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Gianni Bianchini is an Associate Professor at the University of Siena, affiliated with the Department of Information Engineering and Mathematics. His research focuses on control systems theory, aerospace control, smart grids, and haptics. He holds a PhD in Control Systems Engineering from the University of Bologna (2001) and a bachelor's degree in Electronic Engineering from the University of Florence (1997). He teaches courses on Advanced Control Systems and Digital Control at the master's and undergraduate levels. His research emphasizes Model Predictive Control (MPC), spacecraft trajectory optimization, renewable energy systems, and energy management in smart buildings. Notable contributions include robust MPC algorithms for autonomous rendezvous, optimal solar energy storage systems, and haptic interface design. His work often bridges theoretical control methodologies with practical applications in aerospace and energy sectors. Recent publications (2022–2025) highlight advancements in variable-horizon MPC for spacecraft guidance, solar battery optimization, and renewable energy communities. He collaborates with groups like the Systems and Control, Smart Grids, and Aerospace teams at his department. No scientific awards are explicitly mentioned, though his extensive publication record underscores his scholarly impact.

• Control Systems Theory
• Aerospace Control
• Smart Grids
• +5 more

Angelo Cenedese is an Associate Professor at the Department of Information Engineering (DEI), University of Padova, and leads the SPARCS Lab (Flying Arena and Mobile Robotics Laboratory). He co-leads the NAVLAB (Autonomous Navigation Laboratory) and holds senior roles in IEEE societies, including the Control Systems Society (CSS) and Robotics and Automation Society (RAS). His academic activities span teaching, editorial work as Associate Editor for IEEE Transactions on Industrial Informatics, and leadership in research projects focusing on robotics, control systems, and multi-agent networks. His research interests include robotics , control systems , multi-agent coordination , computer vision , autonomous navigation , and industrial automation . His recent publications emphasize machine learning for industrial vision systems, adaptive control in aerospace robotics, distributed state estimation , and secure UAV navigation under GNSS spoofing. Key trends involve edge computing , collaborative robotics , and AI-driven optimization . Scientific Awards: Award for 'Most Innovative Application' at Quality Control by Artificial Vision Conference (QCAV 2019) His projects include AI in Manufacturing (AIMS5.0), Sustainable Mobility (PNRR-MOST), and 6G Networking (PREDICT-6G), often in collaboration with Italian and international institutions. Teaching roles cover Robotics and Control , Networked Control Systems , and Computer Vision courses at both undergraduate and graduate levels.

• Robotics
• Control Systems
• Multi-Agent Systems
• +5 more

Giulia De Pasquale is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology, specializing in Control Systems. Her research focuses on social network interventions, optimization algorithms, and fairness in AI systems. She leads the Control Systems Group, addressing challenges in distributed control, hypergraph reconstruction, and ethical algorithm design. Her work integrates machine learning, network science, and control theory to develop fair and safe recommendation systems. Recent projects include hypergradient-based optimization for social network interventions and optimal transport approaches to fairness in influence maximization. She actively collaborates with institutions like Santa Fe Institute and UC San Diego. Giulia organizes interdisciplinary workshops on algorithmic fairness and has presented at NeurIPS, CDC, and NetSci. She advises PhD students like Alessandro Casu and hosts visiting scholars such as Camilla Quaresmini. Her research has been published in prestigious venues including Nature Communications and ICML.

• Control Systems
• Social Network Analysis
• Optimization Algorithms
• +3 more

Francesco Amigoni is affiliated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. His research focuses on robotics, multi-agent systems, and machine learning, with applications in autonomous systems, anomaly detection, and energy systems. He has contributed to advancements in multi-agent coordination, path planning, and predictive maintenance through interdisciplinary approaches. Key research areas include: Multi-Agent Systems: Task allocation, cooperative robotics, and deadlock prevention in dynamic environments Machine Learning: Anomaly detection, transfer learning, and neural networks for battery lifecycle analysis Autonomous Robotics: Exploration strategies, SLAM algorithms, and map completeness estimation Data Mining: NLP-driven classification of road accidents and healthcare system analysis His work bridges theoretical foundations with real-world applications, addressing challenges in energy systems, environmental monitoring, and healthcare management. Recent studies highlight innovations in lithium-ion battery prognostics and swarm robotics fault detection.

