Stefano Riva is a Researcher at NRGroup , with an R&D period spanning from 2022 to today. His work focuses on multi-scale and multi-physics analysis , generation IV reactors , computational fluid dynamics , and model order reduction . PhD Thesis : Development of data-driven Reduced Order Modelling with application to MultiPhysics systems MSc Thesis : Reduced Basis Methods for Data Assimilation with application to real thermal-hydraulics systems (2021) Research Trends : Stefano's publications from 2021–2024 emphasize data assimilation , reduced-order models , and multi-physics systems in nuclear and fluid dynamics contexts. He explores hybrid techniques (e.g., GEIM and PBDW), noise stabilization in data assimilation, and finite element implementations for fluid simulation. His work bridges nuclear reactor analysis and thermal-hydraulics with advanced computational methods. Key Collaborations : Stefano has contributed to projects involving FEniCSx-OpenMC coupling for temperature feedback in neutronic calculations and sensor positioning optimization for Circulating Fuel Reactors .
Giancarlo Sangalli is a Professor in the Department of Mathematics at the University of Pavia. His research focuses on Scientific Computing, particularly Numerical Methods and Applications, with a strong emphasis on Isogeometric Analysis (IGA) for solving Partial Differential Equations (PDEs). He leads the Scientific Computing group and contributes to interdisciplinary fields such as computational mechanics, biomedical engineering, and environmental modeling. His work integrates advanced numerical techniques, including high-order finite element methods, space-time formulations, and matrix-free solvers, to address challenges in computational efficiency and accuracy. Key areas of application include cardiac electrophysiology, wave propagation, and groundwater flow modeling. Sangalli has pioneered low-rank solvers, Tucker tensor-based methods, and immersed boundary techniques to enhance computational scalability. He actively publishes in top journals and conferences, with a focus on advancing IGA theory and its applications to real-world problems. His research also explores uncertainty quantification, Bayesian calibration, and nonlinear dynamics. Despite no explicitly listed awards, his extensive publication record reflects recognition in computational mathematics and engineering. Sangalli collaborates internationally and maintains a research website at https://mate.unipv.it/sangalli . His group's work is supported by projects in computational electromagnetics, structural mechanics, and fluid-structure interaction, demonstrating a commitment to bridging theoretical advancements with practical engineering solutions.
Enrico Carlini is a Full Professor in the Department of Mathematical Sciences (DISMA) at Politecnico di Torino, where he conducts research in algebraic geometry and its applications to tensor decompositions, polynomial representations, and computational mathematics. He teaches courses such as Linear Algebra and Geometry, Mathematical Analysis I, and advanced PhD-level topics in computational algebra and tensor theory. Full Professor in Geometry Department of Mathematical Sciences (DISMA) Politecnico di Torino, Italy Email: enrico.carlini@polito.it His research centers on algebraic geometry, with strong emphasis on tensors, Waring problems, secant varieties, and zero-dimensional schemes. He explores the interplay between abstract algebra and geometric structures, particularly in the context of polynomial decompositions and their applications in computational mathematics. The recent publications highlight a consistent focus on tensor decompositions, secant varieties, star configurations, and the Waring problem. These works span both theoretical advances and computational methods, often bridging pure algebra with practical mathematical modeling. The recurring themes include symmetric tensors, Hilbert functions, and the geometry of special algebraic varieties. Carlini has supervised PhD students, including Stefano Canino, and has been involved in PhD collegia at both Politecnico di Torino and Università degli Studi di Torino. He leads the nationally funded PRIN project 0DISTA (2023–2025) on 0-dimensional schemes and tensor theory. He has also served as an evaluator for the American Mathematical Society and the National Research Council of Canada. He has participated in organizing major conferences such as the SIAM Conference on Applied Algebraic Geometry and workshops on Commutative Algebra and Tensors. His academic engagement extends to a contractual professorship at Monash University (2013–2015), demonstrating international collaboration.
