جست‌وجوی استاد و پژوهشگر

Maurizio Righettiمشاهده پروفایل

استاد

• Hydraulic Engineering
• Water Resources Management
• Climate Change Impacts
• +۲ مورد دیگر

Maurizio Righetti is a Full Professor at the Free University of Bozen-Bolzano within the Faculty of Agricultural, Environmental and Food Sciences. His research integrates hydraulic engineering, climate change adaptation, and sustainable water management, with a focus on Alpine environments. Research Interests: Righetti's work spans: Hydraulic systems optimization (e.g., sediment flushing, water distribution networks) Climate model bias correction for hydrological forecasting Renewable energy integration in water infrastructure Machine learning applications in ecohydraulics and resource management Impacts of hydropeaking and climate change on river ecosystems Recent Publications: His 15 most recent articles (2024-2025) demonstrate strong trends in: sediment dynamics modeling, AI-driven leak detection in water networks, climate data processing, and hybrid energy-water systems. Over 60% leverage machine learning, reflecting a shift toward data-centric environmental solutions. Engagement: He co-founded AIAQUA (unibz's water management spin-off) and leads public initiatives like "Action For Climate" to address climate-water linkages in Alpine regions.

• Quality Engineering
• Statistical Process Control
• Innovative Production Systems
• +۳ مورد دیگر

Elisa Verna is a Fixed-term Tenure-Track Assistant Professor at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino, Italy. She is a member of the Quality Engineering and Management Group and contributes to teaching in Management Engineering programs. Her research focuses on Quality Engineering, Statistical Process Control, and Innovative Production Systems.

• Biomedical Imaging
• Medical Physics
• Cultural Heritage Technology
• +۴ مورد دیگر

Alessia Artesani is an Assistant Professor in the Department of Biomedical Sciences at Humanitas University in Milan, Italy. She holds a PhD in Physics from Politecnico di Milano and has expertise in biomedical imaging, medical physics, and cultural heritage technology. Her research focuses on parametric PET imaging techniques, motion correction in medical imaging, and terahertz spectroscopy for material analysis. Education: 2015–2019: PhD in Physics, Politecnico di Milano 2011–2014: MSc in Physics, Università degli Studi di Milano Her research interests include: - Development of advanced PET imaging protocols for clinical applications - Application of terahertz spectroscopy in art conservation and material science - Investigating motion artifacts in dynamic medical imaging - Correlation between metabolic imaging and clinical outcomes in oncology. Awards include a €2,500 grant from Lorentz Workshop Competition (2021) and €1,000 Bando Cassini award (2017). She has also received the Best Communication Award at the 2016 SIF National Congress. Her work bridges biomedical imaging with cultural heritage technologies, demonstrated by publications in both clinical and material science domains. Current research emphasizes translational applications of imaging techniques for improving diagnostic accuracy in oncology and preserving art materials.

• Human-Centered Design
• Ergonomics and Safety Engineering
• Affective Computing
• +۵ مورد دیگر

Prof. Maura Mengoni is an Associate Professor at the Department of Industrial Engineering and Mathematical Sciences of the University of Macerata (UNIVPM). Her work focuses on human-centered design methodologies integrating advanced technologies like AI-driven systems, XR applications, and affective computing. She leads research in smart manufacturing systems, ergonomic assessment tools, and inclusive technology development for diverse user groups including people with disabilities. Key projects include SOPHIA's IoT architecture for predictive maintenance and emotion-aware interfaces for automotive safety. Research interests span industrial automation, virtual/augmented reality applications, and multimodal interaction design. Recent studies investigate cognitive workload in driving simulators, emotion-based museum experiences, and facial expression analysis for educational evaluation. Her work bridges engineering with humanities through projects like Civitas, enhancing cultural heritage accessibility via spatial augmented reality at Urbino’s Ducal Palace. Publications emphasize interdisciplinary approaches, including collaborative designs with end-users for accessible technologies and data fusion techniques in manufacturing. She has pioneered systems linking customer emotions to shopping experiences and developed tools for ergonomic risk assessment using RGB camera networks.

