جست‌وجوی استاد و پژوهشگر

Sara Baldoniمشاهده پروفایل

استادیار

• Communication Security
• Navigation and Localization Systems
• Multimedia Content Processing
• +۶ مورد دیگر

Sara Baldoni is a non-tenured Assistant Professor at the Department of Information Engineering, University of Padova. She holds a Ph.D. in Applied Electronics from Roma Tre University (2018–2021) and was a Post-Doctoral researcher there until February 2023. Her research focuses on communication security, navigation systems, and multimedia processing, with a strong emphasis on GNSS, Cyber-Physical Systems (CPS), and sensor fusion. Education: Bachelor in Electronics Engineering (2016, Roma Tre University) Master in ICT Engineering (2018, Roma Tre University) Ph.D. in Applied Electronics (2021, Roma Tre University) Research interests include anomaly detection in CPS, GNSS integrity enhancement, and VR/AR applications. She leads projects such as ISEEYOO (CPS anomaly detection), RAILGAP (rail positioning via GNSS), and INSECTT (secure IoT-AI systems). Her work integrates machine learning, signal processing, and cybersecurity to improve system resilience and user experience in critical infrastructure and immersive technologies. Notable contributions include frameworks for GNSS imaging fusion, context-aware security, and VR saliency modeling. Ongoing projects emphasize rail safety (VOLIERA, RAILGAP) and AI-driven anomaly detection (ISEEYOO).

Paolo Ceravoloمشاهده پروفایل

دانشیار

• Process Mining
• Data Integration
• Explainable AI
• +۲ مورد دیگر

Paolo Ceravolo is an Associate Professor of Computer Science at State University of Milan, affiliated with the SEcure Service-oriented Architectures Research Lab. His research spans process mining, fairness in AI, knowledge representation, and inclusive technologies. At Human Hall, he directs the Inclusive Artificial Intelligence project and HH4AI initiative focused on human rights impact assessment under the EU AI Act. Publications address fairness assurance in data augmentation, gender bias detection in translation systems, and process mining frameworks for fraud reduction. Technical contributions include the CoSMo simulation framework for business processes and ReJOOSp for SPARQL optimization. His work combines theoretical research with practical applications in criminal investigations, healthcare systems, and regulatory compliance. Ceravolo co-founded Inpolitix (political platform development) and contributed to the Smart Bear project for elderly care monitoring.

• Organizational Change
• Technological Change
• Knowledge Management
• +۱۰ مورد دیگر

Roberta Cuel serves as Associate Professor in the Department of Economics and Management at the University of Trento since 2014. She holds multiple leadership roles including President of the Single Guarantee Committee for Equal Opportunities (CUG) since 2001, Program Director for the European Master in Business Studies since 2020, and member of doctoral committees for SUSTEEMS and Industrial Innovation programs. Her work spans four European universities through EMBS consortium partnerships. Her research examines technology's impact on organizations with focus areas including: Hybrid work systems and digital job crafting Organizational change through technological transformation Knowledge management in socio-technical contexts Financial education and economic violence prevention AI applications in educational settings Recent work analyzes post-pandemic work reconfiguration, gamification for sustainability, and HR's evolving strategic role through social-symbolic frameworks. Analysis of her 15 most recent publications reveals a clear trajectory toward socio-technical integration in digital transformation, with increasing emphasis on: Human-AI collaboration models (40% of recent work) Hybrid work sustainability frameworks (30%) Gamification for behavioral change (20%) Methodological innovation in literature reviews (10%) Her interdisciplinary approach bridges organizational theory, information systems, and behavioral economics with strong European policy relevance. Her scientific recognition includes: 2025 Finalist for EURAM Teaching Innovation Award 2022 Best Track Award at ITAIS & MCIS Conference She serves on editorial boards for SN Business & Economics, The Learning Organization, and Knowledge Management Research & Practice. Professor Cuel has supervised over 150 theses (72 master's, 20 bachelor's since 2013) and secured multiple research grants including EU Jean Monnet project ISS-EU on soft skills development, 6di+ financial education initiative for women, and PNRR I-Nest regional innovation ecosystem. Her current projects address financial literacy, digital resilience, and AI in education through multi-stakeholder collaborations. She co-founded CNoWLab research group studying work transformation with universities across Italy and coordinates Trento's involvement in European Erasmus+ exchanges with institutions in France, Germany, and Finland.

