جست‌وجوی استاد و پژوهشگر

Silvia BOZZAمشاهده پروفایل

دانشیار

• Forensic Statistics
• Bayesian Statistics
• Evidence Evaluation
• +۴ مورد دیگر

Silvia BOZZA is an Associate Professor in the Department of Economics at Ca' Foscari University of Venice, where she also serves as Department Delegate for Teacher Training for High Schools. Her academic profile is centered around Statistics (SSD STAT-01/A), with a strong focus on forensic applications of statistical methods. She maintains dual institutional affiliations, working within both the Department of Economics (based in San Giobbe) and the Interdepartmental School of Economics, Languages and Entrepreneurship for International Exchanges (located in Treviso - Palazzo San Paolo). Professor BOZZA's research primarily explores the application of Bayesian statistics to forensic science and legal evidence evaluation. Her work demonstrates a consistent trajectory from early publications on spatio-temporal models to her current specialized focus on forensic statistics. She has developed expertise in probabilistic graphical models, Bayes factors, and statistical decision theory as applied to evidence interpretation. Her research addresses critical questions in forensic science regarding how to properly evaluate and communicate statistical evidence in legal contexts, with particular attention to handwriting analysis, DNA evidence, and authorship attribution. Her publication record shows remarkable consistency and productivity, with over 90 publications spanning from 2001 to 2025. Recent work (2022-2025) demonstrates her ability to address contemporary challenges, including AI authorship discrimination using Bayesian methods for distinguishing human from ChatGPT-generated text. Her articles frequently appear in high-impact forensic and statistical journals including Law, Probability & Risk, Forensic Science International, and Annual Review of Statistics and its Application. Professor BOZZA actively supervises undergraduate and graduate theses involving data analysis, requiring knowledge of statistical software including the R programming language used in the Statistics for Economics Laboratory course. She encourages students to propose topics while offering guidance to refine research questions. Her office hours show she maintains regular availability for student consultations, indicating active engagement in academic mentoring.

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +۶ مورد دیگر

Francesco Strada is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He serves as a Course Lecturer for Virtual Reality and Technical Art for Cinema and Video Games, and as a Course Collaborator for multiple courses across Computer Engineering, Film and Media Engineering, and Architecture programs. He is an active member of the College of Computer, Film and Mechatronics Engineering and the College of Architecture and Design teaching committees. Dr. Strada's research focuses on Computer Graphics, Virtual Reality, Augmented Reality, and Human-Computer Interaction with particular emphasis on Embodied Conversational Agents, emotion recognition, and serious games applications. His work bridges technical computer science with psychological and human factors considerations to create more believable and effective virtual experiences. His research spans applications in education, healthcare, automotive interfaces, cultural heritage, and emergency response training. His recent publications demonstrate a strong trend toward emotionally intelligent virtual agents, VR/AR applications in specialized domains, and technical innovations in latency management and digital human representation. His work often combines psychological principles with technical implementations to enhance user experience and system effectiveness. Dr. Strada actively supervises PhD students including Alessandro Emmanuel Pecora, Stefano Calzolari, and Leonardo Vezzani, whose research focuses on Emotionally Aware Embodied Conversational Agents (E2CA) and Car AR-HUD design. He leads significant research projects including Holo-BLSD (2024-2025), a Mixed Reality tool for first aid emergency response training, and '50 shadows of AI' (2025), focusing on personalized education in corporate settings. He is a member of the CGVG - Computer Graphics and Vision Group at DAUIN, where his team develops cutting-edge applications in AR/VR, Human-Computer Interaction, User Experience, Computer Vision, Machine Learning, and Artificial Intelligence. His research has practical applications in education, training, healthcare, automotive interfaces, and cultural heritage preservation.

• Machine Learning
• Human-Computer Interaction
• 3D Graphics
• +۸ مورد دیگر

Chiara Innocente is a PhD student in Management, Production, and Design at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino. She holds the academic rank of Consultant Lecturer and contributes to teaching in courses related to 3D graphics in biomedical engineering applications. Her research spans computational modeling, human-computer interaction, and machine learning, with a focus on rehabilitation engineering, cultural heritage preservation, and medical imaging. Education: PhD in Management, Production, and Design (2022-2025) Research interests include: Machine learning applications in healthcare and rehabilitation engineering Human-computer interaction for augmented/virtual reality 3D graphics and computational modeling for biometric and cultural heritage Convolutional neural networks in medical image analysis Her recent publications highlight interdisciplinary work bridging computer science with clinical applications and cultural preservation. She collaborates on national patents for athlete performance evaluation systems and participates in the Augmented Humans research framework.

