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Luca TeseiView profile

Associate Professor

• Computational Structural Bioinformatics
• RNA Secondary Structure Analysis
• Topological Data Analysis
• +5 more

Luca Tesei is an Associate Professor in the Department of Computer Science at the University of Camerino's School of Science and Technology, Italy. His research focuses on computational structural bioinformatics, particularly RNA secondary structures and their functional implications. Current Projects: Principal Investigator of PRIN 2022 PNRR Project RNA2Fun (RNA Secondary Structures & Function in non-coding RNAs) Editorial Roles: Guest Editor for BMC Bioinformatics' RNA Prediction Collection; Editorial Board Member of BMC Bioinformatics Luca's work integrates topological data analysis with biological systems modeling, spanning RNA structure alignment, pseudoknot detection, and machine learning applications in biomedical fields. He has received the Italian National Scientific Qualification as Associate Professor in INF/01 (Computer Science) and ING-INF/05 (Information Systems Engineering) in 2017. Recent Trends: His publications emphasize RNA computational modeling (2016-2025), with growing integration of topological methods (persistent homology, entropy analysis) and machine learning techniques for structural comparisons and biomedical applications like seizure detection and stock market modeling. Scientific Awards: Italian National Scientific Qualification as Associate Professor (2017)

Fabrizio FornariView profile

Assistant Professor

• Internet of Things (IoT)
• Digital Twins
• Business Process Management (BPMN)
• +6 more

Fabrizio Fornari is an Assistant Professor in Computer Science at the University of Camerino (Italy), focusing on cutting-edge technologies like Internet of Things (IoT), Digital Twins, and Business Process Management (BPMN). His work bridges theoretical modeling with practical implementations, emphasizing formal verification and modern software development practices. Research Pillars: IoT programming paradigms (Fluidware, FloWare), Digital Twin applications for business processes, and formal BPMN verification. Technical Contributions: Development of model-driven frameworks (X-IoT, FloBP), 3D simulation tools for IoT platforms, and BPMN analysis utilities (BPMN Inspector, BProVe). Domain Applications: Earthquake response systems (SAFE), intelligent transportation data flows, and educational IoT test environments. Methodological Focus: Community detection algorithms for routine extraction, CI/CD optimization for databases, and systematic literature reviews on IoT-aware BPMN modeling. Collaborative Efforts: Active involvement in MIDas4CS workshops and repository platforms for process model sharing (RePROSitory).

• Electrical Engineering
• Electromagnetic Compatibility
• Machine Learning Applications in IC Modeling
• +3 more

Tommaso Bradde is a Fixed-term Researcher (Law 240/10 art.24-a) in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino. His academic affiliation includes membership in the College of Electronic, Telecommunications and Physics Engineering. Dr. Bradde teaches courses across multiple degree programs, including Electromagnetism and Circuit Theory (2025/26, Computer Engineering), Electrical Engineering (2023/24, Electronic Engineering), and Convex Optimization and Engineering Applications (2021/22–2019/20, Mechatronic Engineering). Research Interests Dr. Bradde's work focuses on Electromagnetic Compatibility (EMC) Model Order Reduction techniques Machine Learning applications in IC modeling Convex Optimization for engineering systems Data-driven modeling of electrical components Stability-preserving numerical algorithms Recent Publications His research output spans 2025 and 2024, covering bias-dependent powder core permeability, modified AAA algorithms for stable reduced-order models, and machine learning-based modeling of IC buffers and switched systems. These works intersect Electrical Engineering, Machine Learning, and Scientific Computing. Academic Activities He contributes to doctoral-level instruction through the Introduction to Model Order Reduction course (2024/25, Electrical/Electronics/Communications Engineering) and holds teaching responsibilities in Master's and undergraduate programs.