• Robotics
• Multi-Agent Systems
• Machine Learning
• +3 more

Vincenzo Caglioti is a Professor at the Department of Electronics, Information and Bioengineering (DEIB) of Politecnico di Milano. His research focuses on computer vision, robotics, and image processing, with emphasis on motion analysis, sensor fusion, and multi-robot systems. He has contributed extensively to fields such as augmented reality, motion blur recovery, and uncalibrated camera systems. Key research areas include: Development of algorithms for 3D reconstruction from motion-blurred images Design of efficient exploration strategies for mobile robots Integration of sensor data for environmental monitoring and autonomous navigation Analysis of geometric properties in catadioptric systems His work spans theoretical advancements in computer vision alongside practical applications in robotics and surveillance. Over 30 years of publications demonstrate a sustained contribution to advancing perception systems for autonomous systems. No scientific awards explicitly listed in provided texts Labs/Teams: Likely affiliated with DEIB's Robotics and Computer Vision research groups, though specific lab names not explicitly stated in text.

• Computer Vision
• Robotics
• Image Processing
• +5 more

Gianluca Campana is a Full Professor at the University of Padua, specializing in visual neuroscience and neuroplasticity. His research focuses on perceptual priming, learning, and the application of brain stimulation techniques like TMS and tRNS to enhance visual functions in clinical populations such as amblyopia, myopia, and dyslexia. He investigates mechanisms underlying motion perception, form-motion integration, and cognitive benefits of exergames and video games in aging populations. His work bridges basic neuroscience with applied interventions, aiming to improve visual and cognitive deficits through neurotechnological approaches. Research interests include transcranial electrical stimulation mechanisms, perceptual learning paradigms, and the neural basis of motion processing. He explores how sensory and parietal cortices contribute to visual perception and memory. Notable projects include DOMHO (2020), an IoT system for ambient assisted living, integrating neuroscience principles into technology. Recent studies highlight interventions combining action video games with parietal tRNS to boost reading fluency in dyslexia and exergame training's impact on mood/cognition in older adults. His lab also examines motion detection in dogs and humans, revealing parallels in perceptual mechanisms. Key contributions include characterizing contrast-mediated collinear interactions and advancing understanding of visual working memory’s role in serial dependence. His work underscores the dynamic interplay between neural plasticity and external stimuli in optimizing sensory and cognitive functions.

• Visual Neuroscience
• Perceptual Learning
• Brain Stimulation Techniques
• +3 more

Marianna Valente is an Assistant Professor at Politecnico di Torino, Italy, affiliated with the Department of Management and Production Engineering. Her research bridges aerospace engineering, climate science, and space technology applications, with a particular focus on how climate change impacts aviation systems and how space-based solutions can address these challenges. Dr. Valente's research interests center on aerospace engineering applications with climate relevance. Her work spans satellite data analysis for atmospheric monitoring, structural dynamics of aerospace components, and climate change impacts on aviation operations. She has developed methodologies for assessing gust spectra via satellite data, analyzing membrane structure vibrations, and monitoring turbulence for aviation safety. Her research demonstrates how space technologies can provide critical data for adapting aviation systems to changing climate conditions. The publication trends show consistent output from 2023-2025, with research spanning both theoretical structural analysis and practical climate-aviation applications. Her work appears in reputable aerospace and engineering venues, indicating recognition within these fields. The research demonstrates a progression from fundamental structural analysis to increasingly applied climate-aviation-space technology integration. Dr. Valente's research has garnered international attention, with significant engagement from North American, European, and Asian institutions. Her work appears particularly relevant to aerospace industry stakeholders and climate adaptation researchers, as evidenced by the geographical distribution of interest in her publications. Her advising approach likely emphasizes interdisciplinary research that connects engineering fundamentals with real-world climate challenges. Given her publication record, she probably encourages students to work at the intersection of aerospace engineering, data science, and climate impacts, preparing them for careers addressing some of aviation's most pressing contemporary challenges. Dr. Valente leads the Aerospace and Climate Impact Research Group, which focuses on applying space-based technologies to understand and mitigate climate effects on aviation systems. The group's work combines satellite data analysis, structural engineering principles, and climate science to develop practical solutions for the aviation industry facing changing atmospheric conditions.

• Aerospace Engineering
• Climate Change Impacts on Aviation
• Space Technologies
• +3 more

Didier Galmiche is a Professor of Computer Science at Université de Lorraine, where he serves as Scientific Leader of the TYPES Group (Logic, Proof Theory and Programming) and Director of the Master Programme in Computer Science. He directs the DEPEND Erasmus Mundus Joint MSc in Advanced Systems Dependability. His research centers on computational logic, automated deduction, and formal verification, with specific interests in proof-search methods, substructural logics, and logical modeling of concurrent systems. The TYPES group develops software tools for theorem proving including IBiS, SigBi, STRIP, and BILL. Recent publications focus on separation logic, epistemic logics, and tableaux methods, demonstrating applications in program verification and automated reasoning. His work shows consistent innovation in proof-theoretic approaches across intuitionistic, linear, and non-commutative logics. He leads multiple research initiatives including the OPERATION CONTRA project studying logical methods for system reliability. No scientific awards are mentioned in the provided materials. Galmiche heads the TYPES group at LORIA UMR 7503, collaborating with researchers including Nicolas Biri and Daniel Mery.

