جست‌وجوی استاد و پژوهشگر

• Data Science
• Database Systems
• Machine Learning
• +۱۱ مورد دیگر

Silvia Anna Chiusano is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino , Italy. She is a member of the DBDM - Database and Data Mining Group and the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory . She actively serves on PhD collegia for the Computer and Systems Engineering program and contributes to academic governance through course planning boards. Research Interests: Her primary research areas include Data Science, Database Systems, Machine Learning, Artificial Intelligence, Smart Cities, Urban Intelligence, Business Intelligence, and E-health . Her work integrates advanced data analytics with real-world applications in urban mobility, transportation safety, cultural heritage digitization, and aerospace engineering. She applies techniques in natural language generation, explainable AI, and spatiotemporal data mining. Recent Publications Trends: Her recent publications (2022–2025) reflect a strong focus on leveraging AI and data science for societal and industrial challenges. Key themes include autonomous vehicle safety, urban mobility forecasting, natural language generation from structured data, database design tools, and smart city applications . Her work appears in journals like INFORMATION and INFORMATION SYSTEMS , and conferences such as IEEE AICT , ADBIS , and SEBD . Scientific Awards: No scientific awards are listed in the provided text. Advising and Grants: She supervises two PhD students: Andrea Avignone (Urban Data Science) and Davide Napolitano (Neural Explainers and Multimodal Learning). She has led multiple research projects, including: FI-WARE (EU-funded, 2014) – Scientific Director I-DREAM (2024–2027) – Scientific Head (Commercial) R&D Motion Sickness Prediction Model (2019) – Scientific Director Study and design of algorithms for Internet of Boilers (2017–2019) – Scientific Manager These projects span EU and commercial funding, highlighting her ability to translate research into practical engineering solutions. Labs and Research Groups: She is a core member of the DBDM - Database and Data Mining Group (DAUIN) and contributes to the SmartData@PoliTO center, which focuses on big data and data science applications for societal and industrial innovation.

• Multimedia Data Management
• Collaborative Filtering
• Similarity Search
• +۵ مورد دیگر

Ilaria Bartolini is a Full Professor at the University of Bologna's Department of Computer Science and Engineering, specializing in multimedia data management and preference learning. She coordinates the MultiMedia Database Group and leads the PhD Programme in Computer Science and Engineering. Her research focuses on similarity search, collaborative filtering, and applications in cultural heritage and health domains. Education: Laurea in Computer Science (1997), University of Bologna PhD in Electronic and Computer Science Engineering (2002), University of Bologna Research Interests: Her work spans multimedia systems, data curation, and AI-driven solutions for healthcare and cultural heritage. She collaborates with institutions like HKUST, NJIT, and the European Processor Initiative, leading projects such as DETECt (EU H2020) and S-PIC4CHU (PRIN 2022). Grants & Projects: EU H2020 DETECt (2018–present): Transcultural crime narrative analysis PRIN 2022 S-PIC4CHU (2024–present): Data science integrity GenData 2020, WISDOM, COOPERARE (Italian national projects) Teaching: Leads courses on web applications, multimedia data management, and digital humanities at the undergraduate and graduate levels. Her educational framework emphasizes active e-learning through tools like ALDO. Labs & Teams: Directs the MultiMedia Database Group, fostering interdisciplinary research in data science and AI applications.

• Robotics
• Precision Agriculture
• Vehicle Dynamics
• +۵ مورد دیگر

Giulio Reina serves as a Full Professor in the Department of Mechanics, Mathematics and Management at the Polytechnic University of Bari, Italy. His academic focus centers on robotics and mechanical systems with strong applications in agricultural automation and vehicle dynamics. His research spans Robotics , Precision Agriculture , and Vehicle-Terrain Interaction Modeling . Key contributions include developing path-planning frameworks for agricultural robots, deformable tire models for obstacle negotiation, and yield estimation systems using deep learning in viticulture. His work integrates mechanical engineering principles with AI-driven solutions for field robotics applications. Analysis of his recent publications reveals a strong emphasis on mobile robotics for agricultural automation , particularly in grapevine monitoring and terrain interaction. His research bridges theoretical modeling (e.g., multibody dynamics) with practical implementations in off-road vehicles and farmer robots, consistently addressing challenges in precision agriculture through sensor fusion and machine learning. No specific scientific awards were documented in the provided materials. Professor Reina leads research in agricultural robotics without explicit mention of formal student advising in the source text. His work demonstrates significant focus on practical implementations for sustainable farming, including terrain estimation systems and autonomous navigation solutions for uneven agricultural environments. His laboratory activities center on agricultural robotics development, featuring projects like the SNAP lightweight vehicle platform and POLYPUS adaptive gripper systems. Current initiatives emphasize real-world deployment of farmer robots for crop monitoring and precision viticulture applications.