Alessio Orsinoمشاهده پروفایل

پژوهشگر ارشد

• Big Data Analysis
• Distributed Computing
• Edge-Cloud Computing
• +۵ مورد دیگر

Alessio Orsino is a Research Fellow at the Department of Computer Science, Modeling, Electronics and Systems Engineering (DIMES) at the University of Calabria. His academic journey includes a Ph.D. in Information and Communication Technologies (ICT) awarded in January 2025, a Master’s in Computer Engineering (Big Data Analytics and Data Science) from 2020, and a Bachelor’s in Computer Engineering from 2018, all from the University of Calabria. He also served as a visiting researcher at the University of Cambridge’s Department of Computer Science and Technology (July–December 2023). His research focuses on big data analysis, distributed computing, machine learning, and edge-cloud integration. He contributes to projects like ASPIDE (Exascale programming models) and INSIDER (cloud-edge IoT deployment optimization), funded by EU Horizon 2020 and Italy’s MIUR. He is a contract professor at DIMES and a member of the Scalable Computing and Cloud Laboratory (SCALab). Orsino’s work bridges theoretical and applied computing, emphasizing efficient machine learning on resource-constrained systems and real-time adaptive models for edge environments. His publications address edge-cloud continuum challenges, adversarial robustness in AI, and scalable big data frameworks. Key grants include Horizon 2020 (ASPIDE) and PRIN 2022 (INSIDER), supporting his interdisciplinary research in hybrid cloud-edge infrastructures and data-intensive applications. He has authored/co-authored a book on big data programming and collaborates internationally through visiting positions and lab engagements.

Sergio Grecoمشاهده پروفایل

استاد

• Database Theory
• Data Integration
• Inconsistent Data Processing
• +۳ مورد دیگر

Sergio Greco is Full Professor at University of Calabria's DIMES Department, Coordinator of the Computer Engineering Degree, and Vice-president of the Computer Engineering national Group. His research spans database theory, data integration, inconsistent data processing, and computational logic. Research Focus: Development of theoretical frameworks for data management including argumentation frameworks, knowledge base querying under inconsistency, and decentralized learning systems. Recent work integrates machine learning with formal reasoning methods. Honors: Best Paper Award at International Conference on Logic Programming (2020) Best Paper Award at RuleML Symposium (2014) Leads projects on cybersecurity and data management funded by EU and Italian Ministry of Research, coordinating national and international research groups.

Roberto Salaمشاهده پروفایل

استادیار

• Data-Driven Decision Making
• Maintenance Engineering
• Industry 4.0
• +۲ مورد دیگر

Roberto Sala is Assistant Professor at the University of Bergamo's Department of Management, Information and Production Engineering, and member of the CELS Research Group. He received his Ph.D. from Bergamo in 2021 with a thesis on data-driven maintenance service delivery. Research interests include data-driven decision-making for industrial systems, maintenance optimization, Industry 4.0 implementation, and digital servitization in manufacturing. He participates in regional, national and European research projects transforming industrial service models. Recent publications (2023-2025) address digital servitization trends, AI education frameworks, sustainable PSS assessment, and NLP applications in maintenance services. Work consistently bridges theoretical models with industrial case studies.

Arti Ahluwaliaمشاهده پروفایل

استاد

• In-vitro models
• Biomaterials
• Tissue Engineering
• +۳ مورد دیگر

Arti Ahluwalia is Professor of Bioengineering at the University of Pisa's School of Engineering, affiliated with the Research Center 'E. Piaggio' and serving as Director of the Interuniversity Center for the Promotion of the 3Rs Principles in Teaching and Research (Centro 3R). With a multidisciplinary background spanning physics, instrumentation science, and bioengineering, her research integrates biomaterials, microfabrication, and computational modeling. Research focuses on human-based organ and system models using soft materials, cell derivatives, and intelligent bioreactor design. Current projects include: in-vitro models of metabolic disease/aging, nanotoxicology, advanced imaging, and open biomedical engineering education. Her work has produced commercialized multicompartment bioreactors through spin-off companies Kirkstall Ltd and IVTech srl. Recent publications demonstrate strong emphasis on open-source medical devices, 3Rs principles implementation, and computational platforms for nanotoxicology and cellular construct design. Key themes include regulatory frameworks for open-source medical technology, diagnostic tools for resource-limited settings, and ethical alternatives to animal testing. Teaching encompasses Biomechanics of Tissues, Micro & Nanobioscopy, and Design Principles for Bionics Engineering across undergraduate and graduate biomedical engineering programs.

Gigliola Vagliniمشاهده پروفایل

استاد

• Distributed Systems Verification
• Model Checking
• Machine Learning Applications
• +۲ مورد دیگر

Gigliola Vaglini is Full Professor of Computer Engineering at the University of Pisa's Department of Information Engineering. She teaches Software Systems Engineering and Databases, with research focusing on formal specification and verification of concurrent/distributed systems. Her work integrates model checking methodologies with machine learning techniques for industrial anomaly detection and mobile security applications. She has participated in multiple research projects funded by the Italian Ministry of University and Research, National Research Council, and European Community. Research Focus: Vaglini's work bridges theoretical computer science and practical applications, developing verification frameworks for complex systems while creating AI solutions for real-world problems. Her current investigations span swarm intelligence coordination, structural monitoring via digital twins, and multimodal deep learning architectures. Recent publications demonstrate cross-disciplinary approaches combining formal methods with machine learning, particularly in environmental monitoring, structural engineering, and neural architecture design. This reflects a consistent pattern of translating theoretical computer science concepts into applied technological solutions.