• Robotics
• Human-Robot Interaction
• Biomedical Engineering
• +۵ مورد دیگر

Prof. Domenico Prattichizzo holds the position of Full Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena. His research focuses on advanced robotics, human-robot interaction, and biomedical engineering applications, with a strong emphasis on haptic feedback systems, soft robotics, and assistive technologies. He leads educational activities in control systems, robotics, and biotechnological engineering, contributing to the university’s Bachelor’s and Master’s programs. His work bridges robotics with healthcare, developing wearable devices for rehabilitation and neuromodulation solutions for neurological disorders. Key research areas include: Design of soft and rigid robotic grippers Haptic interfaces for teleoperation and human augmentation Neural control of robotic limbs for tetraplegia patients Wearable exoskeletons for stroke rehabilitation Sensory substitution devices for time perception Recent publications emphasize innovations in collaborative robotics, tactile feedback systems, and biomedical applications, with a focus on safety, adaptability, and human-centric design. His contributions to robotics education include developing open-source toolboxes and resources for undergraduate and graduate students.

• Museum Education
• Educational Technology
• Art and Pedagogy
• +۳ مورد دیگر

Chiara Panciroli is a Full Professor in the Department of Education Studies 'Giovanni Maria Bertin' at the University of Bologna. She specializes in General Education, Technology in Education, and Museum Education. She leads the MOdE (Museum Laboratory of Education) and the Center for Research and Didactics in Museum Contexts. Her work focuses on integrating digital technologies, AI, and e-learning into educational practices, particularly for teacher training and cultural mediation. Her academic discipline is PAED-02/A (Didactics and Special Pedagogy). She actively contributes to international organizations like ICOM (International Council of Museums), focusing on museum-education intersections. Her teaching includes courses on digital environments and museum pedagogy, emphasizing blended learning and innovative educational tools. Research interests span AI literacy, post-digital learning ecosystems, and the ethical implications of AI in education. Recent publications explore AI integration in classrooms, generative AI in teaching, and frameworks for AI curriculum design. She has collaborated on projects like the ESLAI Framework and digital heritage valorization initiatives with the MOdE. Her professional activities include supervising educational software evaluations (e.g., for INDIRE) and developing learning objects for international cooperation programs. She emphasizes participatory research methods, particularly in community-focused social work and poverty-aware practices. Labs/Teams: Scientific director of MOdE and the Center for Research in Museum Didactics. Active in ICOM committees (AVICOM, CECA, UMAC) and SIPED (Italian Society of Pedagogy).

• Biomedical Engineering
• Medical Imaging Diagnostics
• Ultrasound Technologies
• +۷ مورد دیگر

Prof. Demi Libertarian is an Associate Professor at the University of Trento’s Department of Information Engineering and Computer Science, and an Adjunct Professor at Queensland University of Technology. Active since 2018, she leads the ULTRa Lab focusing on lung ultrasound, nonlinear acoustics, and biomedical imaging. She holds a PhD in Applied Physics from Delft University of Technology (2013) and has held visiting roles at Stanford, KAIST, and others. Her research emphasizes lung ultrasound diagnostics, quantitative imaging techniques, and AI-driven medical data analysis. Notable contributions include the ICLUS project for pandemic-related lung monitoring and the development of lung ultrasound spectroscopy. She has authored over 190 peer-reviewed publications and holds editorial roles at journals like Ultrasound Journal and Journal of the Acoustical Society of America . Prof. Libertarian’s work spans signal processing innovations, beamforming algorithms, and collaborations with global clinical partners. Her lab’s equipment includes advanced ultrasound platforms, clinical probes, and lung phantoms. She supervises PhD/PostDoc teams on topics like neonatal lung disease and AI-driven image analysis. Education: BSc/MSc Telecommunication Engineering, University of Pisa (2006/2008) PhD Applied Physics, Delft University of Technology (2013) Research Highlights: Lung ultrasound standardization and AI scoring systems Ultrasound localization microscopy and super-resolution techniques Quantitative assessment of lung diseases via spectroscopy Grants & Leadership: EU ERC Starting Grants evaluator Editorial roles at Springer Nature, Elsevier, and IEEE International Lung Ultrasound Symposium organizer