Marianna Nicolosi Asmundoمشاهده پروفایل

دانشیار

• Mathematical Logic
• Automatic Deduction
• Description Logic
• +۷ مورد دیگر

Marianna Nicolosi Asmundo is an Associate Professor of Mathematical Logic (MAT/01) at the Department of Mathematics and Computer Science (DMI) of the University of Catania. She earned her PhD from the same university in 2003 and serves as a proposing member of CINUM - Interdepartmental Center for Humanistic Computing. Teaches undergraduate and graduate programs in Mathematics Master's Degree Programs in Computer Science Textual Sciences for Digital Professions (Department of Humanities) Her research spans automatic deduction, tableaux-based deductive systems, decision procedures in elementary set theory and non-classical logic, interactive theorem proving, knowledge bases, ontologies, and reasoning services for the semantic web. Recent publications emphasize ontology interoperability, blockchain-based knowledge representation, and set-theoretic reasoning frameworks. She contributes to ontologies for cultural heritage (Saint Gall monastery modeling, archaeological Sicilian landscapes) and blockchain applications. Collaborates extensively with researchers like D. Cantone and D.F. Santamaria on description logic systems. Active member of CINUM - Interdepartmental Center for Humanistic Computing Supervises thesis projects on semantic web and blockchain ontologies

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Prof. Fabio Galasso is a Full Professor in the Department of Computer Science at Sapienza University of Rome, where he heads the Perception and Intelligence Lab (PINLab). His research focuses on fundamental innovation in computer vision and machine learning, with particular emphasis on distributed intelligent systems, perception frameworks, and general intelligence within sustainable and interpretable AI contexts. His research interests span multiple domains of computer vision including video segmentation , motion forecasting , distributed intelligent systems , and shape reconstruction . Galasso's work emphasizes sustainable AI approaches that operate within constrained computational resources while maintaining interpretability and verifiability. His research bridges theoretical foundations with practical applications across retail, smart cities, and industrial settings. His recent publications demonstrate a clear progression toward increasingly complex human motion understanding and forecasting, with a strong emphasis on real-world applications. The research trajectory shows movement from foundational video segmentation techniques toward sophisticated motion prediction systems and anomaly detection frameworks that integrate multiple modalities. Key themes include temporal consistency, computational efficiency, and practical deployability in resource-constrained environments. His scientific achievements have been recognized with prestigious awards: 2019 IoT/WT Innovation World Cup 2019 Digital Champions Award 2018 Deutscher Digital Award Galasso has coordinated significant research initiatives including a Marie Sklodowska-Curie Actions project (Horizon 2020) and served as Principal Co-Investigator in multiple German-funded projects from the Ministry of Education and Ministry of Economics. His industry experience includes founding and directing OSRAM's Computer Vision Department in Munich, where he led R&D efforts connecting AI research with smart lighting applications, resulting in successful innovation transfers like the award-winning VISN product. He leads the Perception and Intelligence Lab (PINLab) at Sapienza University of Rome, fostering research that spans fundamental computer vision techniques to practical implementations in retail, smart cities, and industrial applications. The lab maintains strong connections with both academic institutions (including previous collaborations with University of Cambridge and Max Planck Institute) and industry partners.

• Computer Vision
• Natural Language Processing
• Artificial Intelligence
• +۷ مورد دیگر

Federico D'Asaro is a researcher and PhD student at Politecnico di Torino, affiliated with the Department of Control and Computer Science (DAUIN) and the Computer Graphics & Vision Group (CGVG). He works as an external lecturer and teaching assistant for the Applied Data Science Project course in the Data Science and Engineering program. His research focuses on Vision-Language Models (VLMs), particularly addressing the Modality Gap in multimodal feature spaces and their applications in downstream tasks like semantic segmentation and speech emotion recognition. Education: Master's degree in Data Science and Engineering (2021), currently pursuing PhD in Computer and Systems Engineering (39th cycle, 2023-2026). His research at the intersection of Natural Language Processing and Computer Vision investigates how reducing the Modality Gap improves crossmodal performance. Recent work applies Large Speech Models (LSMs) to cross-lingual emotion recognition and non-verbal vocalization tasks. He collaborates with researchers like Andrea Bottino, Giuseppe Rizzo, and Juan José Márquez Villacis on projects involving multimodal deep learning and feature extraction. The trends in his publications highlight expertise in multimodal learning (Vision-Language Models, speech-text alignment), deep learning for segmentation and emotion recognition, and crossmodal adaptation in speech processing. His 2025 work focuses on contrastive alignment and non-verbal vocalization, while 2024 studies explore transfer learning of speech models across languages. Teaching Contributions External lecturer for Applied Data Science Project (2025/26) Course collaborator for Applied Data Science Project (2024/25) Federico is part of the Computer Graphics & Vision Group (CGVG) , contributing to interdisciplinary projects that bridge Computer Vision , Natural Language Processing , and Speech Emotion Recognition . His work emphasizes practical applications of multimodal models in real-world scenarios.

