Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services
Paolo Buono is Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. He holds a PhD in Computer Science with specialization in Visual Data Analysis. His research focuses on Information Visualization, Visual Analytics, Human-Computer Interaction, and Mobile Applications. Co-founder and CEO of LARE (2010), a university spinoff providing real-time surgical support through audio-video telestration Member (since 2002) and computer science coordinator at METEA Research Center for environmental protection Visiting scientist at AVIZ (France), University of Maryland (USA), and Fraunhofer IPSI (Germany) His work spans multiple application domains including: Cultural Heritage through interactive exploration systems Healthcare with smart therapeutic devices Environmental Monitoring via CET system IoT-based Smart Interactive Experiences He has contributed to: Dynamic hypergraph visualization techniques End-User Development frameworks (EUDroid) Usability evaluation methodologies Mobile health applications As project leader, he has coordinated: EU-funded VisMaster Coordination Action (2008-2010) Italian Ministry-funded LOGIN project (2014-2015) Apulia Region environmental projects His professional engagements include: Co-chair roles at INTERACT, AVI, IS-EUD conferences Program committee participation in VIS series and HCI conferences Member of ACM, IEEE, and SIGCHI Italy
Mauro Bonfanti is a Fixed-term Assistant Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Politecnico di Torino, Italy. His academic work focuses on wave energy conversion systems, mechatronics, and applied mechanics within the field of industrial and information engineering. Dr. Bonfanti's primary research interests include wave energy conversion systems, system identification, optimal control, mechatronics, and renewable energy systems. His work centers on developing advanced control strategies for wave energy converters, with particular emphasis on improving energy extraction efficiency through innovative mechanical designs and control algorithms. He has made significant contributions to the understanding of wave-structure interactions, hydrodynamic modeling of floating bodies, and optimization of wave energy converter systems under various sea conditions. His research bridges theoretical modeling with practical implementation, often involving high-fidelity numerical simulations validated through experimental testing. His publication record demonstrates a strong focus on advancing wave energy conversion technology, with particular emphasis on control systems, hydrodynamic modeling, and optimization techniques. The research shows progression from fundamental modeling approaches to increasingly sophisticated control strategies and system integration. Recent work has expanded to include hybrid renewable energy systems that combine wave and wind energy technologies. Dr. Bonfanti serves as a Scientific Responsible for several research projects including OCEANGLIDE, AQUALEV, and WISE, which focus on innovative wave energy conversion technologies. He holds multiple patents related to wave energy conversion systems, including the WISE (Water-air Injectable Swath Elevator) and AQUALEV magnetic support systems. He actively supervises PhD students including Alessandro Brusasco, Matteo Mastorakis, Francesco Balestrieri, and Domenico Edoardo Sfasciamuro, guiding research in sustainable materials, mechanical engineering, and wave energy conversion systems. His teaching responsibilities include courses on System Identification and Optimal Control of Wave Energy Conversion Systems, as well as Mechatronics across multiple academic years. Dr. Bonfanti is a member of the Mechatronics and Servosystems research group at DIMEAS, where he collaborates on projects related to marine renewable energy systems and advanced control technologies.
Prof. Mastroddi Franco is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMA) of Sapienza University of Rome, affiliated with the Faculty of Civil and Industrial Engineering. His expertise spans aerospace engineering, aeroelasticity, and multidisciplinary design optimization. He contributes to training programs such as the 2nd-level Master's in 'Satellites and Orbiting Platforms' and 'Energy Efficiency and Renewable Energy Sources'. His research focuses on fluid-structure interactions, sloshing dynamics in aircraft tanks, and sustainable aircraft design. He has led studies on green aviation technologies, launch vehicle aerodynamics, and numerical modeling techniques like Smoothed Particle Hydrodynamics (SPH). Research Interests: Aeroelastic Stability and Response Hydrogen-Powered Aircraft Systems Neural Network Applications in Fluid Dynamics Green Energy Integration in Aviation Reduced-Order Modeling for Complex Systems Publications highlight contributions to sloshing dynamics, hybrid aircraft design, and computational methods for hypersonic systems. Awards: None explicitly mentioned. Grants and advisory roles include participation in the 'Premio Liviu Librescu' thesis award committee (2010). He collaborates on projects involving structural damping models and multi-objective optimization for aerospace systems.