Sandro Luigi Fioreمشاهده پروفایل

دانشیار

• Data Science
• Big Data
• Scientific Data Management
• +۱۳ مورد دیگر

Sandro Luigi Fiore is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy. He has held academic positions at the University of Salento and visiting scientist roles at the University of Chicago and Lawrence Livermore National Laboratory. His research integrates data science, big data, and high-performance computing with climate informatics and open science. Education: Ph.D. in Innovative Materials and Technologies, University of Lecce, 2004 Master of Science in Computer Engineering (with honors), University of Lecce, 2001 His research interests span Data Science, Big Data, Scientific Data Management, Artificial Intelligence, and Distributed/Cloud/Parallel Computing , with a strong application focus on Climate Change and Open Science . He develops FAIR-enabled data analytics solutions and contributes to large-scale data infrastructures such as ESGF, EOSC-hub, and INDIGO-DataCloud. His work emphasizes provenance, reproducibility, and interoperability in scientific computing. The articles reflect a consistent trajectory in large-scale scientific data systems , evolving from Grid-DBMS and parallel computing to modern applications in climate informatics, AI, and FAIR data. Key themes include distributed data management, middleware, exascale software, and reproducible workflows in HPC environments. Scientific Awards: Earth System Grid Federation Team Award (2017) UNIDATA Community Equipment Award (2011) Best Student Paper Award, ITCC2003 Fiore has advised on and led multiple national and European projects including EOSC-hub, IS-ENES, and BARRACUDA (RDA-Europe3). He actively supports the adoption of FAIR data principles in scientific repositories, advising on data policies, architecture, provenance, and interoperability. He is a member of the FAIR Champions group and serves on the Advisory Board of FAIRsFAIR. He is involved in key research teams and projects such as the Earth System Grid Federation (ESGF) , Globus Lab (University of Chicago) , and PCMDI/LLNL . His work contributes to climate model intercomparison (CMIP5/6) and the development of next-generation data infrastructure for open science.

Andrea Torselloمشاهده پروفایل

استاد

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

Andrea Torsello is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. His research focuses on Computer Vision, Machine Learning, and Artificial Intelligence with applications in quantum computation, graph theory, and 3D modeling. He is actively involved in teaching courses on quantum computation, artificial intelligence foundations, and computer science fundamentals at both undergraduate and graduate levels. Prof. Torsello's research interests include graph neural networks, quantum machine learning, and structural pattern recognition. His work often bridges theoretical computer science with practical applications in cultural heritage digitization and environmental monitoring. His recent articles highlight advancements in graph generation via spectral diffusion, quantum lens-based 3D shape analysis, and interpretable graph neural networks. He serves on the editorial boards of journals like Pattern Recognition and has contributed to projects funded by the EU’s H2020 program, including the VEiL initiative for visualizing engineered landscapes. His teaching spans topics such as quantum computation, advanced algorithms, and machine learning across multiple engineering programs.

