Find Academic Supervisors

• Computer Science
• Artificial Intelligence
• Distributed Systems
• +3 more

Giacomo CABRI is a Full Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Physical, Computer and Mathematical Sciences. His roles include teaching advanced courses such as Distributed Algorithms, Object-Oriented Programming, and Software Development Methodologies across multiple disciplines including Computer Science, Mathematics, and Medicine. His research focuses on distributed systems, autonomous vehicles, smart cities, and digital twins, with a strong emphasis on applying AI and machine learning to real-world challenges. He actively contributes to academic communities through editorial roles and conference organization. Research interests span distributed algorithms, multi-agent systems, smart infrastructure, and socio-technical systems. His work bridges theoretical foundations with practical applications in transportation, manufacturing, and environmental monitoring. Recent publications highlight innovations in autonomous vehicle coordination, digital twin implementations, and context-aware systems. Teaching responsibilities include courses for Computer Science, Mathematics, and interdisciplinary programs such as Medicine and Dentistry. He integrates hands-on labs and project-based learning, emphasizing practical software development and algorithm design. His courses cover topics like object-oriented programming in Java, distributed systems, and big data architectures. Professional activities include organizing workshops on adaptive computing and collective intelligence, and leading projects like the FIRST initiative for virtual factories. His work addresses challenges in interoperability, scalability, and self-adaptation in complex systems. He maintains a personal website and is active in international collaborations through platforms like ORCID (0000-0002-4942-2453).

Claudio SterleView profile

Associate Professor

• Operations Research
• Logistics Optimization
• Operations Management
• +6 more

Claudio Sterle is an Associate Professor in Operations Research at the University of Naples Federico II, affiliated with the Department of Electrical Engineering and Information Technology (DIETI-UNINA). He also maintains an affiliation with the IASI-CNR Institute for Systems Analysis and Computer Science. His work focuses on optimization methodologies applied to logistics, transportation systems, healthcare management, and manufacturing processes. Research interests include: Combinatorial optimization and integer programming Logistics network design involving drones and multi-agent systems Healthcare operational efficiency (e.g., operating room scheduling) Transportation systems optimization (modal shift incentives, freight distribution) Algorithm development for cutting problems and facility location Recent work emphasizes practical applications like optimizing emergency room operations in Naples hospitals and developing drone-truck collaboration logistics models. His contributions to mathematical programming formulations for complex routing and coverage problems have been widely applied in both academic and industrial contexts. He leads the Optimization and Problem Solving Laboratory, focusing on bridging theoretical optimization research with real-world problem-solving. Teaching efforts include developing problem-based learning strategies for mathematics education through the OPS4Math project.

Adriano MasoneView profile

Lecturer

• Operations Research
• Logistics Optimization
• Supply Chain Management
• +4 more

Adriano Masone is a Lecturer in Operations Research at the University of Naples Federico II's Department of Electrical Engineering and Information Technology (DIETI-UNINA). His research focuses on optimization problems in logistics, healthcare operations, and smart infrastructure systems. He has developed innovative formulations and algorithms for drone routing, vehicle scheduling, and resource allocation in healthcare settings. His work integrates mathematical modeling (e.g., integer linear programming) with real-world applications like blood supply chain reorganization and operating room management. Notable research contributions include: Drone-team logistics for last-mile delivery Emergency room scheduling optimization Smart grid infrastructure optimization using ILP Feature-based approaches for customer classification in routing problems His articles frequently address combinatorial optimization challenges, with a strong emphasis on heuristic and exact algorithm development. Masone also engages in educational initiatives like the OPS4Math project, promoting problem-solving methodologies in mathematics education. He maintains a dedicated research laboratory focused on optimization and problem-solving applications, publishing extensively on topics spanning transportation, healthcare, and industrial engineering.

• Numerical Analysis
• Image Processing
• 3D Reconstruction
• +5 more

Silvia Tozza is an Associate Professor at the Department of Mathematics, University of Bologna. Her research focuses on numerical analysis, image processing, 3D reconstruction, and mathematical modeling in vision. She has expertise in Hamilton-Jacobi equations, shape-from-shading, and computational geometry. Her recent work emphasizes numerical schemes for PDEs and applications in computer vision, such as image inpainting and photometric stereo. She teaches courses in Mathematics for Environmental Sciences and Architecture-Engineering, with office hours available upon email confirmation. Her articles explore topics like semi-Lagrangian schemes, multi-view normal estimation, and thermal insulation optimization. She actively contributes to interdisciplinary fields linking 3D vision to additive manufacturing and astrophysical imaging.