Sergei I. Simak is a researcher at Linköping University, affiliated with the Department of Physics, Chemistry and Biology within the Faculty of Science & Engineering, and also associated with Uppsala University's Department of Physics and Astronomy, Materials Theory. His work is centered on theoretical and computational materials physics, particularly in condensed matter systems. His research interests span condensed matter physics , materials theory , ab initio calculations , thermoelectrics , electronic structure , and phase transitions . He applies first-principles methods to study the thermodynamic, electronic, elastic, and thermal properties of novel materials such as perovskites, MAX phases, and transition metals. The recent publication trends show a strong focus on lead-free perovskites , thermochromic materials , antiferromagnetic semiconductors , and high-pressure phase behavior . His work often involves collaboration across institutions and integrates computational modeling with experimental validation, particularly in energy-related materials. Sergei I. Simak has been supported by major research funders including the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation, and the European Research Council (ERC). He contributes significantly to collaborative projects in functional materials and thermoelectrics. He is involved in the development and application of advanced computational tools such as the Temperature Dependent Effective Potential (TDEP) method for phonon simulations and has contributed to software in open-source journals.
Enzo D'Innocenzo is a Junior Assistant Professor in Econometrics, Statistics, and Data Science at the Department of Economics, University of Bologna. His primary research focuses on advanced econometric methodologies, including time series analysis, statistical inference, asymptotic theory, score-driven models, and financial econometrics with applications to option pricing. Previously, he served as an Associate Researcher at the School of Business and Economics, Vrije Universiteit Amsterdam. Research Interests: Time Series Econometrics Volatility Modeling (GARCH, Score-Driven) Financial Markets Analysis Option Pricing Theories Extreme Value Theory Dynamic Pricing Strategies Notable Publications: His recent work includes advancements in score-driven models for spatio-temporal data (JASA 2023), dynamic partial correlation networks in financial markets (Journal of Econometrics 2024), and analysis of last-minute hotel pricing strategies (2024). His research bridges theoretical econometric innovation with practical applications in finance and hospitality sectors. Professional Activities: Presenter at NESG Conference 2022 (University of Groningen) Active contributor to econometric journals and conferences Maintains personal academic webpage with research links
Pietro De Palma serves as a Full Professor in the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy. His research focuses on fluid machinery systems with applications spanning hydrogen propulsion, renewable energy conversion, and fundamental fluid dynamics. Contact details include email pietro.depalma@poliba.it and office phone +39 080 596 3226 at Via Orabona 4, Bari. His primary research domains encompass Fluid Dynamics , Combustion Engineering , and Turbomachinery , with specialized expertise in hydrogen engine combustion phenomena, wind turbine aerodynamics, and thermal management systems. Recent work investigates lubricant oil interactions in hydrogen engines, Coriolis effects on wind turbine wakes, and stability mechanisms in transitional channel flows. He employs advanced computational methods including Large Eddy Simulation (LES), Reynolds-Averaged Navier-Stokes (RANS), and Dynamic Mode Decomposition (DMD) for complex fluid-structure interactions. Analysis of his 15 most recent publications (2024-2026) reveals three dominant research thrusts: (1) Hydrogen propulsion systems addressing pre-ignition mechanisms and combustion characterization, (2) Wind energy optimization focusing on wake dynamics and floating platform simulations, and (3) Fundamental fluid mechanics exploring coherent structures in turbulent flows. His work consistently bridges theoretical fluid dynamics with practical energy system challenges, particularly in decarbonization technologies. No scientific awards were documented in the provided sources. While student advising details are unavailable in the scraped materials, his extensive publication record indicates active mentorship in mechanical engineering research. No specific grant information appears in the sources, though his involvement in projects like PONa3_00372 'Innovative Processes for Energy Conversion–PrInCE' suggests competitive funding acquisition. Research activities appear centered within the university's Department of Mechanics, Mathematics & Management, with collaborations evident in wind energy and combustion studies through co-authored publications. His work connects with international initiatives like the IEA Wind Task 32 on wind turbine wake behavior.
