Sebastiano Boscarino is an Associate Professor of Numerical Analysis (MAT/08) at the Department of Mathematics and Computer Science, University of Catania, Italy. His research focuses on numerical methods for conservation laws , stiff problems , hyperbolic systems with relaxation terms , and kinetic problems , with a special emphasis on semi-Lagrangian methods. Education: Ph.D. in Applied Mathematics (2006, University of Catania), Laurea in Mathematics (2001, University of Catania) Research Projects: Coordinated national and international projects including PRIN 2017/2022 and European MODCLIM/MODCOMPSHOK. From 2016 to 2023, his publications highlight high-order semi-implicit and IMEX schemes for evolutionary PDEs , particularly in gas dynamics , Boltzmann equations , and shallow water models . Collaborations include institutions in the USA, South Korea, and Germany. He has organized international workshops and minisymposia at conferences like ICIAM, SCICADE, and ODS2018, and serves as a referee for journals such as SIAM Journal on Scientific Computing and Journal of Computational Physics. His teaching includes courses in Numerical Analysis and participation in PhD programs since 2017.
Pietro Cornetti is an Associate Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Politecnico di Torino, where he also serves as Coordinator of the Doctoral School in Civil and Environmental Engineering. He is a member of the SISCON Interdepartmental Center for the Safety of Infrastructures and Constructions and the Doctoral School Council. His academic career has been deeply rooted at Politecnico di Torino, where he completed his education and has held continuous academic positions since 1999. His research interests span a broad spectrum of solid and fracture mechanics, with a focus on finite fracture mechanics , fractional calculus , fractal geometry , non-local elasticity , size effects in concrete and granular materials, and structural retrofitting using FRP/FRCM systems . His work bridges theoretical mechanics with practical applications in civil engineering and structural integrity. The 15 most recent publications highlight a strong trend toward integrating advanced mathematical frameworks—particularly fractional calculus and phase-field modeling—with classical and finite fracture mechanics. These works address brittle fracture, dynamic crack propagation, fatigue in composites, and debonding phenomena, demonstrating a consistent focus on improving predictive models for structural failure across scales. He actively mentors PhD students and leads major research initiatives, including the H2020-funded NEWFRAC project and the nationally funded REHARZE project on retrofitting historic architecture for zero emissions. His teaching portfolio includes Solid Mechanics, Structural Mechanics, Fracture and Plasticity, and advanced topics in computational mechanics across undergraduate, master's, and doctoral levels. He is affiliated with several professional organizations: Italian Group of Fracture (IGF) Italian Association of Applied and Theoretical Mechanics (AIMETA) European Structural Integrity Society (ESIS), Technical Committee TC16 He has served on the program committee of the International Conference on Fracture (ICF14) and participated in the organizing committee of AIMETA XXI. His research is supported by competitive grants from national (PRIN) and EU (H2020) funding programs. He supervises a research group focused on fracture mechanics and leads the Laboratorio di Meccanica della Frattura (DISEG) , which supports experimental and computational research in structural integrity. His team works on both theoretical developments and practical applications in civil and environmental engineering.
Paolo Bonicatto is an Assistant Professor in the Department of Mathematics at the University of Trento . His teaching responsibilities include courses such as Analisi matematica 2 for Industrial Engineering students, focusing on differential and integral calculus for functions of several variables and applications to physics. He also contributes to advanced programs in Mathematics at the Master's level, including Geometric Measure Theory and Optimal Transport , emphasizing problem-solving and mathematical modeling skills. His research interests span Geometric Measure Theory , Optimal Transport , and Partial Differential Equations (PDEs) , with a focus on topics like current transport, regularity theory for transport equations, and applications to material science. Recent work involves the analysis of advection-diffusion equations, homogenization of elasto-plastic evolutions, and the structure of divergence-free measures in low dimensions. His publications highlight contributions to the well-posedness of transport equations, renormalization techniques for vector fields, and the study of BMO-type norms and Poincaré inequalities. Notably, his work addresses foundational questions in calculus of variations and functional analysis, such as representations of total variation and decomposition results for vector fields. While no scientific awards or grants are explicitly listed, his academic output reflects active engagement with cutting-edge problems in mathematical analysis. He collaborates on interdisciplinary projects, bridging pure mathematics and applications in physics and engineering. No lab affiliations or student advisements are documented in the provided materials.