Alessandro FarinelliView profile

Professor

• Artificial Intelligence
• Robotics
• Multi-Agent Systems
• +4 more

Alessandro Farinelli is a Full Professor at the University of Verona's Department of Computer Science. His research focuses on Artificial Intelligence, Robotics, and Cyber-Physical Systems, with a strong emphasis on multi-agent coordination, decentralized optimization, and reinforcement learning. He has led numerous national and international projects in AI and robotics, contributing to high-impact journals and conferences like AAMAS, IJCAI, and IROS. His work bridges theoretical advancements with practical applications in logistics, environmental monitoring, and disaster response. Farinelli's teaching spans Foundations of Artificial Intelligence, Programming Lab II, and specialized courses in Robotics and Autonomous Systems. He has been a key contributor to benchmarking frameworks like RMASBench for urban search and rescue scenarios. His research integrates formal verification methods with reinforcement learning to ensure safety in autonomous systems, particularly in challenging environments like aquatic navigation and medical robotics. His projects include leading the EU-funded INTCATCH for catchment management and collaborating on energy-saving solutions for wastewater systems. Farinelli's contributions also extend to anomaly detection in industrial robots and safe policy synthesis using inductive logic programming.

• Climate Change
• Fluid Mechanics
• Hydraulic Constructions
• +11 more

Diego Avesani is an Assistant Professor at the Department of Civil, Environmental and Mechanical Engineering, University of Trento. His expertise spans Climate Change, Fluid Mechanics, Hydrological Modeling, and Water Resources Management. He teaches courses such as 'Integrated Water Resources Management' and 'Introduction to Climate Change' within the Environmental Engineering and Territory programs. His research focuses on developing advanced hydrological models to address challenges in hydropower optimization, uncertainty analysis, and sustainable water resource management in mountainous and Alpine regions. Key research interests include elevation-driven biases in weather forecasts, integration of satellite data for hydrological modeling, and the role of machine learning in improving forecast accuracy. He has contributed to projects analyzing the Po watershed basin and Alpine regions, emphasizing the interplay between climate change and hydrological systems. His recent publications highlight work on hydropower system modeling, post-processing of seasonal forecasts using neural networks, and reducing uncertainty in large-scale hydrological simulations. These studies often address practical applications in sustainable infrastructure and climate adaptation strategies.

Mario MarinelliView profile

Associate Professor

• Sustainable Mobility
• Transportation Engineering
• Fuel Cell Electric Vehicles
• +3 more

Mario Marinelli is an Associate Professor at the University of Sannio , affiliated with the Department of Transport under the School of Engineering . His research focuses on sustainable mobility, freight transport optimization, hydrogen vehicle applications, and emission reduction strategies. Academic Rank: Associate Professor University: University of Sannio School: School of Engineering Department: Department of Transport Research Interests: Marinelli's work spans transportation systems, with emphasis on low-emission vehicles, fuel cell electric freight transport, and algorithmic approaches to traffic assignment. He has contributed to hydrogen infrastructure modeling, waste management optimization, and demand-responsive urban mobility solutions. His studies frequently involve simulation models and policy impact assessments. Publication Trends: Recent articles address eco-ADAS systems, freight network design, and hydrogen traction. Subfields include emission reduction at signalized intersections, multi-objective transport optimization, and berth allocation using bio-inspired algorithms. Keywords span sustainability, freight logistics, and computational methods.