Massimo Roma is an Associate Professor of Operations Research at the Department of Computer, Control, and Management Engineering "A. Ruberti" of Sapienza University of Rome. He has been with the university since 1996, initially as an Assistant Professor until 2004, and has served as an Associate Professor since January 1, 2005. In April 2021, he obtained the National Scientific Qualification for Italian Universities as Full Professor of Operations Research, indicating his eligibility for promotion to Full Professor. He teaches Operations Research courses in Bachelor's and Master's programs in Management Engineering and Computer Engineering at the Faculty of Engineering. His educational background includes: M.S. degree in Mathematics (summa cum laude) from the University of Rome "La Sapienza" in October 1988 Ph.D. degree in Operations Research from the University of Rome "La Sapienza" in October 1995 Roma's research focuses on Nonlinear Optimization, with particular emphasis on developing methods and algorithms for solving nonlinear optimization problems. His work has made significant contributions to large scale unconstrained optimization from both theoretical and computational perspectives. He also investigates global optimization and constrained optimization problems with specific structures. A notable aspect of his research involves applying optimization and simulation models to solve real-world problems, particularly in healthcare management and transportation logistics. His publication record demonstrates a consistent focus on advancing optimization techniques, especially in Newton-Krylov methods, negative curvature directions, and large-scale unconstrained optimization. In recent years, he has expanded his research to include simulation-based optimization applications in emergency department management and cruise ship itinerary planning, showing the practical impact of his theoretical work across multiple domains. His scientific recognition includes: AIRO Best Application 2015 award by the Italian Operations Research Society for "Optimal Deployment of a cruise fleet" Prof. Roma serves as a member of the advisory board for the Italian Research Doctorate in Automatica, Bioengineering and Operations Research. He regularly advises Bachelor's and Master's degree theses and has been involved in numerous national and international research projects funded by the Italian Ministry of University and Research. In 2011, he co-founded the Academic Spin-off ACTOR (Analytics, Control Technologies and Operations Research) between Sapienza University and ACT Operations Research. He is an active member of the Continuous Optimization research group at DIAG, which focuses on various aspects of optimization including exact penalty methods, non-monotone methods, preconditioning techniques, derivative-free algorithms, and applications in diverse fields such as healthcare, transportation, and engineering design.
Annamaria Bianchi is an Associate Professor of Economic Statistics at the University of Bergamo , specializing in web surveys, online panels, composite indicators, and social media data analysis. She holds a double PhD in Mathematical Statistics from the University of Milan and University Paris VI. Key affiliations: Member of the International Statistical Institute (ISI) , European Master in Official Statistics (EMOS) board member, and research associate at the Institute for Social and Economic Research (ISER) (University of Essex) and Carleton University Current role: Reference Professor for EMOS program at University of Bergamo Research Interests focus on: Improving representativity in non-probabilistic data collection Developing composite indicators for social and economic analysis Methodological innovations in web survey design Machine learning applications for social media data Economic statistics for local development and policy planning Scientific Awards : 2022: Italian Scientific Qualification (ASN) as Full Professor in Economic Statistics Current Research Initiatives : 2023: PRIN Project MYPEOPLE (NRRP) - Measuring inequality, poverty, and living conditions for local strategies
Davide Stocco is a Research Fellow at the Department of Industrial Engineering, University of Trento. He also serves as a Teaching Assistant in the same department, contributing to courses like Computational Methods for Mechatronics and Mechatronic Systems Simulation. His research focuses on symbolic-numerical analysis, differential-algebraic equations (DAEs), and computational mechanics. He develops tools for real-time simulations, tire-ground modeling, and matrix factorization techniques. Recent publications reveal trends in DAE index reduction using symbolic computation, parallel processing of bordered matrices, and geometric modeling for mechatronic systems. His work bridges symbolic mathematics with practical engineering applications. As a Teaching Assistant, he collaborates with Professors Enrico Bertolazzi and Francesco Biral in the Mechatronics Engineering program. He actively contributes to academic research and teaching at the University of Trento.