Eugenio Cesarioمشاهده پروفایل

دانشیار

• Data Mining
• Urban Data Analysis
• Smart Cities
• +۴ مورد دیگر

Eugenio Cesario is an Associate Professor of Computer Engineering at the University of Calabria, Italy. He is affiliated with the Department of Computer, Electronics and Systems Engineering (DiCES). His research focuses on data mining , smart city analytics , energy-efficient cloud computing , and bioinformatics . Cesario co-founded DTOK Lab S.R.L. and is a member of SCALAB. His work bridges computational methods with real-world challenges in urban planning, disaster prediction, and healthcare. Education : Holds a Ph.D. in Computer Engineering. No further educational details provided. Research Interests : Urban Data Analysis: Developing clustering algorithms for hotspot detection in smart cities. Energy-aware Cloud Computing: Optimizing cloud resource allocation with machine learning. Bioinformatics: Analyzing gene signatures in cancer research and RNA-sequencing. Disaster Prediction: Applying regression trees and machine learning to model tsunamis and crimes. Articles Trends : Recent work emphasizes multi-density clustering for urban and crime hotspot analysis, machine learning for energy efficiency , and biomedical data mining . Awards : No scientific awards explicitly mentioned. Advising & Grants : No student advisees or grant details provided. Focus appears to be on collaborative projects with SCALAB and industry partners like DTOK Lab. Labs & Teams : Leads SCALAB (Smart City Applications and Big Data Lab) and co-founded DTOK Lab S.R.L., specializing in data-driven solutions for urban and healthcare challenges.

Stefano Squartiniمشاهده پروفایل

استاد

• Electrical Engineering
• Audio Signal Processing
• Neural Networks
• +۲ مورد دیگر

Stefano Squartini is a Full Professor at the Polytechnic University of Marche, affiliated with the Department of Information Engineering. His research focuses on signal processing, audio engineering, and machine learning applications in embedded systems. Key interests include real-time audio generation, non-intrusive load monitoring, and biomedical signal analysis. His recent publications demonstrate a strong focus on AI-driven solutions for telecommunications, healthcare, and energy systems. Research spans generative models for audio restoration, deep learning for medical diagnostics, and optimization of renewable energy technologies. He maintains active collaboration in multi-disciplinary projects involving neural networks for industrial and clinical applications, with emphasis on low-latency implementations and edge computing.

Massimo Salviمشاهده پروفایل

استادیار

• Biomedical Engineering
• Medical Imaging
• Artificial Intelligence
• +۵ مورد دیگر

Massimo Salvi is an Assistant Professor at the Department of Electronics and Telecommunications of the Politecnico di Torino, Italy. His research focuses on biomedical signal and image processing, artificial intelligence, and deep learning, with a particular emphasis on developing hybrid techniques for complex biomedical problems. He leads projects in fluorescence microscopy analysis, dermatological imaging, and digital pathology. Education: Master’s in Biomedical Engineering (Politecnico di Torino, 2014), PhD in Biomedical Engineering (Politecnico di Torino, 2018). Research areas include synthetic image generation via GANs, AI-driven diagnostics, and stain normalization in histology. Key Projects: REAP (cancer cell analysis), DIPAT3-Care (digital pathology pathways), and automated solutions for microscopy imaging. Teaching activities include courses at DET@POLITO. Research Contributions: Over 150 publications in AI-driven medical imaging, including work on uncertainty quantification, augmented reality in surgery, and histological image synthesis. His work bridges clinical needs with computational innovations. Awards: No awards explicitly listed for Salvi in the provided text.