• Signal Processing
• Atomic Timing
• Global Navigation Satellite Systems
• +3 more

Lorenzo Galleani serves as Associate Professor at the Department of Electronics and Telecommunications within the College of Electronic, Telecommunications and Physics Engineering at Polytechnic University of Turin. His academic appointment falls under Scientific Disciplinary Sector IINF-03/A (Telecommunications) in Area 0009 (Industrial and Information Engineering). His research focuses on signal processing for atomic timing in global navigation satellite systems and nonstationary signal processing , with significant contributions to optical time scale development and atomic clock anomaly detection. As principal investigator of the Navigation, Signal Analysis and Simulation (NavSAS) Group, he bridges theoretical signal processing with practical timekeeping applications. Recent publications demonstrate a clear trajectory toward optical clock integration and robust timescale algorithms , particularly through EU-funded projects like ROCIT. His work shows increasing emphasis on sub-nanosecond precision timekeeping for next-generation satellite navigation systems. Galleani has supervised doctoral students in Metrology across ten consecutive academic cycles (2014/15-2022/23) and teaches core courses including Signal Processing: Methods and Algorithms for Communications Engineering. His extensive grant portfolio includes EU Horizon 2020 projects, national PRIN grants, and commercial contracts with space agencies focused on Galileo system support. He leads the Navigation, Signal Analysis and Simulation (NavSAS) research group, which develops signal processing techniques for satellite navigation timing systems. Current projects focus on optical clock integration for international timescales and robust time reference architectures for European GNSS services.

• Biomedical Informatics
• Clinical Process Modeling
• Healthcare
• +9 more

Gabriella Balestra is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Electronics and Telecommunications (DET) and serving as Coordinator of the College of Biomedical Engineering . She leads research in biomedical signal processing, telemedicine, and AI-driven medical software design, with a focus on cardiac monitoring and radiomics. Scientific Collaborator, Polytechnic University of Turin & University of Turin (2023-2027) Member, GEDI Observatory for Gender Equality and Inclusion Research Interests span biomedical informatics, clinical process modeling, and machine learning for healthcare. Her work includes developing digital twins for heart failure patients and AI tools for cancer segmentation and telemedicine applications. Recent publications highlight AI integration in radiomics , phonocardiography , and multi-center clinical studies, with a focus on wearable sensors and medical device software. Supervisor: Silvia Cannone (Digital Twin for LVAD Patients), Gregorio Dotti (Telerehabilitation), Jovana Panic (MRI-based AI for Oncology) She leads the Biolab: Biomedical Engineering Group and contributes to national and EU-funded projects like RECHARGE and ASSOCIATE .

• Additive Manufacturing
• Mechanical Design
• Smart Structures
• +12 more

Giorgio De Pasquale is an Associate Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) of Politecnico di Torino, where he heads the Smart Structures and Systems (S3) Laboratory. He serves on the Interdepartmental Center J-Tech@PoliTO and holds a national habilitation for Full Professorship (2018). His research spans additive manufacturing, smart structures, energy harvesting, and wearable systems. Additive Manufacturing: Design for AM, multi-material joints, lattice structures Smart Systems: Native sensors in metals, structural monitoring Human-Machine Interface: Wearable bio-mechanical sensors, GoldFinger glove MEMS: Dynamic response, fatigue modeling Recent projects include MIMOSA (multimaterial aircraft components) and STARDUST (wearable rehabilitation devices). He has received awards from ASME, MESAP, and Accademia del Premio Sapio. Teaching roles include PhD courses on lattice structure modeling and MSc/BSc lectures on structural mechanics. Over 60 students have been supervised in his lab.

Michele RutaView profile

Professor

• Pervasive Computing
• Ubiquitous Web
• Knowledge Representation Systems
• +7 more

Michele Ruta serves as Full Professor in the Department of Electrical and Information Engineering at Polytechnic University of Bari, specializing in pervasive computing systems and semantic technologies. His academic journey began with a Master's in Electronics Engineering from the same institution in 2002, followed by a Ph.D. in Computer Science in 2007. His research spans pervasive computing, ubiquitous web systems, knowledge representation, and wireless ad-hoc networks, with recent focus on blockchain integration for IoT, cloud-edge intelligence, and semantic web applications. Key contributions include the COWL ontology framework and Tiny-ME reasoning engine for resource-constrained devices. Analysis of his 15 most recent publications reveals strong emphasis on semantic technologies for smart mobility (2025), AI-driven logistics optimization (2025), and edge-based reasoning systems (2024). His work consistently bridges theoretical knowledge representation with practical applications in smart cities, healthcare, and industrial IoT. As editorial board member for relevant journals and Program Committee participant in international conferences, he actively shapes research directions in his fields. His technical leadership extends to national and international research projects focusing on semantic web infrastructure and IoT integration. Professor Ruta maintains active contributions through his personal research platform and IRIS publication repository, with 178 publications demonstrating sustained scholarly output since 2007. His laboratory work focuses on practical implementations of semantic reasoning for cyber-physical systems, particularly in cloud-edge continuum architectures.

