Find Academic Supervisors

• Semantic Web
• Knowledge Representation and Reasoning
• Artificial Intelligence
• +5 more

Floriano Scioscia is an Associate Professor at the Polytechnic University of Bari, Italy, specializing in Information Processing Systems (SSD ING-INF/05). His research bridges Semantic Web technologies, Knowledge Representation, and Artificial Intelligence to develop innovative solutions for Internet of Things, Blockchain, and smart city infrastructures. His primary research domains include Semantic Web, Knowledge Representation and Reasoning, Internet of Things, Blockchain, Edge Computing, and Artificial Intelligence. He applies these to solve critical problems in smart mobility (e.g., blockchain-enhanced ridesharing), last-mile logistics optimization, energy infrastructure management, and healthcare decision support. His work consistently focuses on creating lightweight, scalable frameworks like Tiny-ME for resource-constrained environments and semantic-enhanced platforms for real-world system integration. Analysis of his 2023-2025 publications reveals a dominant trend toward edge-centric semantic technologies. Key themes include OWL reasoning on constrained devices (Tiny-ME Wasm), blockchain integration for transparent service platforms (RideMATCHain), and AI-driven optimization for logistics/smart cities. His work demonstrates exceptional cross-domain applicability, with consistent emphasis on explainability, scalability, and practical implementation in transportation, energy, and healthcare infrastructure. The publications show strong synergy between theoretical knowledge representation advances and deployable system architectures.

• Quality Engineering
• Industrial Metrology
• Sustainability
• +4 more

Alberto Piovano is a PhD candidate in Management and Production Engineering at the Polytechnic University of Turin, Department of Management and Production Engineering (DIGEP), while serving as an external lecturer and teaching assistant for academic courses. His academic background includes: Current PhD Candidate in Management and Production Engineering, Polytechnic University of Turin (2023-2026) under supervisors Maurizio Galetto and Gianfranco Genta Professional experience in open innovation at Leonardo S.p.A. and consulting prior to doctoral studies Dr. Piovano's research concentrates on sustainability and quality in the agri-food sector, with specific emphasis on digital transformation through Industry 4.0 technologies, process optimization methodologies, and certification impacts within circular economy frameworks. His work bridges industrial metrology with sustainable systems design across food production value chains. His publication on sterilization process optimization demonstrates an interdisciplinary approach merging manufacturing engineering with sustainable food processing. This research contributes to eco-efficient industrial practices by developing multi-objective models that balance quality, resource consumption, and economic viability in perishable goods processing. As an educator, he actively collaborates in teaching Quality Engineering for Master's students in Management Engineering and facilitates industry-linked Challenge@PoliTo projects, integrating real-world problem-solving into engineering education.

• Advanced and sustainable manufacturing
• Circular economy
• Discrete event simulation
• +11 more

Claudio Castiglione is a Fixed-term Assistant Professor at the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino, Italy. His research focuses on Advanced and Sustainable Manufacturing , Circular Economy , and Process Mining within the domain of Industrial Engineering. Scientific Disciplinary Sector: IIND-04/A - Manufacturing Technologies and Systems ERC Sectors: Control Theory, Scientific Computing, Simulation Engineering SDG Goals: Industry Innovation (9), Responsible Consumption (12) His recent work emphasizes digital twin generation for manufacturing systems using production data and process mining techniques. This research aims to enhance resource management by improving environmental sustainability and technical performance. His publications from 2024-2018 span topics like Scheduling Optimization , Industrial Symbiosis , and Waste Valorization . Key Article Trends : Digital twin methodologies for manufacturing Circular economy implementation at scheduling level Multi-layer performance assessment frameworks Stakeholder-driven sustainable production networks Matheuristic algorithm applications in scheduling Inventory balancing in customer-driven demand He teaches Management Systems Simulation and Production Planning and Control at the Master's and Bachelor's levels in Management Engineering. Despite extensive collaborations, no formal student advising roles or scientific awards are documented in the provided information.

• Applied Geophysics
• Environmental Engineering
• Geophysical Methods
• +4 more

Francesca Pace is a Fixed-term Assistant Professor at the Department of Environmental, Land, and Infrastructure Engineering (DIATI) within Politecnico di Torino. She actively contributes to teaching in the College of Environmental and Land Engineering, serving as Main Instructor for Optimization Methods in Matlab (Civil and Environmental Engineering PhD program) and Course Collaborator for multiple geophysics and geothermal energy courses. Research Focus: Applied geophysics, environmental engineering, and computational optimization techniques Expertise: Particle Swarm Optimization, geophysical inversion, thermal modeling, seismic analysis Her work aligns with UN SDGs 6 (Clean Water), 7 (Affordable Energy), and 9 (Infrastructure Innovation). Recent research publications in Geophysics and Geophysical Journal International demonstrate her expertise in geophysical data optimization and inversion techniques. Francesca holds teaching certifications from Politecnico di Torino's innovative teaching programs and collaborates with colleagues like Alberto Godio and Alessandro Santilano on geophysical modeling projects.

