جستجوی استاد راهنمای دانشگاهی

• Urban Planning
• Food Logistics
• Regional Development
• +۳ مورد دیگر

Agostino Strina is a Lecturer at the Interuniversity Department of Regional and Urban Studies and Planning (DIST) at Politecnico di Torino. His academic activities include teaching roles in architecture and urban planning modules across multiple academic years (2021/22–2024/25) and research collaborations with the Future Urban Legacy Lab (FULL Research Center). Education: Pursuing a PhD in Urban Planning (XXXVI Cycle, 2020–2024) His research focuses on the intersection of food logistics and urban development, examining how large-scale retail distribution centers transform metropolitan landscapes. Key subfields include food distribution infrastructure, spatial justice, and sustainable urbanization processes. Recent publications analyze logistics-driven urbanization in Italy and suburbanization trends in China. Strina contributes to Italian national conferences (SUI, SIU) and maintains a teaching portfolio covering urban design, territorial planning, and sustainability. His work emphasizes territory-specific planning tools and adaptive design strategies for food systems.

• Advanced and sustainable manufacturing
• Circular economy
• Discrete event simulation
• +۱۱ مورد دیگر

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.

• Machine Learning
• Artificial Intelligence
• Social Networks
• +۳ مورد دیگر

Franco Galante is a Researcher at the Politecnico di Torino , affiliated with the Department of Control and Computer Engineering (DAUIN) and part of the DBDM - Database and Data Mining Group . He contributes to teaching as a Course Collaborator for the Internet Lab course in Electronics Engineering since the 2023/24 academic year. His research interests span Machine Learning , Artificial Intelligence , Social Networks , Data Mining , and Complex Systems , with a focus on algorithmic fairness, decentralized systems, and predictive modeling. His work includes publications on topics like generative AI for information retrieval, influencer dynamics, and fault prediction in industrial processes. Recent articles highlight his exploration of AI agents for network troubleshooting , decentralized algorithms , and social impact optimization , reflecting a trend toward integrating machine learning with real-world applications in both digital and industrial domains. He actively collaborates with researchers like Michele Garetto and Emilio Leonardi, contributing to interdisciplinary studies in data science and social network modeling. As part of the DBDM Group , he engages in data mining and database research. His doctoral thesis, Modeling Social Interactions in Complex Systems (2024), underscores his expertise in network dynamics and simulation models.

Nikhil Jhaمشاهده پروفایل

پژوهشگر ارشد

• Privacy
• Cybersecurity
• Data Mining
• +۳ مورد دیگر

Nikhil Jha is a Research Fellow at Politecnico di Torino's Department of Control and Computer Engineering (DAUIN), focusing on web privacy, data anonymization, and cybersecurity. He earned his PhD in 2024 with a dissertation titled Privacy on the Web: Algorithms, Tools and Measurements . Teaching collaborations in Data Protection, Privacy and Anonymity , Interdisciplinary Projects , and Internet Performance and Troubleshooting Lab courses Member of the DBDM - Database and Data Mining Group His research investigates privacy risks in web technologies, including re-identification attacks on browser APIs, anonymization techniques like z-anonymity, and user behavior with privacy banners. His work spans both theoretical and applied dimensions of web security. Recent publications analyze the robustness of Topics API, practical data stream anonymization, and the evolution of privacy policies. His interdisciplinary approach combines technical cybersecurity research with insights into user interactions and policy compliance. Co-authored publications at major conferences including The Web Conference, ACM Transactions on the Web, and Privacy Enhancing Technologies Symposium At Politecnico di Torino, Jha contributes to teaching in cybersecurity and interdisciplinary projects. He also pursues creative writing through a Master Daimon in Narrative Techniques (Scuola Holden, 2025) and holds Italian journalism credentials since 2018.

• Automotive Engineering
• Structural Engineering
• Finite Element Analysis
• +۴ مورد دیگر