Enzo Tartaglioneمشاهده پروفایل

دانشیار

• Deep Learning
• Model Compression
• Pruning
• +۶ مورد دیگر

Enzo Tartaglione serves as Associate Professor at Télécom Paris, Institut Polytechnique de Paris, holding a Hi!Paris chair and contributing as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems. His academic journey spans multiple institutions across Europe and the US, reflecting a strong interdisciplinary foundation. Educational milestones include: MS in Electronic Engineering, Politecnico di Torino (2015, cum laude) MS in Electrical and Computer Engineering, University of Illinois at Chicago (2015, magna cum laude) MS in Electronics, Politecnico di Milano (2016, cum laude) PhD in Physics, Politecnico di Torino (2019, cum laude), thesis: 'From Statistical Physics to Algorithms in Deep Neural Systems' His research centers on efficient deep learning , with pioneering work in model compression, neural pruning, and debiasing techniques. He actively develops methods for privacy-aware learning and green AI, targeting real-world deployment constraints in computer vision and medical imaging applications. His approach bridges theoretical physics with practical AI optimization. Recent publications (2024-2025) demonstrate consistent focus on computational efficiency, with 60% of works addressing model compression for vision tasks, 25% on bias mitigation, and emerging contributions in privacy preservation. Key venues include ICCV, CVPR, and IEEE Transactions, reflecting strong industry-academia impact. Scientific recognition includes: Finalist for Multimedia Rising Star Award (2025) He mentors 10 active PhD candidates across compression, debiasing, and on-device learning domains, having previously guided 3 PhD graduates and 17+ Master's researchers. Research funding includes the Hi!Paris GIFFAI project (2025) for frugal AI and ANR's BANERA initiative (2024) on bias-aware architecture search. His group operates within Télécom Paris' joint laboratory, driving the Frugal AI initiative through collaborations with ELLIS Society partners and industry stakeholders focused on sustainable deep learning deployment.

• Computer Networks
• Immersive Video Streaming
• Information Centric Networking
• +۳ مورد دیگر

Giuseppe Ribezzo is affiliated with the C3Lab, focusing on advanced networking and multimedia systems research. His work emphasizes immersive video streaming optimization, information-centric networking (ICN), and IoT middleware design. He has contributed to developing tools like TAPAS-360 for evaluating 360° video streaming systems and exploring adaptive bitrate control mechanisms using DASH protocols. Research interests include optimizing network bandwidth for immersive content, improving industrial IoT communication via IEEE 802.15.4 protocols, and enhancing streaming QoE through innovative compression and resolution adaptation techniques. His publications span from 2015 to 2021, addressing challenges in both theoretical frameworks and practical implementations. No scientific awards or student advisees are explicitly listed in the provided materials. Collaborations and grants are not detailed here, but his work aligns with C3Lab’s focus on cutting-edge telecommunications and multimedia systems.

Vito Andrea Racanelliمشاهده پروفایل

پژوهشگر

• Control Systems
• Autonomous Systems
• Robotics
• +۳ مورد دیگر

Vito Andrea Racanelli is a Researcher at the Department of Electrical and Information Engineering, Politecnico di Bari, Italy. He holds a PhD in Control Engineering (2025) and a cum laude Master's degree in Control Engineering (2021). His research focuses on control strategies for autonomous systems, including industrial vehicles, UAV swarms, and adaptive video streaming. He is affiliated with the Control Engineering and Computer Science Laboratory (C3Lab), collaborating on robotics and control theory projects. Education: Bachelor/Master: Politecnico di Bari (2016–2021), Thesis: 'Autonomous Driving Systems: The AGV's Case' PhD: Politecnico di Bari (2021–2025), Focus: Model Predictive Control, Networked Systems, and Autonomous Mobile Robots Research interests span Model Predictive Control (MPC), decentralized coordination of UAV swarms, fault-tolerant industrial automation, and medical technology applications (e.g., insulin delivery systems). His work bridges control theory with real-time systems, emphasizing safety and adaptability in dynamic environments. His publications highlight advancements in MPC-based video streaming optimization, event-triggered consensus algorithms for live streaming, and GAN-based depth reconstruction for mmWave sensors. He has presented at top conferences like IEEE CCNC, IFAC SAFEPROCESS, and ICUAS. Advising/grants: No formal advisees listed. Collaborates on C3Lab projects funded by EU and national initiatives in robotics and control systems. Labs/Teams: Active member of C3Lab, contributing to interdisciplinary research in robotics, networked control, and AI-driven systems.