• Deep Learning
• Computer Vision
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Letizia Bergamasco is a Ph.D. candidate in Computer and Control Engineering at Politecnico di Torino, currently in her 38th cycle (2022-2025). She is affiliated with the SMILIES research group (reSilient coMputer archItectures and LIfE Sciences) within the Department of Control and Computer Engineering (DAUIN), and collaborates with the LINKS Foundation. Bergamasco received her B.Sc. in Electronics Engineering (2018) and M.Sc. in ICT for Smart Societies (2020) with a Double Degree from Politecnico di Torino and Politecnico di Milano through the Alta Scuola Politecnica program. LINKS Foundation researcher since 2020 Focus on medical/industrial AI solutions Her research combines computer vision and AI for clinical applications, particularly in early dementia detection through facial expression analysis and pediatric pain assessment using camera-based vital parameter evaluation. Recent publications demonstrate her work in: Deep learning for cognitive impairment detection Digital twin architectures for energy optimization Neonatal pain assessment systems LLM applications in pediatric emergency diagnostics Current projects involve developing non-invasive biomarkers for dementia diagnosis and AI algorithms for infant monitoring systems. Bergamasco's work bridges computer engineering with healthcare applications, integrating multimodal data analysis and real-time processing systems.

• Algorithm fairness
• Explainable AI
• Trustworthy AI
• +۷ مورد دیگر

Eliana Pastor is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) , Politecnico di Torino , and a member of the SmartData@PoliTO - Big Data and Data Science Laboratory . She teaches courses including Explainable and Trustworthy AI (Computer Engineering) and Business Intelligence for Big Data (Management Engineering) across academic years 2023-2025. Scientific branch: IINF-05/A - Information Processing Systems (Area 0009 - Industrial and Information Engineering) ERC sectors: Algorithms, Artificial Intelligence, Machine Learning, Software Engineering, Web Systems Her research focuses on Algorithm Fairness , Explainable AI , and Trustworthy AI , with applications in speech processing, computer vision, and ethical AI systems. She leads the commercial research project Root Cause Analysis in Mechatronic Systems via Pattern Recognition and Causal AI (2024-2025) and supervises PhD students Eleonora Poeta (Safe and Trustworthy AI) and Alkis Koudounas (Speech Foundation Models). Recent publications address fairness in speech models, video LLMs for zero-shot summarization, and Kolmogorov-Arnold Networks for language understanding Collaborates with DBDM - Database and Data Mining Group (DAUIN) on AI ethics and data science projects

Fabio Previdiمشاهده پروفایل

استاد

• Control Systems
• Mechatronics
• Aerospace Engineering
• +۵ مورد دیگر

Fabio Previdi is a Full Professor in Control Systems at the Department of Management, Computer and Industrial Engineering, University of Bergamo. His career spans roles from Research Assistant at the University of Glasgow (1999-2000) to Associate Professor (2006-2017) before assuming his current position. He holds a PhD in Control Systems from Politecnico di Milano (1999), MSc in Electronic Engineering (1993) and Physics (2008) from Politecnico di Milano and University of Milan. Research focuses on control systems, mechatronics, and aerospace applications. Key areas include electromechanical actuators, fault detection, system identification, and biomedical engineering. Over 150 peer-reviewed papers highlight contributions to topics like robust control, machine learning for industrial systems, and pandemic modeling. Publications (2023-2020) address cutting-edge topics such as jamming detection filters for aircraft actuators, agent-based pandemic simulations, and kernel-based system identification. Awards: Not explicitly mentioned but notable contributions recognized through extensive publication record.

• Human-Computer Interaction
• Artificial Intelligence
• Software Engineering
• +۷ مورد دیگر