Alessandro Scattina is an Associate Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Polytechnic University of Turin. As a member of the CARS@PoliTO Interdepartmental Center , his work focuses on automotive research and sustainable mobility. He holds a position in the Scientific Disciplinary Sector IND-03/A - Mechanical Design and Machine Construction (Area 0009 - Industrial and Information Engineering). Research Interests: Finite Element Method (FEM), Passive Safety, Lightweight Construction, Simulation Engineering, and Sustainable Automotive Systems Skills: ERC PE8_12 (Lightweight Construction), PE8_7 (Mechanical Engineering), PE7_3 (Simulation Modeling) SDG Contributions: Quality Education (Goal 4), Industry Innovation (Goal 9), Climate Action (Goal 13) His recent works demonstrate expertise in composite material crashworthiness , hybrid structure testing , and automotive safety simulations . Articles show a trend toward green composites , finite element analysis , and impact load characterization , with a focus on electric vehicle design and security barrier performance . Students: Supervises PhD candidates in Mechanical Engineering, including Giovanni Lando (40th cycle) and Elena Caselli (39th cycle) Projects: Scientific Director for HESTER (2023-2026) and UD-BEV (2021-2022), and researcher in SmartCorners (2024-2026) Patents: Co-inventor of commercial vehicle parcel systems and bicycle brake innovations

• Building automation and control systems
• Building energy performance modeling
• Data-driven energy modeling
• +۷ مورد دیگر

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

Giorgio Kaniadakisمشاهده پروفایل

استاد

• Statistical Physics
• Theoretical Physics
• Complex Systems
• +۴ مورد دیگر

Giorgio Kaniadakis is a Full Professor at the Department of Applied Science and Technology (DISAT) of Politecnico di Torino. His research focuses on generalized statistics, theoretical physics, and complex systems, with a strong emphasis on κ-statistics and power-law distributions. Research interests include: κ-Statistics, Power-law Distributions, Quantum Computation, Nonlinear Kinetics, Statistical Physics of Complex Systems His recent publications (2024-2016) span urban scaling laws, epidemiological models, predator-prey dynamics, and quantum statistical mechanics, often applying κ-statistics to interdisciplinary problems in physics, biology, and economics. He has organized major conferences like SigmaPhi2014, SigmaPhi2011, and SigmaPhi2008 as Program Chair. He actively teaches courses in statistical mechanics and physics at both PhD and undergraduate levels. Key teams/groups: Institute of Fundamental Physics and Materials for Nanotechnology (DISAT), Generalized Statistical Mechanics of Complex Systems

• Optimization
• Manufacturing Systems
• Inventory Control
• +۳ مورد دیگر

Dario Bauso serves as Assistant Professor of Operations Research at the Engineering Faculty of the University of Palermo, Italy, with additional affiliation to the Department of Computer Science at the same institution. Education: Laurea in Aeronautical Engineering, University of Palermo, 2000 Ph.D. in Automatic Control and System Theory, University of Palermo, 2004 Visiting Scholar, Mechanical and Aerospace Engineering Department, UCLA, 2001-2002 Short-term Visiting Scholar, Lund University and MIT, 2010 Research Focus: His work bridges Optimization , Manufacturing Systems , Inventory Control , and Game Theory with emphasis on distributed decision-making. He investigates consensus mechanisms in adversarial multi-agent environments using mean-field game theory and nonlinear control frameworks, particularly addressing robustness against disturbances in networked systems. Publication Trends: His research demonstrates deep integration of control theory with noncooperative game dynamics, focusing on large-population regimes where legitimate and malicious agents interact. Key contributions include Riccati equation solutions for consensus problems and Nash equilibrium analyses in distributed control contexts, reflecting strong interdisciplinary connections between systems engineering and strategic decision theory. Professional Service: Member of IEEE Control Systems Society Conference Editorial Board (since 2010), Associate Editor for Dynamic Games and Applications (since 2011), and General Chair of the 6th Spain-Italy-Netherlands Game Theory Meeting (SING 6).

• optimization
• wireless sensor networks
• system level design
• +۲ مورد دیگر

Dr. Carlo Fischione is an Assistant Professor at the Royal Institute of Technology (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and ACCESS Linnaeus Center. He holds a Ph.D. in Electrical and Information Engineering (2005) and a Dr.Eng. in Electronic Engineering (Summa Cum Laude, 2001) from the University of L'Aquila, Italy. His research includes positions at UC Berkeley and KTH. Research Focus: Dr. Fischione specializes in developing fast optimization algorithms for networked systems. His groundbreaking F-Lipschitz optimization theory enables efficient solutions for wireless networks, sensor systems, smart grids, and vehicular networks through novel centralized and distributed computational approaches that outperform traditional Lagrangian methods. Awards and Honors: IEEE Transactions on Industrial Informatics Best Paper Award (2007) IEEE MASS Best Paper Awards (2005, 2009) Ferdinando Filauro Award, University of L’Aquila Alta Formazione Award, Abruzzo Region Government Academic Contributions: He supervises graduate students at KTH and University of L'Aquila, has authored over 50 publications, holds a patent, and serves on conference committees and journal review boards. His industry collaborations include Ericsson, Synopsys, and United Technology Research Center. Research Environment: Leads research at the ACCESS Linnaeus Center, focusing on theoretical foundations and practical applications of optimization in networked systems.