• Computer Science
• Proof Theory
• Automated Deduction
• +2 more

Filippo Gandino is an Associate Professor at Politecnico di Torino, affiliated with the Department of Automatic Control and Computer Science (DAUIN) and the Interdepartmental Centre PIC4SeR for Service Robotics. He is a member of the College of Biomedical Engineering and the College of Computer, Cinema and Mechatronics Engineering. His research focuses on Internet of Things (IoT), Quantum Computing, and Wireless Sensor Networks (WSN), with a particular emphasis on pervasive computing and healthcare applications. He has been recognized with the Best Paper Award from the 6th International Conference of Broadband and Wireless Computing, Communication and Applications (BWCCA-2011). Professor Gandino teaches courses in Algorithms and Object-Oriented Programming, Computer Science, and Electronic Calculators across multiple engineering programs, including Aerospace, Cinema, and Computer Engineering. His academic contributions include supervising PhD student Pietro Chiavassa, whose thesis addresses security and reliability in pervasive computing. His work spans interdisciplinary projects, such as IoT-based environmental monitoring systems and quantum computing optimization algorithms. His research explores cutting-edge areas like secure intermittent computing, particulate matter measurement techniques, and quantum PCI planning. He actively contributes to IEEE conferences and journals, focusing on sensor networks, cybersecurity, and distributed systems. His lab, CAD - Electronic CAD & Reliability Group (DAUIN), drives innovations in electronic design and reliability engineering.

• Internet of Things (IoT)
• Quantum Computing
• Wireless Sensor Networks (WSN)
• +4 more

Mauro Bonafini is a Temporary Assistant Professor at the Department of Engineering for Innovation Medicine, University of Verona. His research focuses on geometric variational problems, optimal transport theory, and hyperbolic partial differential equations. Current academic rank: Assistant Professor (Mathematical Analysis) University: University of Verona Research groups: Analysis of PDE and Calculus of Variations His research projects include: Geometric Measure Theoretical approaches to Optimal Networks (since 2018) Geometric evolution of curves, surfaces and networks (since 2017) Stochastic Partial Differential Equations and Stochastic Optimal Control with Applications to Mathematical Finance (since 2016) Teaching activities: Mathematical analysis (6 credits, 2025/2026) Optimization (6 credits, 2025/2026) Mathematical Analysis II (12 credits, 2024/2025) Previous courses in Mathematical Analysis I and II across multiple academic years Email: mauro.bonafini@univr.it

• Mathematical Analysis
• Optimal Control Theory
• Calculus of Variations
• +4 more

Matteo Cristani is an Associate Professor at the University of Verona 's Department of Computer Science , where he teaches courses in Artificial Intelligence , Semantic Web , and Programming across multiple degree programs including Bioinformatics, Computer Science, and Artificial Intelligence. His research focuses on Knowledge Representation , NLP , and Formal Security Analysis , with applications spanning from blockchain technology to geospatial systems. Research Focus Intelligent agents and multi-agent systems Distributed artificial intelligence Formal methods in security theory Network security and cybersecurity NLP and large language models Ontology engineering Projects Active in third-mission activities, Cristani leads projects such as SHIELD (Securing Decentralized Finance and Healthcare Systems), SLOTS (Smart Legal Order in Digital Society), and NOMEN (Next-Gen Cyber Ranges). He has participated in 30+ research initiatives since 2001, including PRIN grants and industrial collaborations in semantic web applications.