Salvatore Stuvard is an Associate Professor at the Department of Mathematics 'Federigo Enriques' of the University of Milan. He holds a Ph.D. from the University of Zurich (2017) and served as a Bing Instructor at the University of Texas at Austin (2017–2021). His research focuses on regularity theory for solutions in geometric analysis, particularly minimal surfaces, mean curvature flows, and geometric measure theory. He has organized seminars such as the Analysis Seminar at the University of Milan and co-organizes events like the 'Geometric Methods in Calculus of Variations.' His work bridges PDEs, geometric flows, and variational methods, addressing singularities and structural properties of geometric objects. Research interests include: Geometric Analysis and Geometric Flows Partial Differential Equations (PDEs) and Calculus of Variations Mean Curvature Flow (Brakke flows and multi-phase dynamics) Modulo p minimization and singular set structure Soap film/capillarity models and free-boundary problems Recent work emphasizes dynamical instability of minimal surfaces, end-time regularity of Brakke flows, and singular limits in capillarity problems. He co-organized the 2025 'Geometric Methods in Calculus of Variations' conference in Pisa.
Luca Collini is a Professor at the Department of Industrial Systems and Technologies Engineering (DISTI) at the University of Parma. He teaches courses across both Mechanical Engineering and Management Engineering programs, including MACHINE DESIGN AB (I MOD) (3rd year, A.Y. 2025/2026), Mechanics of Materials and Structural Integrity (2nd year, A.Y. 2024/2025), and Principles of Mechanical and Structural Design (1st year, A.Y. 2024/2025). Research Interests: His work focuses on mechanical design optimization, additive manufacturing, and simulation techniques. Key areas include pneumatic actuator design , FDM 3D printing parameters , and Design-to-Value (DtV) methodology . He collaborates on projects involving virtual design integration, structural integrity analysis, and sustainable manufacturing practices. Key Publications Trends: Recent articles emphasize hybrid design approaches combining analytical formulas and simulations, multi-objective optimization using machine learning, and DtV strategies for industrial applications. Collaborative research with Maiocchi, Nicoletto, and colleagues demonstrates interdisciplinary focus on mechanical systems and advanced manufacturing.
Prof. Fabio Galasso is a Full Professor in the Department of Computer Science at Sapienza University of Rome, where he heads the Perception and Intelligence Lab (PINLab). His research focuses on fundamental innovation in computer vision and machine learning, with particular emphasis on distributed intelligent systems, perception frameworks, and general intelligence within sustainable and interpretable AI contexts. His research interests span multiple domains of computer vision including video segmentation , motion forecasting , distributed intelligent systems , and shape reconstruction . Galasso's work emphasizes sustainable AI approaches that operate within constrained computational resources while maintaining interpretability and verifiability. His research bridges theoretical foundations with practical applications across retail, smart cities, and industrial settings. His recent publications demonstrate a clear progression toward increasingly complex human motion understanding and forecasting, with a strong emphasis on real-world applications. The research trajectory shows movement from foundational video segmentation techniques toward sophisticated motion prediction systems and anomaly detection frameworks that integrate multiple modalities. Key themes include temporal consistency, computational efficiency, and practical deployability in resource-constrained environments. His scientific achievements have been recognized with prestigious awards: 2019 IoT/WT Innovation World Cup 2019 Digital Champions Award 2018 Deutscher Digital Award Galasso has coordinated significant research initiatives including a Marie Sklodowska-Curie Actions project (Horizon 2020) and served as Principal Co-Investigator in multiple German-funded projects from the Ministry of Education and Ministry of Economics. His industry experience includes founding and directing OSRAM's Computer Vision Department in Munich, where he led R&D efforts connecting AI research with smart lighting applications, resulting in successful innovation transfers like the award-winning VISN product. He leads the Perception and Intelligence Lab (PINLab) at Sapienza University of Rome, fostering research that spans fundamental computer vision techniques to practical implementations in retail, smart cities, and industrial applications. The lab maintains strong connections with both academic institutions (including previous collaborations with University of Cambridge and Max Planck Institute) and industry partners.