Raffaele Carliمشاهده پروفایل

دانشیار

• Control Systems Engineering
• Energy Systems Management
• Industrial Automation
• +۴ مورد دیگر

Prof. Raffaele Carli is an Associate Professor in Systems and Control Engineering at Politecnico di Bari, Italy. He holds a PhD in Electrical and Information Engineering (2016) and has been qualified as a Full Professor since 2023. His roles include technical lead of the Decision and Control Laboratory (DCLAB) and Vice-Coordinator of the National PhD program in Autonomous Systems (DAuSy). He has extensive editorial roles, including Associate Editor for IEEE Transactions on Automation Science and Engineering and IEEE Transactions on Systems, Man, and Cybernetics. Education: Laurea (Master’s) in Electronic Engineering (2002), PhD in Electrical and Information Engineering (2016), both from Politecnico di Bari. Professional experience includes roles as a System Engineer in the defense sector (2004–2012) and military service as a Reserve Officer (2003–2004). Research focuses on decision and control techniques for energy systems, industrial automation, and complex systems. Key areas include smart grids, energy communities, robotics, and optimization. Recent work emphasizes distributed control for renewable energy integration, human-robot collaboration, and sustainable manufacturing. Publications span 120+ international articles in journals like IEEE Transactions and conferences such as CDC and CASE. His research trends include game-theoretic control, MPC applications, and energy system optimization. Awards include the 2024 IEEE Italy SMCS Chapter Award and recognition for editorial contributions. Advising 8 current PhD students and supervising 7 past candidates. Active in organizing international conferences (e.g., General Chair of SENSYS 2025). Grants include projects on energy communities and smart city technologies funded by the Apulia Region. Labs include the Decision and Control Laboratory (DCLAB), focusing on automation, energy systems, and industrial applications. Collaborations with global institutions like TU Delft, UPC Barcelona, and Chinese Academy of Sciences.

Graziana Cavoneمشاهده پروفایل

استادیار

• Decision Support Systems
• Modeling and Control of Complex Systems
• Transportation Systems Optimization
• +۴ مورد دیگر

Graziana Cavone is an Assistant Professor in Systems and Control Engineering at the University Roma Tre. She holds a Ph.D. in Electronic and Information Engineering from the University of Cagliari and is qualified as an Associate Professor in Automatica. Her research focuses on decision support systems, transportation networks, energy systems, and industrial automation, with expertise in Model Predictive Control (MPC), Petri Nets modeling, and resilient infrastructure design. Education: Ph.D. (Excellent with Honors), Electronic and Computer Engineering, University of Cagliari (2018) Master’s (Summa Cum Laude), Control Engineering, Polytechnic of Bari (2013) Research Interests: Optimization of intermodal transport terminals and railway networks Energy-efficient building management and microgrids Cyber-physical systems in Industry 4.0 Resilient critical infrastructure control Human-robot collaboration and safe ergonomics Grants & Leadership: Principal Investigator for a National Natural Science Foundation of China grant (2020–2021) Recipient of multiple RTD-B and research fellowships in control systems and automation Organizer of international conferences like IEEE CASE 2024 and MED 2021 Labs & Collaborations: Member of the Decision and Control Laboratory at University Roma Tre Collaborations with institutions like Delft University of Technology and Southwest Jiaotong University Industry partnerships with Enel, Fiat Chrysler Automobiles, and Elettric80

Nicola Cordeschiمشاهده پروفایل

استادیار

• Adaptive Wireless Communication
• Internet of Things
• Cognitive Radio Access
• +۶ مورد دیگر

Dr. Nicola Cordeschi is an Assistant Professor in Telecommunications at Polytechnic University of Bari's Department of Electrical and Information Engineering. He earned his Laurea degree (summa cum laude, 2004) and Ph.D. (2008) in Electronic Engineering from Sapienza University of Rome. Contact: +39 080 5963913. Research spans adaptive wireless systems and IoT: Q-learning approaches for wireless energy transfer systems Multi-link optimization in IEEE 802.11be networks Quantum network entanglement distribution strategies Optimized MAC protocols for IoT networks Awarded 2nd Best Paper at ICT-DM 2023 for work on scheduling algorithms in wireless-powered IoT. Teaching includes Internet of Things courses.