• Building automation and control systems
• Building energy performance modeling
• Data-driven energy modeling
• +7 more

Marco Savino Piscitelli is a Fixed-Term Researcher at the Polytechnic University of Turin within the Department of Energy (DENERG) and member of the Interdepartmental Center SmartData@PoliTO. He actively contributes to the BAEDA Lab (Building Automation and Energy Data Analytics) since 2021. His academic activities span two schools: College of Architecture and Design (as member), and College of Electrical and Energy Engineering (as invited member). Research Interests focus on: Adaptive control strategies for smart buildings Data-driven energy management systems Knowledge graphs and LLMs for building interoperability Fault detection in HVAC and district heating systems Energy benchmarking frameworks Grid-interactive efficient buildings Commercial research projects with generative AI applications Recent Publications (2023-2025) demonstrate expertise in: AI-enhanced energy planning Brick-compliant semantic models Deep learning for power demand forecasting Multi-zone HVAC optimization Experimental building diagnostics Collective self-consumption strategies Teaching Roles include: Lecturer for Energy Management and Automation in Buildings (2023-2025) Collaborator for Energy Transition and Low-Carbon Architecture (2021-2025) Lecturer for Models and Scenarios for Energy Planning (2024) Titolare (lead instructor) for Building Physics and Air Conditioning (2024) Research Projects : 2024-2025 : Scientific Manager for "Data-Driven Performance Analysis through Generative AI" 2023-2024 : Scientific Head for "Advanced data-driven smart reporting systems" Labs & Teams : BAEDA Lab - Building Automation and Energy Data Analytics SmartData@PoliTO - Big Data and Data Science Laboratory Collaboration with CityLearn v2 development team

• Combinatorial optimization
• Statistical physics
• Epidemic inference
• +7 more

Alfredo Braunstein is an Associate Professor at the Department of Applied Science and Technology (DISAT), Politecnico di Torino, and a member of SmartData@PoliTO laboratory. His research spans combinatorial optimization, statistical physics of complex systems, epidemic inference, and computational biology . He leads the Simultaneous Inference from Multiscale Biological Data (SIMBAD) project (2023-2027) and previously led Statistical Inference via Belief Propagation for Epidemics (SIBYL) (2015-2017). He has supervised multiple PhD students in Physics of Complex Systems . Research Interests : Statistical physics, machine learning, network science, epidemic modeling, and optimization. Key Collaborations : Collegio Carlo Alberto, Human Genetics Foundation, and interdisciplinary teams. His recent publications focus on epidemic risk estimation , network dismantling , and message-passing algorithms . He received the La Ricerca dei Talenti award from Fondazione CRT (2015).

Alessandro AgnetisView profile

Professor

• Combinatorial Optimization
• Scheduling Algorithms
• Operations Research
• +3 more

Alessandro Agnetis is a Full Professor at the Department of Information Engineering and Mathematical Sciences, University of Siena, with expertise in combinatorial optimization and scheduling theory. His research spans operations research, multi-agent systems, and lean management applications, with recent publications focusing on adversarial bilevel scheduling, drone emergency logistics, and fairness-utility trade-offs in two-agent systems. Current Courses: Optimization Methods, Combinatorial Optimization, Production Planning (Master's in Engineering Management) Contact: alessandro.agnetis@unisi.it Research Trends: His work addresses complex scheduling problems across manufacturing, healthcare, and logistics, particularly emphasizing: Multi-agent coordination and Nash equilibrium models Parallel machine scheduling with unreliable jobs Emergency delivery optimization using drones Time-critical testing and cross-docking systems Lean management integration in healthcare operations

Vincenzo CagliotiView profile

Professor

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

• Space Debris Management
• Aerospace Engineering
• Satellite Technology
• +3 more

Piergentili Fabrizio is a Full Professor at the Department of Industrial and Aeronautical Engineering, Sapienza University of Rome. His research focuses on space debris management, satellite technology, and advanced aerospace systems. He leads projects in CubeSat development, thermal protection systems, and space environment interaction studies. Key areas of research include optical tracking of space objects, CubeSat missions (e.g., LEDSAT, GreenCube), and space debris monitoring through networks like Sapienza Space Debris Observatory Network (SSON). Collaborations with ASI and INAF enhance his work on orbital dynamics and sustainability. His contributions span experimental platforms such as the ROMULUS balloon-borne receiver and the HORUS CubeSat mission for sub-kilometer remote sensing. He emphasizes hands-on education through student-led projects at Sapienza S5Lab, fostering innovation in small satellite systems and space exploration technologies.

• Building Energy Simulation
• HVAC Optimization
• Renewable Energy Systems
• +3 more

Alessandro Prada is an Associate Professor in the Department of Civil, Environmental and Mechanical Engineering at the University of Trento. His research focuses on optimizing energy efficiency in buildings through advanced simulation techniques and HVAC system innovations. His primary research examines dynamic building performance, hybrid heating systems, and uncertainty quantification in energy models. Recent projects investigate renewable energy communities, photovoltaic self-consumption optimization, and decarbonization strategies for Alpine regions. Dr. Prada develops novel methods for monitoring occupant interactions with building systems and improving simulation accuracy. He actively contributes to building science community initiatives, serving on organizing committees for IBPSA conferences and developing optimization algorithms for building retrofit scenarios.