• Computer Science
• Distributed Systems
• Peer-to-Peer Networks
• +2 more

Vittorio SCARANO is a Full Professor at the University of Salerno, affiliated with the Department of Computer Science. His office is located at Fisciano Campus, Building F, Fourth Floor, Room 001. Reception hours are held on Thursdays (9:00–11:00) and Fridays (11:00–12:00) via Microsoft Teams ( vitsca@unisa.it ). Additional appointments can be scheduled by email. His research focuses on Computer Science , with emphasis on: Distributed Systems and P2P Networks Collaborative Learning Environments Algorithm Design and Optimization Mobile and Adaptive Learning Technologies His publications demonstrate consistent work in networking, distributed computing, and educational tools, with recent expansions into mobile learning infrastructure. No scientific awards, grants, or student advising relationships are documented in the sources. He participates in international academic exchanges through Erasmus+ agreements for study and traineeship, though specific lab/team details are unavailable.

• Algorithms
• Optimization
• Mathematical Programming
• +2 more

Federico Della Croce Di Dojola is a Full Professor at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino. He is also a member of the Interdepartmental Center Ec-L - Energy Center Lab. His academic career spans over two decades with international collaborations including a Visiting Researcher position at Université Paris Dauphine (2004-2005). Research Interests focus on algorithm development and optimization techniques, particularly in combinatorial optimization. His work applies to diverse areas including operations research, production scheduling, and mathematical programming, with connections to sustainable cities and communities (SDG Goal 11). Publications demonstrate expertise in exact algorithms, heuristic methods, and scheduling problems across multiple domains. Key contributions include advancements in transportation optimization, bilevel scheduling, and fuel treatment planning. Scientific Recognition : Member of Editorial Board, European Journal of Operational Research (2016-) Member of Editorial Board, Computers & Operations Research (2016-) Principal investigator in multiple research projects Academic Leadership includes: Director of Department of Control and Computer Science (2012-2015) Doctoral College Member (2003-2025) Course Lecturer at multiple degree levels PhD Supervision includes Quentin Schau (2024-in progress) focusing on Industry 4.0 scheduling problems.

• Quality Engineering
• Statistical Process Control
• Innovative Production Systems
• +3 more

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.

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +4 more

Matteo Boffa serves as a Fixed-term Assistant Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He teaches courses including AI and Cybersecurity, Big Data for Internet Applications, and Databases across master's and bachelor's programs. His research spans cybersecurity, artificial intelligence, and data mining with emphasis on: Application of large language models for intrusion detection and malicious log analysis Social mining techniques for urban function identification Combinatorial optimization in network and security contexts Recent publications reveal a decisive shift toward leveraging language models for automated security analysis, with increasing focus on real-world deployment of AI-driven security tools since 2022. This trend bridges theoretical AI advancements with practical cybersecurity applications. Scientific Awards: No awards or fellowships were listed in available sources Teaching and Advising: Course collaborator for AI and Cybersecurity (Master's, 2024/25) Course collaborator for Big Data for Internet Applications (2022/23) Course collaborator for Interdisciplinary Projects (2022/23) Course collaborator for Databases (Bachelor's, 2024/25) Involved in doctoral supervision (2025 thesis: Language Models and Cybersecurity - Applications and Current Limits)

• Artificial Intelligence
• Computer Vision
• Domain Adaptation
• +6 more

Tatiana Tommasi is an Associate Professor at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin, actively contributing to advanced AI research and education. She serves as Deputy Coordinator of the National Doctoral College in Artificial Intelligence and Scientific Advisor for the European AI, Data, and Robotics Association (ADRA) and ELLIS Network. Her affiliations include the SmartData@PoliTO Laboratory and VANDAL Visual and Multimodal Applied Learning Laboratory. Her research focuses on algorithm fairness, computer vision, domain adaptation, autonomous driving, and robot learning. Recent work includes improving neural network reliability through fault-aware design, 3D semantic novelty detection, and visual relationship reasoning for robotic grasp planning. She has contributed to European research projects like ELSA (Secure and Safe AI) and commercial initiatives in space technologies and autonomous vehicle uncertainty quantification. Selected 2024-2025 publications demonstrate expertise in foundation models, fairness metrics, uncertainty estimation, and geometric deep learning. Her team leads commercial research projects on industrial robotics trajectory generation and satellite data analysis. She teaches core courses in Computer Engineering, Automotive Engineering, and Data Science, mentoring PhD students in Artificial Intelligence and Computer Systems Engineering. Research keywords: Artificial Intelligence, Machine Learning, Computer Vision, Domain Adaptation, Robot Learning, Transfer Learning, Fairness in AI, Uncertainty Quantification, Autonomous Driving, 3D Point Cloud Analysis, Vision Transformers, Industrial Robotics.