Annarita De Maio serves as a Researcher in Operations Research (MAT/09) at the Department of Economics, Statistics and Finance (DESF) of the University of Calabria, where she teaches Logistics, Operations Research, and Mathematical Methods for Economics courses across undergraduate and graduate programs including Economics, Data Science, and Management Engineering. PhD in Mathematics and Computer Science (2018), University of Calabria Dissertation: Integrated Logistics and Last-Mile Deliveries (developed with Procter & Gamble) Research periods at P&G Brussels and CIRRELT/Laval University (Quebec) Her research centers on Logistics 4.0 innovations with dual emphasis on sustainable last-mile delivery systems (crowdshipping, autonomous robots, locker networks) and smart tourism applications . Current projects integrate IoT and AI for optimizing pharmaceutical distribution, perishable goods logistics, and urban tourist trip planning while addressing environmental constraints and stochastic demand patterns. Recent publications (2022-2025) reveal three thematic clusters: (1) stochastic optimization for dynamic delivery systems, (2) sustainable urban logistics solutions using multi-modal transport, and (3) data-driven tourism management frameworks. Her work consistently bridges theoretical modeling with industrial case studies involving Italian companies and municipal authorities. As an active member of DESF's Quantitative Methods for Economics, Finance and Management research group, she contributes to regionally and nationally funded projects focusing on mathematical programming applications. Her international conference participation includes speaking and organizing roles at major logistics and operations research events. Dr. De Maio collaborates within the department's research ecosystem through the Quantitative Methods group, which develops computational models for decision-making in finance, actuarial science, and transportation. Current initiatives explore crowdshipping economics, green tourist trip design, and risk-aware inventory systems for perishable commodities.
Filippo Masseni is a Fixed-term Tenure-Track Assistant Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) , Politecnico di Torino. His academic and research activities focus on aerospace propulsion systems, particularly hybrid rocket engines and solid propellant development. Scientific disciplinary sector: IIND-01/G - Aerospace Propulsion ERC sector: PE8_1 - Aerospace Engineering Research Interests include combustion instability modeling, coupled propulsion/trajectory optimization, multidisciplinary design optimization, and robust optimization techniques. His work bridges theoretical modeling with practical applications in hybrid rocket engines and advanced propulsion systems. In teaching , he serves as Course Lecturer for Combustion in Aerospace Engines and supervises courses like Aeronautical Propulsion and Aircraft Engines, spanning academic years 2019-2025. Supervised PhD Students : Vincenzo Madonia, Daniele Tozzi, Leonardo Stumpo, Alessandra Zumbo, Lorenzo Folcarelli, Giovanni Polizzi Research group: Aerospace Propulsion (DIMEAS)
Delibra Giovanni is an Associate Professor at Sapienza University of Rome, specializing in aerodynamics, aeroacoustics, and renewable energy systems. His research focuses on optimizing turbomachinery performance, including axial fans, wind turbines, and hydrogen storage systems. He employs advanced computational fluid dynamics (CFD) and machine learning techniques to address challenges in renewable energy integration, thermal management, and noise reduction. Key research areas include: Wind energy systems and offshore wind farm design Hydrogen storage and safety in green energy applications Aeroacoustic control in industrial fans and turbines CFD-based optimization of heat exchangers and cooling systems Recent work emphasizes the integration of photovoltaic and biomass systems in renewable energy communities, as well as experimental validation of wave energy turbines. His publications highlight innovations in fan blade design, leakage modeling, and multi-objective optimization frameworks for sustainable energy infrastructure. Collaborations involve both academic institutions and industry partners, focusing on real-world applications such as tunnel ventilation systems and Mediterranean island energy solutions. Giovanni's contributions bridge theoretical modeling with practical engineering challenges in the transition to clean energy.