Stefano Berrone is a Full Professor in the Department of Mathematical Sciences "G.L. Lagrange" (DISMA) at the Polytechnic University of Turin, where he also holds key administrative roles as Vice-Rector for Quality and President of the University Quality Assurance Committee. He is a member of the Interdepartmental Center SmartData@PoliTO and the University Committee for Research, Technology Transfer and Services to the Territory. Department of Mathematical Sciences "G.L. Lagrange" (DISMA), Polytechnic University of Turin Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Scientific leadership in EU, national, and commercial research projects Teaching assignment at Turin Polytechnic University in Tashkent (2012–2014) His research lies at the intersection of numerical analysis, scientific computing, and machine learning, with a strong emphasis on the development and analysis of advanced numerical methods. He specializes in the Virtual Element Method (VEM), mesh adaptivity and generation, high-performance computing (HPC), physics-informed neural networks, and deep learning for engineering problems. His work contributes to computational engineering, data science, and sustainable development (aligned with SDGs 4, 9, and 13). He leads multiple research groups and projects focused on numerical optimization, PDE discretization on polygonal meshes, and simulation of complex physical systems. The recent publications (2023–2025) reveal a strong trend toward hybrid computational methodologies, combining classical numerical techniques like VEM with machine learning, particularly physics-informed and neural-approximated models. There is a clear focus on stabilization-free formulations, mesh optimization, and applications in energetic materials, fluid dynamics, and subsurface modeling. The work spans high-impact journals in scientific computing, computational mechanics, and algorithms. Scientific Participations and Memberships: Full Member, SIAM (Society for Industrial and Applied Mathematics) (2020–present) Full Member, Italian Society of Applied and Industrial Mathematics (2020–present) Full Member, Italian Mathematical Union (2020–present) Full Member, National Institute of Higher Mathematics - National Group for Scientific Computing (1999–present) Research Leadership and Grants: Scientific Responsible, In-Deep (EU Horizon Europe, 2024–2028) Scientific Responsible, PYGEOM (PRIN, 2023–2026) Scientific Director of Structure, SHIMMER (Clean Hydrogen JTI, 2023–2026) Scientific Director of Structure, HPC-Spoke 6 (PNRR, 2022–2025) Scientific Responsible, AdPolyMP (PRIN, 2022–2025) Scientific Responsible, Virtual Element Methods: Analysis and Applications (PRIN, 2019–2022) Scientific Responsible, IDEA (PRIN, 2013–2015) Scientific Responsible, AIRTOLYMI (Regional, 2007–2011) Scientific Responsible, Engine Health Monitoring (Commercial, 2024–2025) Advising and Doctoral Supervision: Supervising multiple PhD students in Pure and Applied Mathematics and Mathematical Sciences Member of Doctoral Colleges in Pure and Applied Mathematics at Politecnico di Torino and University of Turin (2013–2023) Key advisor in research areas including energetic materials, computational fluid dynamics, and numerical PDEs Laboratories and Research Groups: Numerical Analysis and Scientific Computing (DISMA) Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory Lead in developing computational tools like HEMSim for energetic materials simulation
Alessandra Puglisi is a Researcher in the Chemistry Department at the University of Milan since 2010. Her research focuses on stereoselective organocatalysis, chiral catalyst development, and nanoparticle synthesis. She holds a PhD in Industrial Chemistry from the University of Milan (2003) and conducted postdoctoral research at Boston College under Prof. Amir H. Hoveyda and collaborated with Nobel Laureate Prof. Richard R. Schrock at MIT. Education: PhD in Industrial Chemistry (2003) Postdoctoral affiliations: Boston College (2004), University of Milan (2005–2008), ISTM-CNR (2009–2010) Research interests include organocatalytic synthesis of pharmaceuticals, radical chemistry (photocatalysis/electrochemistry), and materials chemistry involving 19F imaging agents. Her work emphasizes chiral catalyst design for stereocontrolled reactions and nanomaterial applications in catalysis. Collaborates with the Benaglia Group, focusing on flow-chemistry, 3D-printed catalytic reactors, and silicon chemistry innovations. Active in developing non-conventional reaction media (e.g., on-water reactions) and H-bond mediated reactions.