• Energy Efficiency
• Urban Sustainability
• Historic Preservation
• +3 more

Rosa Francesca De Masi is an Associate Professor at the University of Sannio , Department of Engineering, focusing on energy efficiency in buildings. Her research spans: Energy performance assessment of buildings and historical centers Thermal behavior of innovative envelope solutions Integration of Geographic Information Systems (GIS) for Urban Energy Maps Impact of climate change on building energy balance Development of nearly Zero Energy Buildings (nZEB) in Mediterranean climates Life Cycle Assessment (LCA) of sustainable materials Key publication trends include: 15+ articles on energy retrofit strategies Specialization in thermal bridges and photovoltaic integration Focus on cool roofing materials and hemp-lime composites Methodologies for urban energy mapping and climate resilience She has collaborated with researchers like: Fabrizio Ascione Giuseppe Peter Vanoli Antonio Vanoli Francesco de’ Rossi Valentino Festa

• Quantitative Finance
• Stochastic Volatility Models
• Risk Measurement
• +4 more

Erindi Allaj is an Associate Professor at the Department of Economics and Business Sciences of the University of Parma . She teaches General Mathematics and Quantitative Methods for Financial Markets in the Economics and Management bachelor's program. Office hours: Thursdays and Fridays 10:00-12:00 (in-person by appointment) Research focuses on: mathematical finance, volatility modeling, financial instability prediction, ESG integration in portfolio optimization Research Interests: Her work addresses key challenges in quantitative finance, including no-arbitrage valuation frameworks, stochastic volatility modeling, and financial instability prediction. Recent publications explore ESG integration in portfolio optimization, while earlier works examine transaction cost modeling and the Black–Litterman asset allocation framework. Key Publications Trends: Her research spans 2013-2025 with recent focus on ESG factors (2025), high-frequency data applications (2021, 2024), and financial crisis prediction systems (2022-2023). Academic collaborations include Maria Elvira Mancino and Simona Sanfelici. Contact Information: Email: erindi.allaj@unipr.it Office Location: Department of Economics and Business Sciences – Mathematics Section "E. Levi" Address: Via J.F. Kennedy, 6, 43125 Parma, Italy

Eric MedvetView profile

Associate Professor

• Evolutionary Computation
• Machine Learning
• Grammatical Evolution
• +3 more

Eric Medvet is an Associate Professor of Computer Engineering at the Department of Engineering and Architecture (DIA), University of Trieste, Italy. He leads the Evolutionary Robotics and Artificial Life Lab and co-leads the Machine Learning Lab. His research focuses on Evolutionary Computation, Machine Learning, and their applications to robotics, including Grammatical Evolution, Genetic Programming, and soft robotics. He received the Google Faculty Research Award 2019 for a project on modular soft robots and co-authored a best paper at EuroGP 2024. His recent work emphasizes interpretable control policies, quality-diversity optimization, and evolutionary learning of formal specifications. Medvet teaches advanced courses on machine learning, evolutionary robotics, and programming, consistently updating curricula to reflect cutting-edge research. His labs are hubs for interdisciplinary projects, blending theory with practical implementations in robotics and AI. Research Interests: Medvet’s research spans evolutionary algorithms applied to robotics, with a focus on modular systems. He explores how genetic programming and grammatical evolution can optimize robotic designs and controllers. His work on ‘totipotent neural controllers’ and ‘body-brain co-evolution’ exemplifies efforts to create adaptable, specialized robots. He also investigates formal methods (e.g., STL specifications) for system validation and interpretable AI models. Recent trends in his publications reflect a shift toward practical applications, such as wearable movement analysis and sim-to-real transfer in robotics. Awards: Google Faculty Research Award 2019, EuroGP 2024 Best Paper Award Labs: Evolutionary Robotics and Artificial Life Lab, Machine Learning Lab Teaching: Courses include Advanced Programming, Introduction to Machine Learning, and Evolutionary Robotics, with a focus on Java and practical software development. Medvet’s approach integrates theoretical rigor with hands-on experimentation, emphasizing open-source tools like JGEA and 2D-VSR-Sim. His work bridges computational intelligence and real-world robotics challenges, driving innovation in both fields.

• Mathematical Methods in Economics
• Finance
• Actuarial Sciences
• +5 more

Gianni Bosi is a Full Professor at the Department of Economic, Business, Mathematical and Statistical Sciences (DEAMS Bruno de Finetti) of the University of Trieste. His research focuses on mathematical methods in economics and finance, particularly utility theory, order theory, and multi-utility representations. He has contributed to foundational work on continuous and semicontinuous representations of preorders, topological structures in utility theory, and optimization techniques. Key projects include the FRA 2018 project 'UMMMM' on uncertainly modeling and the 'CLASS4.0' cluster for data-driven solutions in the sea economy sector. His recent publications address advanced topics like ad hoc continuity of interval orders, net-compact topologies, and cinema-based mathematics education. No awards or student advisees are explicitly mentioned.