Daniele Cappelletti is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Politecnico di Torino, where he conducts research in stochastic modeling of biochemical reaction networks. He holds a PhD from the University of Copenhagen and has held postdoctoral positions at ETH Zurich, University of Wisconsin-Madison, and the University of Copenhagen. He is affiliated with the 'Probability and Applications' research group and leads the ConStRAINeD project funded by the Italian PRIN program. PhD in Probability, University of Copenhagen (2012–2015) M.S. in Mathematics, Pisa University (2009–2012) B.S. in Mathematics, Pisa University (2005–2009) His research focuses on stochastic processes, probability theory, and mathematical biology, particularly in the modeling and analysis of chemical reaction networks. He investigates the long-term behavior, stability, and model reduction in both deterministic and stochastic frameworks, with applications in systems biology and synthetic biology. His work bridges theoretical mathematics with practical biological systems, especially those exhibiting absolute concentration robustness. The trend in his recent publications shows a strong emphasis on the mathematical foundations of stochastic reaction networks, including tier structures, non-explosivity, and approximation techniques. He has also extended his work into computational applications such as using chemical networks to approximate probability distributions and analyzing security in blockchain protocols, demonstrating interdisciplinary reach across mathematics, biology, and computer science. Daniele Cappelletti currently supervises PhD student Giulio Cuniberti in the Mathematical Sciences program at Politecnico di Torino. He has been involved in competitive research grants, most notably as Scientific Manager of the ConStRAINeD project (2023–2026), which aims to advance the convergence and stability theory of reaction network dynamics. He has not received any explicitly mentioned scientific awards in the provided text. He is actively involved in teaching across multiple programs, including Mathematical Engineering, Data Science and Engineering, and Management Engineering. He teaches courses on stochastic processes, statistics, and time series analysis, both as course instructor and collaborator. He is a member of the Doctoral College in Mathematical Sciences and participates in the College of Management and Production Engineering and the College of Mathematical Engineering.
Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.
Carmelo La Rosa is an Associate Professor of Physical Chemistry at the University of Catania, Italy, with research focused on protein folding-misfolding dynamics and amyloid aggregation mechanisms in diseases like Alzheimer's, Parkinson's, and Type 2 Diabetes Mellitus. His work bridges experimental biophysics and computational modeling to elucidate how metal ions , lipid bilayers , and nanoparticle interfaces influence amyloid toxicity. Since 2011, he has led the Lyotropic Liquid Crystals Laboratory, advancing model membrane systems. Key research areas include: Elucidating prefibrillar oligomer structures in amyloid diseases Investigating GXXXG motif stabilization in ion-channel-like amyloid pores Developing lipid-chaperone hypothesis framework for membrane damage Applying DSC, CD, MD simulations to thermodynamic analysis His publications (spanning 1996-2024) emphasize membrane-protein interactions , computational drug design , and nanoparticle-based diagnostic tools . He has served on editorial boards (Molecules, World Journal of Diabetes) and evaluated grants for NSERC, CINECA, and ANR. Recent work (2021-2024) explores lipid homeostasis in Alzheimer's, nanodisc integrity for membrane studies, and electrostatic regulation of amyloid-membrane interactions.
Maria Clelia Righi is Full Professor at the Department of Physics and Astronomy “Augusto Righi” of the University of Bologna, Italy. She also serves as Visiting Professor at Imperial College London and acts as scientific advisor to TotalEnergies. Her research centres on computational methods for predicting materials behaviour, with a focus on surface and interface phenomena and tribology. Education 2004 – PhD in Physics, University of Modena and Reggio Emilia 1998 – Laurea Degree in Physics (Cum Laude), University of Modena and Reggio Emilia Research Interests Maria Clelia Righi develops and applies ab-initio and multiscale computational techniques to understand how mechanical stress activates chemical reactions at interfaces and to design advanced lubricants and low-friction materials. Her group pioneered first-principles tribochemistry modelling and collaborates with leading experimental laboratories and multinational companies. Major funded initiatives include the ERC Consolidator Grant “SLIDE” (2020-2025) and the HORIZON-RIA project STORMING, where she coordinates the modelling work-package on CO₂-free methane cracking reactors. Scientific Awards & Distinctions ERC Consolidator Grant 2019 – SLIDE PRACE and DEISA supercomputing allocations (multiple) Marie Curie Individual Fellowship PATCHES – supervisor Supervision & Grants She has supervised 13 PhD students, 19 MSc students, 10 post-doctoral researchers and 2 industry-seconded researchers. Her group has secured funding from the EU (ERC, H2020, Horizon Europe, PRACE), Italian regional authorities and industry contracts with Toyota Central R&D Labs and Total Marketing Services. Editorial & Professional Service Member of the editorial boards of Scientific Reports , Lubricants , Lubrication Science and Coatings .