• Augmented Reality
• Construction Safety
• Building Information Modeling (BIM)
• +۵ مورد دیگر

Francesco Spegni is a Researcher at the Department of Civil, Building and Environmental Engineering (DICEA) within the School of Engineering at Marche Polytechnic University (UNIVPM), Italy. His work integrates advanced computational methods with civil engineering applications, focusing on built environment management through cutting-edge technological solutions. His research spans Augmented Reality , Construction Safety , Building Information Modeling , Facility Management , and Blockchain systems. Key investigations include marker-less AR registration for infrastructure inspections, cybersecurity in construction processes, and mixed reality applications for facility operations. His interdisciplinary approach bridges computer science and civil engineering to solve practical challenges in construction safety and infrastructure management. Analysis of his 2023-2025 publications reveals a dominant trend toward seamless integration of cyber-physical systems in built environments. Core themes include marker-less augmented reality for indoor/outdoor transitions, blockchain notarization of BIM processes, and natural language processing for safety management. His work consistently targets real-world implementation challenges in unprepared environments, emphasizing accuracy, interoperability, and practical usability for construction and facility management professionals.

• Forensic Psychology
• Human-Computer Interaction
• Deception Detection
• +۳ مورد دیگر

Merylin Monaro is an Assistant Professor at the University of Padua, Italy. Her research focuses on interdisciplinary applications of technology in psychology, including deception detection, mental health interventions, and human-computer interaction. She leads studies on forensic psychology in digital spaces, stress management through AI-driven tools, and user behavior analysis in virtual environments. Research Interests : Forensic Psychology & Cybercrime Analysis Machine Learning in Behavioral Assessment Augmented Reality & User Experience Design Psychometric Methods for Deception Detection Mental Health Technology Innovation Her work explores the intersection of technology and human behavior, with recent emphasis on metaverse-related legal challenges, AI ethics in psychological testing, and digital solutions for adolescent well-being. Publications span over 50 peer-reviewed articles since 2014, focusing on biometric authentication, online identity verification, and predictive mental health models. Recent Trends in Work : 2024-2025 research highlights include: Development of AI chatbots for WHO-validated stress management protocols Forensic analysis of metaverse sexual crime dynamics Pioneering VR-based memory testing methodologies Machine learning frameworks to detect response bias in psychological assessments No scientific awards explicitly mentioned, but her work demonstrates significant contributions to interdisciplinary research methods. Active in collaborative projects involving computer science and psychology departments, though specific lab affiliations are not detailed in the provided texts.

• Operations Research
• Optimization
• Problem Solving
• +۲ مورد دیگر

Anthony Sforza is a Full Professor of Operations Research at the University of Naples “Federico II”, affiliated with the Department of Electrical Engineering and Information Technologies. He leads the Optimization and Problem Solving Laboratory and can be reached at antonio.sforza@unina.it. His work focuses on applying operations research methodologies to complex engineering and technological challenges. Research interests include optimization algorithms, systems engineering, and the integration of information technologies with operational decision-making processes. His laboratory specializes in developing innovative solutions for real-world problem-solving scenarios. No academic awards or grants are explicitly listed in the provided text. No advised students or recent publications are detailed here.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +۵ مورد دیگر

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

• Air Quality Monitoring
• Sensor Networks
• Traffic Engineering
• +۵ مورد دیگر

Laura PO is an Associate Professor in the Department of Engineering 'Enzo Ferrari' at the University of Modena and Reggio Emilia. Her work focuses on environmental informatics, sensor networks, and data-driven solutions for smart cities. She leads research in air quality monitoring, traffic analysis, and crime event extraction using advanced techniques like machine learning and knowledge graphs. Research Interests: Laura specializes in sensor data calibration (e.g., HypeAIR framework for PM sensors), anomaly detection in sensor networks, and semantic modeling for urban systems. Her interdisciplinary projects combine environmental engineering with computer science, addressing challenges like hygroscopicity correction in low-cost sensors and real-time traffic flow simulations. Key Projects: She is a principal investigator in the TRAFAIR EU project, which integrates traffic and air quality data to create predictive models and visualization tools. Her contributions include the AirMLP neural network for PM2.5 correction and the CEM ontology for crime event analysis. She collaborates with institutions like Wiseair SRL and Arpa Piemonte to deploy sensor networks and validate environmental data. Technical Contributions: Laura's work spans frameworks like H-BOLD for Linked Data visualization, the DICE crime news dataset, and the SenseBoard dashboard for sensor management. She emphasizes reproducibility, publishing code (e.g., AirMLP source code) and datasets (e.g., SPS30 sensor data). Collaborations: Her research involves European partners in Spain (Universidad de Zaragoza) and Italy, addressing urban sustainability through sensor networks, traffic modeling, and open data integration. She also contributes to open-source platforms like the TRAFAIR air quality dashboard and semantic traffic data frameworks.