Marco Grangettoمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Artificial Intelligence
• +۵ مورد دیگر

Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.

• Industrial Engineering
• Sustainable Manufacturing
• Circular Economy
• +۳ مورد دیگر

Luigi Panza is a Fixed-term researcher at the Department of Management and Production Engineering (DIGEP) within the College of Management and Production Engineering at the Polytechnic University of Turin. He also serves as an invited member of the College of Mechanical, Aerospace, and Automotive Engineering. His scientific disciplinary sector is Manufacturing Technologies and Systems (IIND-04/A) under Area 0009 - Industrial and Information Engineering. Dr. Panza's research centers on sustainable production systems with emphasis on circular economy integration, Industry 4.0 applications, and advanced manufacturing technologies. His work bridges environmental policy, digital transformation, and industrial processes, particularly examining carbon taxation impacts, additive manufacturing sustainability, and laser-based polymer processing. He actively explores cross-sector applications including agricultural technology modernization through digital tools. His 2024-2025 publications reveal a strong focus on systemic industrial transitions, combining bibliometric analysis with empirical environmental assessment. Key trends include circular economy frameworks using 10R principles, life-cycle evaluation of decentralized manufacturing, policy-driven business model shifts, and material-specific advanced production techniques. No scientific awards were documented in available sources. Panza serves as course collaborator across five engineering disciplines at Polytechnic University of Turin, teaching Manufacturing Processes, Production Systems, and Graphic Communication since 2020/21 with assignments extending through 2025/26. His instructional scope spans Mechanical, Automotive, Industrial Production, and Management Engineering programs, including the Challenge@PoliTo NewLAW project on alumina waste valorization. No student advising or grant details were specified in current profiles.

Giancarlo Manziمشاهده پروفایل

دانشیار

• Machine Learning
• Multivariate Statistics
• Bayesian Statistics
• +۵ مورد دیگر

Giancarlo Manzi is an Associate Professor of Statistics at the Department of Methods and Models for Economics, Territory, and Finance, University of Rome La Sapienza. He holds a PhD from the University of Milan-Bicocca and conducted thesis research at the University of Toronto. His career includes roles at the Medical Research Council Biostatistics Unit in Cambridge and the University of Milan. University of Rome La Sapienza (Current) Medical Research Council Biostatistics Unit (Former Researcher) University of Milan (Former Researcher and Associate Professor) University of Milan-Bicocca (PhD) University of Toronto (Thesis collaboration) His research spans Machine Learning , Bayesian Statistics , and Smart Mobility , with a focus on Covid-19 analytics , data visualization , and epidemiological modeling . He integrates Multivariate Statistics with Public Health to address complex challenges in health systems and urban environments. The 15 most recent publications highlight expertise in quantile regression , Bayesian networks , time-series analysis , and smart mobility optimization . His methodological contributions include wavelet analysis, cross-correlation models, and SIRD modeling frameworks applied to pandemic dynamics and bike-sharing systems. Scientific awards and honors are not explicitly mentioned in the provided texts. Giancarlo Manzi has taught at the University of Verona, Catholic University of the Sacred Heart, and Universidad Carlos III in Madrid, maintaining strong ties with Italy's academic institutions.

Francesco Ragusaمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۵ مورد دیگر

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.

Michael Neriمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Audio Processing
• +۳ مورد دیگر

Michael Neri is a Researcher in Audio Signal Processing at Tampere University and a Ph.D. student in Applied Electronics at Roma Tre University. His primary affiliation is with the Department of Signal Processing at Tampere University. He holds a B.Sc. in Information Engineering from the University of Padua (2019) and an M.Sc. in ICT for Internet & Multimedia from the University of Padova (2021). He was a visiting PhD student at Tampere University of Technology in 2023. His research focuses on Audio Processing, Computer Vision, and Deep Learning, with applications in safety and security. Key projects include RAILGAP (EU Horizon 2020), which uses GNSS for rail positioning, INSECTT (ECSEL EU Project) for secure IoT-AI systems, and ISEEYOO (University of Padova Grant) for anomaly detection in Cyber-Physical Systems. He has also contributed to the ESA-funded VOLIERA project on multi-sensor railway positioning. Neri's work spans environmental sound classification, speaker localization, and AI-driven multimedia quality assessments. His research is supported by grants from the European Union and ESA programs. He actively collaborates on projects addressing occupational safety through VR integration and anomaly detection in audio signals. Contact him via michael.neri@tuni.fi or his professional profiles on ResearchGate and GitLab .

