetry , remote sensing , 3D laser scanning , GIS-BIM integration , and augmented reality for cultural heritage. He investigates degradation diagnostics, low-cost survey tools, and micro-photogrammetry, emphasizing interdisciplinary and methodologically rigorous approaches to digital documentation. Publications and technology: His recent articles highlight the application of UAVs, wearable SLAM scanners, and handheld microscopes in heritage contexts. He validates instruments like the Shining 3D EinScan-Pro and develops protocols for high-accuracy documentation. His work consistently underscores the importance of expert interpretation over purely automated processes in surveying. Scientific Awards: No specific awards mentioned in the provided text. Advising and grants: While specific students and grants are not listed, he collaborates on international projects, participates in technology transfer agreements (e.g., with Dino-Lite), and contributes to methodological advancements in heritage science. His role as a faculty member implies advising graduate students in civil engineering and architectural documentation. Labs and teams: He is involved in research activities related to digital heritage documentation, likely within laboratory facilities at the University of Salerno. His collaborative work with researchers across Europe and on diverse heritage sites indicates active participation in interdisciplinary research teams focused on advanced surveying and conservation technologies.

• Architectural Drawing
• Conservation and Restoration
• Remote Sensing
• +8 more

Antonia Teresa Spano' is a Full Professor at the Department of Architecture and Design (DAD), Politecnico di Torino, where she leads research and teaching in geomatics for architectural and landscape heritage. She is a member of the Future Urban Legacy Lab (FULL) and serves as Deputy Coordinator of the PhD College in Architectural Heritage. Her work spans interdisciplinary collaborations with institutions such as the Archaeological Park of Pompeii, the Royal Museums of Turin, the University of Salento, and the Bruno Kessler Foundation. She has led numerous national and international research projects, including those funded by PRIN, EU, and commercial contracts. Her research focuses on the application of advanced geomatic technologies—including 3D modeling, UAV photogrammetry, LiDAR, SLAM-based mobile mapping, and GIS—to the documentation, analysis, and conservation of cultural heritage. She integrates computer vision, remote sensing, and digital reconstruction techniques to support sustainable urban development and heritage preservation. Her work is closely aligned with UN Sustainable Development Goals (SDGs) 4 (Quality Education), 5 (Gender Equality), and 11 (Sustainable Cities and Communities). The most recent publications reflect a strong trend in digital heritage, with emphasis on AI-driven decay detection, multispectral UAV data for landscape analysis, semantic classification of LiDAR data, and integrated 3D survey methods for heritage structures. Her work frequently involves collaborations with PhD students and international research teams, focusing on both built and archaeological heritage. Best poster, GEORES 2019 (ISPRS) Best poster, GISTAM 2016 CNR Youth Award, 2005 She is actively involved in advising PhD students and managing research grants, including scholarships funded by IREN Energia SPA and the Bruno Kessler Foundation. She serves as Scientific Director for multiple collaborative agreements with public and private institutions. She also contributes to major research projects such as the diagnosis of Pier Luigi Nervi’s exhibition halls and urban regeneration initiatives in Elva and Turin. She leads the LabG4CH – Geomatics Laboratory for Cultural Heritage – and participates in editorial boards of journals like Sensors , Techne , and Virtual Archaeology Review .

• Geomatics
• Cultural Heritage Documentation
• 3D Modeling
• +15 more