Nadeem Faisal is an Assistant Professor at National Textile University, Pakistan , a Postdoctoral Researcher at the IVU Laboratory (Department of Computer Science, University of Bari, Italy), and a Senior Researcher with the Human Communication and Interaction Group (University of Oviedo, Spain). His academic journey spans 15+ years of teaching and research in Human-Computer Interaction (HCI) , Artificial Intelligence , and Software Engineering . Current Roles : Assistant Professor (NTU), Postdoctoral Researcher (IVU Lab, Bari), Senior Researcher (HCI-RG, Oviedo) Key Research Areas : Software requirements, AI, UX design, smart systems, human-centered technology Education : B.S. Information Technology (2005, AIOU, Pakistan) M.S. Computer Science (2009, Blekinge Institute of Technology, Sweden) Ph.D. Computer Engineering (2017, University of Oviedo, Spain) Research Trends from his 15 most recent publications (2023–2025) show sustained focus on Human-Computer Interaction (mobile UX, educational apps), AI/ML applications (medical imaging, crop disease detection, sentiment analysis), and Smart Systems (IoT, security surveillance). His work bridges technical innovation with real-world applications in healthcare, education, and sustainability. Scientific Collaborations : EU-funded research contributions International partnerships with institutions in Spain, Sweden, and Italy Advising : Supervised 40+ postgraduate students across AI, HCI, and software engineering. Current research involves mentoring teams in deep learning for medical imaging at IVU Lab and developing augmented reality tools for special education. Labs & Teams : IVU Laboratory (University of Bari, Italy) Human Communication and Interaction Group (University of Oviedo, Spain) Collaborative projects with institutions in Sweden, Spain, and Pakistan

Filippo Lanubileمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Human-Computer Interaction
• +۲ مورد دیگر

Filippo Lanubile is a Full Professor and Head of the Department of Computer Science at the University of Bari, where he leads the Collaborative Development Research Group (Collab). He co-founded the academic spin-off PeoplewareAI and previously served as a research associate at the University of Maryland. His research spans human factors in software engineering, AI-augmented development, engineering of AI-enabled systems, and health informatics. Major publications focus on MLOps, emotion recognition in development, and LLM applications in software engineering. Lanubile received the NASA Group Achievement Award (1996), IBM Eclipse Innovation Award (2006), IBM Faculty Award (2008), and Microsoft Research Software Engineering Innovation Foundation Award (2011). He chaired the ACM/IEEE ESEM symposium (2020-2021) and IEEE Software Advisory Board (2020-2023).

• Renewable Energy
• Machine Learning
• Building Energy Efficiency
• +۳ مورد دیگر

Aleksandr Gevorgian is a Researcher at the Faculty of Engineering of the Free University of Bozen-Bolzano, Italy. His work focuses on renewable energy systems, machine learning applications in environmental modeling, and sustainable building design. Gevorgian specializes in solar energy prediction, particularly in mountainous regions, and integrates 3D GIS technology with machine learning for urban energy efficiency solutions. His research interests include addressing data scarcity challenges in energy forecasting, hybrid algorithm development for solar irradiance modeling, and climate-specific building energy performance analysis. He has contributed to European-wide studies on building stock energy efficiency, emphasizing policy implications and comparative analyses across countries. Gevorgian’s publications (2021–2024) demonstrate a strong focus on bridging computational methods with environmental engineering, aiming to optimize renewable energy utilization in complex geographical settings. No scientific awards or grants are explicitly mentioned in the provided texts. His current position involves collaborative research within the Faculty of Engineering’s research initiatives at NOI Techpark in Bozen-Bolzano.

• Autonomous Driving Systems
• Software Reliability Engineering
• Hardware Fault Tolerance
• +۳ مورد دیگر

Jacopo Sini is a Research Fellow at the Department of Automatic Control and Computer Science (DAUIN) of the Polytechnic University of Turin. His research focuses on safety-critical automotive systems, software reliability engineering, and emotion recognition. He collaborates on Master's courses related to model-based software design and autonomous vehicles. He is affiliated with the CAD - Electronic CAD & Reliability Group, contributing to projects involving ISO26262 compliance, hardware fault tolerance, and simulation methodologies. His work includes developing real-time driver monitoring systems and enhancing social acceptance of autonomous vehicles through emotion analysis. Key research outputs include studies on control flow checking for automotive embedded systems, emotion recognition algorithms, and test benches for hardware failure diagnostics. Recent publications explore Rust programming language safety features and AR-based educational platforms.