Corrado Loglisci is an Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research focuses on Temporal Data Mining , Machine Learning , and Quantum Computing , with applications in bioinformatics, medical informatics, and cybersecurity. He earned his Ph.D. in Computer Science with a thesis on temporal projection in longitudinal data. Research Highlights : Temporal Learning, Textual Data Mining, Quantum-Classical Hybrid Systems Collaborations : IRSTEA Research Institute (France), Aristotle University of Thessaloniki (Greece) His publications address dynamic network analysis , emotion detection in social media , and quantum-enhanced classification . He contributes to program committees and journal editorial work, including a special issue on Mining Complex Patterns in the Journal of Intelligent Information Systems . Notable contributions include the jKarma framework for change detection and studies on concept drift robustness in intrusion detection systems. His work spans European/National research projects, leveraging machine learning for tasks like mobile crowd sensing trustworthiness prediction (2020) and investor behavior analysis (2023-2025).
Ruggero Carli is an Associate Professor at the Department of Information Engineering, University of Padova. His research focuses on control systems, robotics, and optimization, with emphasis on model-based reinforcement learning, distributed optimization algorithms, and energy systems. His work bridges theoretical advancements with real-world applications, including autonomous robotics, smart grids, and nonlinear control. Key contributions include physics-informed machine learning frameworks, ADMM-based distributed optimization methods, and MPC-driven control solutions for underactuated systems. Research interests include: Model-Based Reinforcement Learning for Robotics Nonlinear Model Predictive Control (NMPC) Distributed Optimization and ADMM Variants Energy Networks and Smart Grids Robot Dynamics and System Identification Recent publications emphasize: Continual learning for driver behavior analysis Physics-informed control for underactuated systems Robust optimization in unreliable networks Autonomous robotic manipulation with large language models His research integrates control theory with modern machine learning techniques, addressing challenges in edge computing, distributed systems, and real-time implementation.
Andrea Botta serves as a Fixed-term Assistant Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin. He is an invited member of both the College of Electrical and Energy Engineering and the College of Mechanical, Aerospace, and Automotive Engineering. His academic career spans teaching Mechanics of Automatic Machines across multiple degree programs including Mechanical Engineering and Energy Engineering since the 2020/21 academic year. Botta's research focuses on Applied Mechanics and Robotics, with particular expertise in articulated robots, mobile manipulators, precision agriculture systems, and rehabilitation robotics devices. His work bridges theoretical mechanics with practical applications in agricultural automation and assistive technologies, addressing challenges in mobility platforms, mechanism design, and human-robot interaction. His research directly contributes to multiple UN Sustainable Development Goals including Zero Hunger, Good Health, Clean Energy, and Climate Action. His publication record shows consistent output with significant contributions in 2023-2025, demonstrating expertise across both agricultural and medical robotics domains. Recent work reveals a strong trend toward practical implementations of robotic systems for greenhouse agriculture, rehabilitation assistance, and hospital service applications, with notable emphasis on control strategies, kinematic modeling, and user-centered design. Scientific Recognition: Best Paper Award of Jc-IFToMM International Symposium (2022) Botta actively supervises doctoral research, currently guiding Francesco Amodio in the 40th cycle of the Mechanical Engineering PhD program. He participates in competitive research projects including PAL-HAND (Pneumatic And Lightweight Handheld Device) and TWIN-IT-ROMANS (Twinning IZTECH in Robotics Manufacturing Systems), with funding from European Union initiatives including EIT and Horizon Europe Widening Participation programs. His work demonstrates strong interdisciplinary collaboration across mechanical engineering, control systems, and application-specific domains. As a member of the Automation and Robotics research group within DIMEAS, Botta contributes to developing innovative robotic solutions with practical implementations in precision agriculture through projects like AGRIMARO.Q and rehabilitation technology through wearable assistive devices like WELiBot.