Luigi La Riccia is a researcher at the Interuniversity Department of Regional and Urban Studies and Planning (DIST) within Politecnico di Torino . He specializes in GIS, remote sensing, and digital twins for environmental planning, with a focus on landscape and territorial resilience. Research Interests : Digital twins, participatory GIS, blue/green infrastructure, climate action, sustainable cities Teaching Roles : PhD and master’s courses in urban and regional development (2024/25-2019/20) His work addresses the intersection of geospatial technologies and sustainable development goals (SDG 11, 13, 14, 15). Recent research explores semi-supervised LiDAR segmentation, ecological networks in marginal areas, and climate-adaptive urban design. Articles highlight innovations in satellite big data analysis and AI-driven tools for territorial planning. Scientific Awards : Agritecture and Landscape Awards - Expo Milan (2015) Erasmus+ KA2 Strategic Partnerships (2019) He contributes to editorial boards and international conferences (e.g., IUCN World Conservation Congress, Urban E-Planning conferences). His projects include Turin3D, Turin digital twins, and SDG11Lab initiatives.
Professor Alessandro Chiuso is a Full Professor in the Department of Information Engineering at the University of Padova, Italy. His research focuses on control systems, machine learning, system identification, and their applications to neuroscience and medical imaging. He has contributed to advancing data-driven control methodologies, regularization techniques, and brain network modeling. His work bridges theoretical control systems with practical applications, including predictive control under uncertainty, nonlinear system identification, and understanding brain dynamics through fMRI and PET data. Notable areas include developing algorithms for adaptive control, optimizing brain region interactions, and analyzing metabolic-functional couplings in neurological conditions. Recent publications highlight advancements in policy gradient methods for LQR control, sparse dynamic causal models for brain aging studies, and predictive control frameworks for stochastic systems. His research emphasizes the integration of machine learning with classical control theory to solve complex real-world problems.
Prof. Alberto Salvadori is an Associate Professor at the University of Brescia (Italy) and Research Assistant Professor at the University of Notre Dame (USA). He founded and leads the Multiscale Mechanics and Multiphysics of Materials Lab, focusing on computational modeling of complex physical phenomena across multiple scales. He holds a Ph.D. in Structural Engineering from Politecnico di Milano (2000). His research spans: Fracture mechanics and crack propagation in embrittled materials Multiphysics modeling of Li-ion batteries and energy storage systems Mechanobiology of cell motility and protein relocation Machine learning applications in materials science Granular material behavior and powder compaction His publications show strong focus on: Advanced battery technologies and solid-state electrolytes Multiscale computational methods for materials design Biomechanics of cellular processes Innovative fracture propagation algorithms Awards include: Marie Curie Fellowship (2013) from European Union Research funding from: EU Marie-Curie Sklodowska actions University of Notre Dame Italian Ministry of Education Private industry partners He leads the Multiscale Mechanics and Multiphysics of Materials Lab at University of Brescia, collaborating with Cornell Fracture Group and Patient-based Medicine Lab.
Chiara Gastaldi is an Associate Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin, specializing in mechanical design and machine construction. Her academic career spans multiple teaching roles across bachelor's, master's, and doctoral programs, with particular focus on sustainable design, mechanical engineering, and computational methods. She serves on the College of Mechanical, Aerospace, and Automotive Engineering and the College of Biomedical Engineering, contributing to curriculum development and academic governance. Dr. Gastaldi's research centers on bearings, friction, multiphysics modeling, and numerical modeling, with emphasis on sustainable and circular design approaches. Her work bridges traditional mechanical engineering with modern computational techniques, focusing on practical applications in aerospace engineering, computational engineering, fluid mechanics, and sustainable design. She leads the ISED (Industrial Systems Engineering and Design) research group, driving innovation in model-based systems engineering applied to sustainable product development. Her recent publications reveal a strong trend toward integrating sustainability principles into mechanical design, particularly through life cycle assessment methodologies applied to human-powered vehicles and circular design strategies. The research demonstrates growing interest in lattice metamaterials, friction modeling, and computational approaches to mechanical design optimization, with applications ranging from turbine blades to hydrogen storage systems. ASME Yetep Award (2016) ASME Yetep Award (2019) Dr. Gastaldi actively supervises multiple PhD students working on sustainable mechanical design, lattice metamaterials, and circular economy approaches. Her research portfolio includes significant projects funded by competitive calls and commercial contracts, such as PRIME for predictive maintenance, mechanical design of metal scrap crushing machines, CO2 footprint assessment of vehicle aftermarkets, and dynamic design of turbine blades with friction contacts for renewable energy applications. She also serves as an Associate Editor for the PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS. PART C, JOURNAL OF MECHANICAL ENGINEERING SCIENCE and participates in scientific committees including the ASME Technical Committee on Sound and Vibration and the International Committee on Joint Mechanics. Through the ISED research group, Dr. Gastaldi leads collaborative efforts in industrial systems engineering and design, with particular emphasis on sustainable and circular approaches to mechanical product development. Her team works closely with industry partners on practical applications of advanced mechanical design principles, while also mentoring the next generation of engineers through student teams like Policumbent, which focuses on human-powered vehicle design.