• Operations Research
• Vehicle Routing Problem
• Machine Learning Applications
• +7 more

Giusy Macrina is a Researcher at the Department of Mechanical, Energy and Management Engineering (University of Calabria, Italy). Her work focuses on Operations Research and Machine Learning applications to complex logistics and transportation problems. Specializes in Vehicle Routing Problems with drones and crowd-shipping Develops hybrid algorithms combining mathematical optimization and artificial intelligence Active in green logistics and sustainable transport systems Collaborates with international institutions like Amazon Her research spans smart mobility , energy-efficient delivery systems , and IoT localization challenges . Recent publications demonstrate her focus on integrating machine learning into traditional optimization problems . She teaches courses in Management Engineering , including Methods and Tools for Engineering and Production Management and Control at the graduate level. Her work addresses both static and dynamic optimization challenges in logistics and energy systems.

Claudio SILVESTRIView profile

Associate Professor

• Data Mining
• Privacy in Location-Based Services
• Spatio-Temporal Data Analysis
• +3 more

Claudio SILVESTRI is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He specializes in Computer Science (INFO-01/A), with a focus on data mining, privacy in location-based services, and spatio-temporal data analysis. His research integrates computer science with environmental and biomedical applications. Teaching Responsibilities include courses on Advanced Data Management (Computer Science) and Geographic Information Systems (Environmental Sciences) at the Master's level across multiple academic years. Research Interests span: Algorithms for privacy protection in location-based services Spatio-Temporal Data Warehouses and trajectory analysis Parallel computing on GPU and cloud platforms Applications in fisheries monitoring and diabetic kidney disease modeling Funding Projects include EU initiatives like H2020 (e.g., DC-ren for kidney disease research) and regional grants (e.g., ADMIN4D on Industry 4.0). Key collaborations involve researchers like Salvatore ORLANDO and Debora SLANZI. He is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Social Innovation. Office hours are held Wednesdays 2-4 PM by email appointment.

Antonio VioliView profile

Associate Professor

• Stochastic Programming
• Risk Management
• Energy Procurement
• +4 more

Antonio Violi is an Associate Professor at the University of Sannio (UNISANNIO) in the Department of Law, Economics, Management and Quantitative Methods (DEMM). His research focuses on stochastic programming applications in industrial optimization, energy systems, and logistics. Key research areas include: Stochastic Optimization Risk Management Energy Procurement Smart Mobility Solutions Industrial Performance Modeling Logistics Network Optimization Recent publications (2024) address advanced models for: Production error prevention Dynamic performance evaluation systems Tourism car-pooling optimization Earlier works cover energy market modeling (2008-2021), logistics e-marketplaces (2018), and agri-food supply chain dynamics (2023).

• Aerospace Engineering
• Aircraft
• Composites
• +8 more

Alfonso Pagani is an Associate Professor at the Department of Mechanical and Aerospace Engineering, Polytechnic of Turin. He holds a Ph.D. in Aerospace Engineering (City University of London, 2016) and a Ph.D. in Fluid-dynamics (Politecnico di Torino). His work focuses on aerospace structures, composites, computational mechanics, and multiscale modeling. Research Interests: Aerospace engineering, composite materials, deployable structures, nonlinear dynamics, and spacecraft design. He leads the MUL2 research group and has secured major grants including an ERC Starting Grant (2019) for variable stiffness composites and PNRR projects on additive manufacturing and renewable composites. Recent publications analyze thermal stresses in 3D printed composites, variable stiffness optimization, and deployable space structures. His work integrates Carrera Unified Formulation (CUF) with machine learning for structural analysis. ERC Starting Grant (2019) ACAM8 Best Paper Award (2014) Ian Marshall Best Student Paper (2013) Ernesto and Ben Omega Petrazzini Scholarship (2012) Aldo Muggia Award (2012) He teaches courses such as Asymptotic Methods in Structural Mechanics and Peridynamics, and supervises Ph.D. students in mechanical and aerospace engineering. He collaborates with institutions including Caltech, Purdue, and RMIT, and co-organizes international conferences on advanced materials.