Sandro Bartolini serves as Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, where he teaches advanced courses in computer architecture and parallel programming while leading cutting-edge research in high-performance computing systems. His academic journey began with a cum laude Laurea in Computer Engineering followed by a PhD in Computer Science and Engineering from Università di Pisa. Education: PhD in Computer Science and Engineering, Università di Pisa Laurea in Computer Engineering (cum laude), Università di Pisa Research Focus: His work centers on photonic interconnects for chip multiprocessors , energy-efficient software optimization for multi-core/GPU architectures, and performance-portable parallel programming models . Current investigations span cryptographic acceleration, blockchain algorithms, and hardware/software co-design for emerging computing paradigms, with strong emphasis on practical implementations bridging theoretical advances and real-world applications. Publication Trends: Recent publications (2019-2023) reveal three dominant threads: (1) Photonic network innovations addressing energy bottlenecks in chip multiprocessors, (2) The PHAST library ecosystem enabling seamless CPU/GPU programming across domains from autonomous vehicles to UAV navigation, and (3) Hardware accelerator designs for convolutional networks and cryptographic workloads. These works consistently target performance-portability challenges in heterogeneous computing environments. Grants and Collaborations: As principal investigator for the Italian Ministry-funded PHOTONICA project, he established international research partnerships with Murcia University, Columbia University, and Hong Kong University of Science and Technology, while securing industry collaborations with STMicroelectronics, Intel Munich, IBM, and IMEC. He has also managed complex IT system deployments for Siemens Italy, RAI (Italian public broadcasting), and SpaceDys. Academic Leadership: Bartolini serves as Associate Editor for the Eurasip Journal of Embedded Computing and actively contributes to the European HiPEAC network. His research group at Siena maintains strong industry ties for technology transfer, particularly in photonic interconnect validation and parallel programming frameworks for next-generation computing systems.
Luca Settineri is a Full Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin. He serves as Vicerector for Planning at the university since 2018 and acts as Advisor to the Rector for the University's building and infrastructure development plan. He is also a Member of the Interdepartmental Center J-Tech@PoliTO and Scientific Advisor of the European Association EFFRA and European Partnership EIT Manufacturing. His research focuses on Additive manufacturing (AM), Joining, Machining, Manufacturing technology, Sustainable manufacturing, and Cutting tools materials and coatings. Professor Settineri has published extensively on sustainable manufacturing approaches, with recent work emphasizing the integration of AI in manufacturing processes to enhance inclusivity and efficiency. His research output shows a clear progression toward human-centered manufacturing systems that accommodate cognitive diversity while maintaining production efficiency. His publications from 2023-2025 demonstrate a strong focus on AI-assisted assembly systems, sustainable additive manufacturing processes (particularly WAAM), and the environmental-economic tradeoffs in manufacturing technologies. The interdisciplinary nature of his work bridges mechanical engineering, sustainability science, and human factors engineering. His scientific recognitions include: Fellow of AITEM (Italian Association of Manufacturing Technologies), 2018-2022 Vice-President of AITEM, 2017-2018 Steering Committee member of AITEM, 2013-2018 Fellow of CIRP (International Academy for Production Engineering), 2012-present Effective member of CIRP, 2006-2012 Professor Settineri has supervised PhD students including Salvatore Mafrici and Marta Ceroni, whose research focuses on sustainable manufacturing approaches. He has secured numerous research grants, including FACILE (2024-2026) on agile and sustainable hybrid manufacturing, GREENER (2023-2025) on reducing environmental impact of metal forming processes, and 3A-ITALY Spoke 5 (2023-2025) on circular and sustainable Made-in-Italy initiatives. His leadership extends to the Interdepartmental Center J-Tech@PoliTO where he contributes to advancing manufacturing technology research at the university.