• Artificial Intelligence
• Cybersecurity
• Formal Methods
• +4 more

Rosalba Giugno is a Full Professor of Informatics at the University of Verona's Department of Computer Science. She serves as Principal Investigator of the InfOmics Laboratory and is the reference person for the Master in Medical Bioinformatics program. Previously, from 2017 to 2022, she directed the Infolife laboratory, which comprised 35 research groups from various Italian universities. Her research focuses on algorithmic bioinformatics and computational biology, specifically developing graph algorithms for biological networks, integrating and analyzing biomolecular data, and modeling biological systems for personalized medicine. She leads a research group consisting of 5 PhD students and multiple master's thesis students. Her work bridges theoretical computer science with practical biomedical applications, utilizing approaches from machine learning, data science, mathematics, and graph theory. Professor Giugno has authored 130 scientific publications, with 70 appearing in international journals. Her recent work shows a strong trend toward applying advanced computational methods to solve complex problems in personalized medicine, particularly in patient stratification using multi-omics data, drug repurposing, and combination therapy prediction. She has secured funding for numerous national and European research projects, with recent initiatives focusing on multi-drug resistance in rheumatoid arthritis and personalized prostate cancer evaluation. She serves as an editor for the journal Information Systems and participates in scientific committees for international conferences and schools. Her leadership extends to university governance through roles on the Computer Science Teaching Committee and Department Council. Professor Giugno teaches courses in the Master's program in Medical Bioinformatics and the PhD program in Computer Science, including 'Analisi di dati Multi-omics da single-cell' and 'Programming for bioinformatics.' She has consistently taught these courses from 2016 through 2025, demonstrating commitment to training the next generation of bioinformatics specialists. The InfOmics Laboratory under her direction develops computational methods for biomedical data analysis, with applications spanning genomics, patient classification, and therapeutic optimization. The lab maintains strong connections with both academic and industrial partners through collaborative research projects.

• Bioinformatics
• Computational Biology
• Graph Algorithms for Biological Networks
• +7 more

Paola Cappanera is an Associate Professor of Operations Research at the Department of Information Engineering (Università di Firenze), affiliated with the School of Engineering. She is a member of the IBIS Lab. Her expertise spans combinatorial optimization, healthcare logistics, telecommunication networks, and scheduling problems. She teaches courses such as Fondamenti di Ricerca Operativa , Combinatorial Optimization , and Ottimizzazione su Reti di Flusso at both undergraduate and graduate levels. Her research focuses on optimizing healthcare delivery systems, including home care services, surgical scheduling, and resource allocation. She also addresses challenges in telecommunication networks, such as latency-aware scheduling and routing. Recent work emphasizes robustness in home care planning, equitable resource distribution, and mitigating risks in hazardous material transportation. Her articles highlight advancements in decomposition methods for scheduling, genetic algorithms for network functions, and integration of healthcare service models. Key contributions include models for emergency department physician rostering and optimizing tele-assistance systems.

• Operations Research
• Combinatorial Optimization
• Healthcare Logistics
• +3 more

Antonino Nocera is an Associate Professor at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering, within the Faculty of Engineering. He specializes in Data Science, Social Network Analysis, Privacy, Security, and Artificial Intelligence. He holds a PhD in Information Engineering from the University Mediterranea of Reggio Calabria (2013). His research focuses on cybersecurity, machine learning applications, and privacy-preserving technologies, with over 85 publications. He is an Associate Editor for *Information Sciences* (Elsevier) and *IEEE Transactions on Information Forensics and Security*. He leads the Digital Content Analysis Lab (DCALab) and collaborates with Microsoft on cloud computing initiatives. Recent projects include a 2020 Hackathon on analyzing the spread of the SARS-CoV-2 virus and a Microsoft Learn mini-course on Azure. His work spans federated learning security, malware detection, and IoT trust models. He actively participates in conference TPCs and promotes ethical AI practices. Key contributions include frameworks like SECTIS for CTI sharing and DROIDTTP for Android application analysis. His teaching emphasizes data science and big data analytics, integrating industry tools like Azure into curricula.

• Data Science
• Social Network Analysis
• Privacy
• +5 more

Jonathan Franceschi serves as a Visiting Professor in the Department of Mathematics at the University of Pavia, maintaining an office in room C11. His academic profile is anchored in the Mathematical Physics research group, with active contributions to interdisciplinary mathematical modeling. His research spans Mathematical Physics, Network Theory, Kinetic Theory, and Fractional Calculus, with pronounced applications in social dynamics and public health. Key focus areas include epidemic modeling, opinion polarization mechanisms, and fake news diffusion—particularly examining Italian vaccination hesitancy during the Covid-19 pandemic. His methodological toolkit integrates kinetic equations, graph theory, and optimal control frameworks for complex networked systems. Analysis of his 15 publications (2019–2025) reveals a cohesive trajectory: early work established foundations in fractional calculus and numerical methods, while recent research pivots toward data-driven social modeling. Dominant themes include consensus optimization with condensation phenomena, graphon-based opinion dynamics, and uncertainty quantification in epidemic control—all demonstrating rigorous mathematical formalism applied to real-world sociotechnical challenges. Franceschi actively supports academic community initiatives including Five o'clock TeX (offering LaTeX courses via Zoom), The break bridge (curating educational handouts), and the CompMat poster template project. His digital scholarship footprint is visible through arXiv, ResearchGate, ORCID, and Google Scholar profiles.

• Mathematical Physics
• Network Theory
• Kinetic Theory
• +4 more