Martina Pastorino is a Researcher in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa. Her work focuses on integrating machine learning with probabilistic graphical models for advanced remote sensing image analysis , particularly in multiresolution classification using satellite and UAV data. She teaches courses on Machine Learning for Pattern Recognition and Remote Sensing in master’s programs related to Internet and Multimedia Engineering and Energy Engineering . Research Interests : Remote Sensing, Machine Learning, Image Segmentation, Data Fusion, Hyperspectral Imaging, UAV Applications. Key Techniques : CNN-MRF Hybrids, CRFNet, Probabilistic Graphical Modeling, Multiresolution Analysis. Her recent publications explore applications in wildfire mapping , urban land-use analysis , and hyperspectral-panchromatic fusion , with a focus on improving semantic segmentation accuracy through hybrid deep learning frameworks. She is available for office hours on request via email at martina.pastorino@unige.it .
Nadia Loy is a fixed-term Researcher in the Department of Mathematical Sciences (DISMA) at the Polytechnic University of Turin , specializing in kinetic theory, mathematical biology, and statistical mechanics. She contributes to the 'Models and Methods in Mathematical Physics' research group and leads project components in nationally funded initiatives like ANATOMY (2023-2026) for modeling muscular dystrophies. Current PhD supervisor for Martina Fraia (Scienze Matematiche, 39th cycle) Teaches Theoretical mechanics (Civil and Environmental Engineering) and Algebra lineare e geometria (Management Engineering) Active in interdisciplinary research bridging mathematics with biomedical and social applications Her research focuses on nonlocal kinetic equations for complex systems, including fake news propagation , cancer cell migration , and agent behavior modeling . Recent publications in Kinetic and Related Models and Nonlinearity demonstrate her work in continuum mechanics, nonlinear dynamics, and social diffusion processes. Scientific contributions include: 2025 - Open badge for research communication to citizens 2024 - Collaborative publications on cell mechanics, nonlocal PDEs, and multi-agent kinetic models She actively collaborates on teaching modules across engineering disciplines, from aerospace to architecture, and participates in outreach activities related to mathematical physics applications.
Giacomo Como is a Professor of Automatic Control at the Department of Mathematical Sciences "GL Lagrange" (DISMA) at Polytechnic University of Turin, Italy. He is a member of the Energy Center Lab and actively contributes to interdisciplinary research spanning Distributed Control , Game Theory , Network Systems , and Resilient Infrastructure . Research Focus : His work addresses stability analysis of dynamical flow networks, evolutionary game theory in social and epidemic models, and robust optimization in transportation and energy markets. Scientific Recognition : Recipient of the IEEE CSS George S. Axelby Outstanding Paper Award (2015) for contributions to networked control systems. Publication Trends : Recent articles explore population game stability , opinion dynamics in biased networks , and controlled evolutionary diffusion , reflecting his expertise in merging control theory with network science and social resilience . Key subfields include traffic signal optimization , imitation learning , and systemic risk modeling .
Gianluca Boccardo is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Polytechnic University of Turin, where he conducts research at the intersection of computational fluid dynamics, deep learning, and porous media applications. His work bridges theoretical chemical process development with practical industrial applications in energy systems and sustainable engineering. His research interests span multiple domains of engineering and computational science: Computational Fluid Dynamics for complex engineering systems Deep learning applications in chemical process modeling Multiscale modeling of transport phenomena in porous media Energy processes engineering and sustainable technologies Fluid mechanics applications in industrial contexts Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional computational methods to solve challenging problems in chemical engineering. His work particularly focuses on applying these hybrid approaches to porous media systems, pharmaceutical processes, and energy storage technologies, demonstrating a commitment to both theoretical advancement and practical industrial application. Professor Boccardo actively supervises numerous PhD students working on cutting-edge research topics and leads significant research initiatives including the MULTIPHASE Erasmus Mundus Joint Master program and the BATCAT Battery Cell Assembly Twin project. His research group receives funding from both competitive EU grants and commercial contracts with industry partners. He is an active member of the Molecular Engineering Lab (MolE) and the Multiscale Modeling research group at DISAT, where his team develops innovative approaches to modeling complex chemical processes and developing sustainable engineering solutions.