• Actuators
• Digital Twin
• Flight Control Systems
• +9 more

Massimo Sorli is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Polytechnic University of Turin. He serves as a Scientific Advisor for the partnership agreement with Leonardo SpA and is actively involved in the Power Electronics Innovation Center (PEIC) . His academic leadership includes membership in the Board/Steering Committee of the Piedmont Aerospace District (2019-present) and the Scientific Committee of Custer Tecnologico Nazionale Aerospazio CTNA (2013-present). Research Interests : Actuators and Servo Systems Digital Twin and PHM (Prognostics and Health Management) Flight Control Systems in Aerospace and Automotive Mechatronic Design and Analysis Transmission Systems and Harmonic Drives Recent Research Trends focus on condition-based maintenance for aerospace systems, digital twin integration in actuation systems, and AI/ML applications for aircraft diagnostics. His work spans computational modeling of harmonic drives, vibration mitigation in helicopters, and ergonomic industrial design. Teaching includes courses on Servosystems and System Health Management at the doctoral and master's levels since 2019. He has supervised numerous PhD students in mechanical engineering cycles, with recent theses on Compact Electromechanical Actuators , Inflatable Robots for On-Orbit Servicing , and Model-Based Robot Health-Management . Patents cover aerospace actuation systems, harmonic drive diagnostics, and coffee machine flow regulators. His industry collaborations with Collins Aerospace, Lufthansa Technik, and Leonardo SpA focus on hydraulic diagnostics, flight control actuator testing, and asbestos risk reduction.

• Artificial Intelligence
• Fault Detection and Diagnosis
• Metamodeling
• +8 more

Nicola Pedroni is an Associate Professor at the Department of Energy (DENERG) of Politecnico di Torino, Italy. His research focuses on advanced computational methods for nuclear safety, uncertainty quantification, and artificial intelligence applications in risk assessment. He has held external academic roles at institutions including MIT, École Centrale Paris, and CEA Saclay. Research Interests: Artificial Intelligence, Monte Carlo Methods, Nuclear Safety, Uncertainty Quantification, Probabilistic Risk Assessment, Resilience Analysis His recent work spans inverse uncertainty quantification, fault detection in safety-critical systems, and metamodeling techniques for nuclear reactor analysis. He serves on editorial boards for Frontiers in Nuclear Engineering , Energies , and Proceedings of the Institution of Mechanical Engineers, Part O . Pedroni leads the ARISTOTELES project on AI and stochastic simulation for critical infrastructure resilience and contributes to the EU-funded ENDURANCE project for molten salt reactor safety. He supervises PhD student George Afful and teaches courses in nuclear plant modeling and risk analysis.

• Smart Transportation
• Sustainable Mobility
• Environmental Impact Assessment
• +4 more

Cristina Pronello is a Full Professor at the Politecnico di Torino , affiliated with the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) and the SmartData@PoliTO - Big Data and Data Science Laboratory . Her career spans international collaborations at institutions like IFSTTAR, Université Lumière Lyon 2, and École des Ponts ParisTech. Research Interests Smart transportation Environmental impact assessment Data collection via IoT and smartphones Travel behavior analysis Intelligent Transport Systems (ITS) Pro-environmental behavior Notable Scientific Awards TRA VISIONS 2020 (European Commission, 2020) 2010 award from Université Paris Est Marie Curie fellowship (INRETS-LTE, 1994) Key Contributions Her research integrates big data analysis with sustainable mobility, focusing on behavioral theories and environmental impact mitigation. She leads EU-funded projects like FORTHCOMING and WE-TRANSFORM , while contributing to editorial boards of journals such as Sustainable Cities and Society . She has supervised numerous PhD students and designed courses on smart transportation, behavioral theories, and data applications in mobility.