Lorenzo Rosascoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Robotics
• +۵ مورد دیگر

Lorenzo Rosasco is a Full Professor at the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa. He holds roles including University contact for the thematic area "Artificial Intelligence" and membership on the Department Board. His research focuses on machine learning theory, kernel methods, optimization, robotics, and their applications in control systems, domain adaptation, and interdisciplinary fields like biomedical engineering. His educational background includes advanced expertise in mathematical foundations of machine learning, though specific academic credentials are not detailed here. Teaching responsibilities include courses such as MACHINE LEARNING, SEQUENTIAL PREDICTION AND REINFORCEMENT LEARNING, and INFORMATION THEORY AND INFERENCE at both undergraduate and graduate levels. Research interests revolve around developing efficient algorithms for large-scale machine learning, including iterative regularization, transfer learning, and control systems using Koopman operator theory. Notable contributions include work on fast kernel methods, optimization in neural networks, and applications in robotics for tasks like humanoid locomotion and tactile sensing. Recent publications explore topics such as double descent phenomena, sim-to-real transfer learning, and adaptive control strategies. His work bridges theoretical insights with practical applications, emphasizing computational efficiency and interdisciplinary impact.

Agnese Seminaraمشاهده پروفایل

استاد

• Fluid Dynamics
• Biomechanics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Prof. Agnese Seminara is a Full Professor in the Department of Civil, Chemical and Environmental Engineering (DICCA) at the University of Genoa, Italy. She specializes in fluid dynamics, biomechanics, and computational modeling, with research emphasizing turbulence, biological systems, and machine learning applications. Her work spans interdisciplinary areas such as fungal spore dispersal, odor navigation in turbulent environments, and the mechanics of biological tissues and sensory systems. Teaching: Seminara teaches advanced courses including Fluid Mechanics, Turbulence and CFD Models, and Mechanics of Sensory Systems at both undergraduate and graduate levels. Her courses are offered in English and focus on mechanical engineering and bioengineering disciplines. Research Interests: Her research integrates fluid dynamics with biological and environmental systems. Key areas include: (1) turbulence effects on odor transport and navigation strategies, (2) molecular mechanisms in fungal and marine organisms, (3) bioinspired robotics and control systems, and (4) computational modeling for public health challenges like airborne disease transmission. Recent projects explore machine learning applications for wind prediction and odor plume navigation. Publications Trends: Over 50 publications since 2005 highlight her contributions to fluid dynamics, biological systems, and interdisciplinary science. Recent work emphasizes machine learning integration with physical systems, evolutionary biology of sensory organs, and pandemic-related fluid mechanics. Labs/Teams: Collaborates with multidisciplinary teams in bioengineering, physics, and computational science. Active in international research networks focused on mycology, robotics, and environmental fluid mechanics.

Franco Milicchioمشاهده پروفایل

استادیار

• Computer Science
• Computational Mechanics
• Reverse Engineering
• +۷ مورد دیگر

Franco Milicchio is an Assistant Professor (tenured) at the College of Engineering, University Roma Tre. He holds a Ph.D. in Computer Science and Engineering from the same institution and has conducted postdoctoral research in structural engineering. His research spans computational mechanics, reverse engineering, bioinformatics, and mobile application development for cultural heritage accessibility. He has led projects such as the Palazzo Massimo LIS/ASL mobile app (awarded the European Excellence Award for Accessible Tourism) and has contributed to the NeuroLab project for EEG file format analysis. His academic roles include teaching courses like Computer Graphics, Mobile Computing, and Parallel and Distributed Systems. Education: Summa cum Laude Laurea Vecchio Ordinamento (2003), Ph.D. in Computer Science (2007). Advisor: Prof. Alberto Paoluzzi. Dissertation: 'Towards a topological unification of finite computational methods.' Research interests include fluid dynamics simulations, genetic sequence parsing via SIMD acceleration, and deformation analysis in 3D models. He has collaborated on grants such as the Air Force Office of Scientific Research projects on nanocomposites and the CINECA High-Performance Computing initiatives. Awards include the IBM EMEA Student Recognition (2003) and multiple grants for cultural heritage digitization. Key projects: 'Distributed Services with OpenAFS' (Springer, 2007), 'Ostia Antica Mobile for Deaf' (2016), and 'Bimillenary of Augustus' gesture-based app (2014). His work bridges computational methods with real-world applications in engineering, biology, and cultural preservation.