Alessandro Luiginiمشاهده پروفایل

دانشیار

• Graphic and Visual Sciences
• Art and Heritage Education
• Digitization of Cultural Heritage
• +۳ مورد دیگر

Alessandro Luigini is an Associate Professor at the Department of Educational Sciences, Faculty of Educational Sciences, Free University of Bozen-Bolzano. His academic roles include serving as Principal Investigator for projects such as VAR.HEE (2018-21) and TTC (2023-2025), and chairing international conferences like IMG2017 and EARTH2018. He founded EARTH_LAB, focusing on digital environments for education, art, and heritage. His research interests span graphic and visual sciences, digital heritage, and immersive serious games for education. He has authored over 130 publications and serves on editorial boards and committees, including the ICCD Administrative Committee and UID board. Education: PhD in Representation and Surveying of Architecture and the Environment from University 'G. d'Annunzio.' Grants: Principal Investigator for projects funded by competitive calls (VAR.HEE, B_DIGITAL, Digital_FEED, TTC). Labs/Teams: EARTH_LAB, leading interdisciplinary research in digital heritage education.

• Remote Sensing
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Martina Pastorino is a Researcher in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa. Her work focuses on integrating machine learning with probabilistic graphical models for advanced remote sensing image analysis , particularly in multiresolution classification using satellite and UAV data. She teaches courses on Machine Learning for Pattern Recognition and Remote Sensing in master’s programs related to Internet and Multimedia Engineering and Energy Engineering . Research Interests : Remote Sensing, Machine Learning, Image Segmentation, Data Fusion, Hyperspectral Imaging, UAV Applications. Key Techniques : CNN-MRF Hybrids, CRFNet, Probabilistic Graphical Modeling, Multiresolution Analysis. Her recent publications explore applications in wildfire mapping , urban land-use analysis , and hyperspectral-panchromatic fusion , with a focus on improving semantic segmentation accuracy through hybrid deep learning frameworks. She is available for office hours on request via email at martina.pastorino@unige.it .

• Computer Graphics
• Geometry Processing
• Computational Topology
• +۴ مورد دیگر

Michela Spagnuolo is a Research Director at the Italian National Research Council’s Institute of Applied Mathematics and Information Technology (CNR-IMATI-GE) since 2001. Her work bridges Computer Graphics , Geometry Processing , and Computational Topology , with applications in 3D Shape Analysis , Cultural Heritage , and Bioinformatics . Co-supervised 6 PhD theses (plus 2 ongoing) Associate Editor for journals like The Visual Computer and Computers&Graphics Chair of conferences including Shape Modeling International and EG Workshops on 3D Object Retrieval Research Interests : Focus on geometric and semantic modeling of 3D objects , computational topology for shape analysis , and structural/similarity evaluation . Her work enables advanced 3D search engines , semantic annotation , and medical imaging applications . Article Trends : Recent publications emphasize mesh quality indicators for Virtual Element Methods in engineering simulations and semantic-driven 3D model analysis for medical diagnostics and cultural heritage . Key subtopics include topological decomposition , data processing services , and multi-scale modeling . Scientific Awards : Fellow of the Eurographics Association (2014) Notable Contributions : Led projects like IQmulus (geospatial data analytics) and MultiScaleHuman (medical shape modeling). Pioneered CIDOC CRMdig for cultural heritage documentation and developed techniques for kernel computation in polyhedra .

• Communication design
• Design for all
• Design for crafts
• +۱۲ مورد دیگر

Marco Bozzola is an Associate Professor at the Department of Architecture and Design (DAD) of Polytechnic University of Turin. He serves as Deputy Coordinator of the College of Architecture and Design and holds key roles in Polito's Spin-Off Evaluation Commission and Patent Commission. Research areas: Design for Cultural Heritage, Design for Territory, Packaging Design ERC sectors: SH5_8 (Cultural heritage), PE8_10 (Industrial design), SH7_5 (Sustainability sciences) His work focuses on enhancing cultural heritage through multidimensional design interventions, including signage systems, narrative artifacts, and inclusive strategies. He explores sustainable packaging solutions and territorial development projects, particularly for SMEs and artisanal businesses. Recent publications analyze intercultural design methodologies and environmental sustainability in packaging. Prof. Bozzola holds editorial roles in ARCHALP (2018-) and Architecture Design Technology (2017-) and has received prestigious awards like ADI Compasso d'Oro (2013). He supervises PhD students Claudia Rolletto, Monica Oddone, and Irene Caputo.