Maurizio BocciaView profile

Associate Professor

• Operations Research
• Optimization
• Logistics
• +5 more

Maurizio Boccia is an Associate Professor at the University of Naples Federico II, affiliated with the Department of Electrical Engineering and Information Technologies. His research focuses on optimization methodologies and their applications in logistics, transportation systems, and healthcare management. He holds a Ph.D. in Operations Research and has contributed extensively to the development of exact and heuristic algorithms for complex scheduling and routing problems. Key research interests include combinatorial optimization, vehicle routing problems (e.g., TSP variants with drones), automated guided vehicle (AGV) scheduling, and optimization in healthcare settings. He has also explored educational strategies, such as the OPS4Math project, which integrates optimization techniques into mathematics education. His work frequently involves mixed-integer linear programming (MILP), branch-and-cut algorithms, and matheuristics. Notable applications include railway dispatching for the Union Pacific Railroad, operating room planning in hospitals, and logistics network design. He has collaborated on real-world projects, such as improving exam scheduling in Norway and optimizing postal collection routes in rural areas. Boccia’s publications span over two decades, with contributions to both theoretical advancements (e.g., lifted cover inequalities, Fenchel cuts) and practical implementations (e.g., web cache location models, traffic sensor placement). His research often bridges theoretical optimization frameworks with real-world operational challenges.

SAURO LONGHIView profile

Professor

• Automation
• Robotics
• Control Systems
• +6 more

Prof. SAURO LONGHI is a Full Professor at the Department of Information Engineering, Faculty of Engineering, Polytechnic University of Marche. His research focuses on robotics, control systems, industrial automation, and AI-driven solutions for manufacturing and cyber-physical systems. He specializes in fault-tolerant control, predictive maintenance, human-robot collaboration, and autonomous systems resilience against cyber attacks. His work bridges theoretical advancements with practical applications in Industry 4.0, smart manufacturing, and ambient assisted living. Key research interests include: Development of collaborative robotics for industrial processes Real-time anomaly detection using edge AI frameworks Resilient control architectures for UAVs and autonomous vehicles Integration of digital twins for assembly line optimization Psychophysiological interfaces for assistive robotic systems Recent publications highlight advancements in: ISO-compliant human-robot co-transport systems Lightweight neural networks for edge-based anomaly detection Cybersecurity for quadrotor drones Predictive maintenance frameworks using energy data He leads projects like Health@Home , developing smart sensor networks for elderly care. His work emphasizes human-centric design principles in automation technologies.

Patrizia ScandurraView profile

Professor

• Software Architecture
• Formal Methods
• Self-adaptive Systems
• +3 more

Patrizia Scandurra is a Professor at the University of Bergamo, Italy. She has held significant roles including Co-chair of the Doctoral Symposium-track at ECSA 2020, Program Co-Chair for multiple conferences, and is a member of steering and organizing committees for various international software engineering events. Her research focuses on Software Architecture, Formal Methods, Self-adaptive Systems, and Cyber-Physical Systems. She has contributed to frameworks like ASMETA and RAMSES, emphasizing rigorous system design and safety assurance. Her work spans formal specification, model-based testing under uncertainty, and adaptive systems for diverse applications such as automotive systems, medical devices, and smart cities. She has published extensively on topics like self-adaptation under model uncertainty, microservices resilience, and anomaly detection in urban infrastructure. Patrizia’s contributions include conference organization across ECSA, ASE, ICSE, and SEAMS, reflecting her leadership in advancing software architecture theory and practice. Her research bridges formal methods with real-world applications, addressing challenges in autonomous systems and digital twin integration.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +5 more

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

Luca Del ZannaView profile

Associate Professor

• Plasma Astrophysics
• Relativistic Magnetohydrodynamics (MHD)
• Neutron Stars
• +3 more

Luca Del Zanna is an Associate Professor at the Department of Physics and Astronomy , University of Florence. He holds dual affiliations with the University of Florence (UniFi) and the National Institute for Astrophysics (INAF). His research focuses on plasma astrophysics, relativistic magnetohydrodynamics (MHD), and compact objects such as neutron stars and black holes. He leads the Space Plasma and Astrophysics Group at UniFi and co-organizes international workshops like the Arcetri Workshop on Plasma Astrophysics and Vlasovia . Research Interests include relativistic MHD simulations, magnetic reconnection, accretion disk dynamics, and the development of computational tools like the ECHO and XNS codes. His work bridges theoretical and numerical approaches to understand astrophysical phenomena such as gamma-ray bursts, pulsar wind nebulae, and solar/heliospheric processes. Recent Activities : Hosted SoHe4 (2023) and Vlasovia 2024 (2024), co-organized the INFN-TEONGRAV meeting (2022), and commemorated the legacy of Claudio Chiuderi (2022). His research group actively collaborates on projects like the XPE mission and explores multi-scale plasma physics. Publications span over two decades, emphasizing numerical methods, relativistic plasma dynamics, and high-energy astrophysics. He is a key developer of the ECHO code, used for GRMHD simulations of neutron stars and accretion disks.