Matteo Scandellaمشاهده پروفایل

استادیار

• Control Systems
• System Identification
• Machine Learning
• +۳ مورد دیگر

Matteo Scandella is an Assistant Professor at the University of Bergamo , Italy, since February 2024. Previously, he served as a post-doctoral researcher at Imperial College London (2020–2024). He holds a PhD in Control Systems (2019) and advanced degrees in Computer Science Engineering from the University of Bergamo (Bachelor 2014, Master 2016). His research focuses on kernel-based machine learning techniques applied to system identification , nonlinear dynamics , and control systems , with emphasis on aerospace applications and mechatronics. He has developed methods for stable nonlinear system modeling, continuous-time system identification, and data-driven control strategies like SelfMPC. Education: Bachelor Degree in Computer Science Engineering (2014) – University of Bergamo Master Degree in Computer Science Engineering (2016) – University of Bergamo PhD in Control Systems (2019) – University of Bergamo Research interests span kernel methods (e.g., manifold regularization, RKHS), stability analysis of nonlinear systems, and data-driven control . His work bridges theoretical advancements with engineering applications such as health monitoring of aerospace actuators and urban traffic optimization. Recent publications highlight innovations in automated MPC tuning and graph-based system identification techniques. Teaching includes courses like Automatica (6 CFU) and laboratory modules in sustainable industrial systems. His research has been published in top journals like Automatica and conferences such as L4DC and SYSID.

• Astrophysics
• Cosmology
• Galaxy Evolution
• +۳ مورد دیگر

Luca Valenziano is a Contract Professor at the University of Genoa, affiliated with the Department of Physics. His research focuses on astrophysics and cosmology, particularly leveraging the Euclid Survey to advance understanding of galaxy morphology, weak gravitational lensing, and cosmic shear. He contributes to the Euclid mission through studies on photometric sample optimization, redshift determination, and the impact of baryonic feedback on cosmological parameters. His work integrates computational methods like deep generative models for predictive analysis. Teaching includes the course FISICA E TECNOLOGIA DELLO SPAZIO in the Master's Program in Physics at the University of Genoa. Recent publications (2021–2022) emphasize methodological advancements for Euclid data interpretation, with a focus on statistical and computational techniques. While no specific awards or grants are listed, his active participation in the Euclid collaboration underscores his role in cutting-edge observational cosmology.

• Bioengineering
• Artificial Intelligence
• Explainable AI
• +۷ مورد دیگر

Gloria Menegaz is a Full Professor of Bioengineering at the Department of Engineering for Innovation Medicine, University of Verona, where she directs the BraiNAVLab. She has been serving in this position since 2021, following her appointment as Full Professor in Computer Science in 2017. Previously, she held Associate Professor and Assistant Professor positions at the University of Verona, University of Siena, and University of Fribourg (Switzerland). Her research spans multiple interdisciplinary fields including bioengineering, artificial intelligence, machine learning, and neuroimaging. She specializes in explainable AI methods applied to biomedical data, with particular focus on brain connectivity analysis using multi-modal neuroimaging data (fMRI, EEG) integrated with genetic information. Her work has resulted in over 160 publications in prestigious journals including IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging, and Frontiers in Neuroscience. Her recent research trends emphasize the development of explainable AI frameworks for clinical applications, particularly in neurological disorder diagnosis and treatment planning. She has pioneered approaches for integrating structural and functional brain connectivity data with genetic markers to identify numerical biomarkers for various neurological conditions. Senior Member of IEEE (2017) Chair of Steering Committee of IEEE Transactions on Medical Imaging Member of IEEE-SPS Challenges and Data Collection Technical Committee Vice-Chair of IEEE Bioimaging and Signal Processing Committee Recipient of Rita Levi Montalcini grant Throughout her career, Professor Menegaz has secured over 1 million euros in research funding from international institutions including the European Commission (H2020, FP7), European Science Foundation, MIUR (PRIN, SIR, FIRB), and ANR (France). She maintains extensive international collaborations with Georgia Tech University, INRIA (France), EPFL (Switzerland), Queen Mary University, and University College London. Her laboratory, BraiNAVLab, focuses on developing advanced computational methods for brain imaging analysis and navigation.