Francesco Scarcello is a Full Professor in Computer Science (SSD ING-INF/05) at the University of Calabria. He is affiliated with the Department of Computer Engineering, Modeling, Electronics and Systems Science (DIMES) and has held his current position since 2001. Education: PhD in Computer Science, University of Calabria (1997) His research spans database theory, constraint satisfaction, computational complexity, graph theory, knowledge representation, and game theory. He is renowned for developing hypertree-width decomposition methods, which identify tractable classes of complex problems in databases and CSPs. His publications focus on structural decomposition techniques, conjunctive queries, and disjunctive logic programming. These works have significantly influenced database theory and artificial intelligence. Scientific Awards: 2008 IJCAI-JAIR Best Paper Prize 2009 ACM PODS Alberto O. Mendelzon Test-of-Time Award Professor Scarcello serves as an Associate Editor for the Artificial Intelligence journal and actively participates in international conference program committees. He co-founded two University of Calabria spin-offs: Artémat and DLVSystem Evo-Bi, focusing on technology transfer in knowledge-based systems.
Giovanni Girardi is a Researcher in the Department of Industrial Engineering and Mathematical Sciences at Marche Polytechnic University (UNIVPM) , Italy. His work spans mathematical analysis , partial differential equations , and applied mathematics , focusing on problems involving critical nonlinearity , fractional calculus , and non-local modeling . Contact Information: Email: g.girardi@staff.univpm.it Research Areas: Girardi investigates evolution equations with critical nonlinearities, time-dependent damping mechanisms, and fractional diffusion models. His work extends to environmental applications like plant water deficit modeling through Richards' equation and soil hydrology. Publication Trends: Over the past six years, Girardi's research has focused on fractional and hyperbolic PDEs, critical exponents, and damping effects in wave equations. His 2025 papers emphasize lifespan estimates and well-posedness, while 2024 studies highlight non-local hydrological models. Applications range from theoretical mathematics to environmental engineering.
Biagio Simonetti is an Associate Professor in Statistics (SECS-S/01) at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of the University of Sannio, Italy. He has been serving in this role since 2015, following a progression from Researcher since 2006. His academic journey began with a PhD in Computational Statistics from the University of Naples Federico II in 2003. His research interests center on applied statistics , particularly in multivariate analysis , correspondence analysis , fuzzy systems , cluster analysis , and ordinal data modeling . His work extends into interdisciplinary domains such as healthcare economics, customer satisfaction, tourism, and financial markets. He has applied statistical techniques to evaluate obesity’s impact on healthcare costs, model doctor-patient communication, and analyze cultural perceptions of food. The trend in his recent publications reflects a strong focus on fuzzy logic , big data applications , and robust statistical methods in socio-economic and health contexts. His work often involves international collaboration, particularly with researchers in Spain, Australia, India, and Turkey. Certificate of Appreciation for collaboration with Hanoi University (Vietnam), 2014 Simonetti has participated in numerous research projects, including European TEMPUS and Jean Monnet programs, and has coordinated EU-funded research on grapevine virology and applied statistics education. He has served on the editorial boards of journals such as the Journal of Reliability and Statistical Studies and Electronic Journal of Applied Statistical Analysis . He has also been actively involved in organizing and serving on scientific committees for international conferences like DYSES, MTISD, and Agrostat. He has collaborated extensively with institutions abroad, including the University of Moncton (Canada), University of Western Sydney (Australia), and Universitat Rovira i Virgili (Spain), and has held research visits in Denmark and Barbados. His academic service includes participation in PhD programs and doctoral examination committees, particularly in biostatistics and socio-economic systems.
Carlo Alberto MAGNI is a Full Professor in the Department of Economics "Marco Biagi" at the University of Modena and Reggio Emilia. He teaches courses including General and Financial Mathematics and Principles and Models for Managerial Decisions for the Business Economics and Management degree program. Professor MAGNI's research focuses on financial mathematics, investment analysis, and capital budgeting. His work centers around the development of the Split-Screen Approach for project appraisal, which unifies financial planning and investment analysis into a single theoretical framework. His research spans corporate finance, accounting, operations research, and mathematical methods of economics, with particular emphasis on NPV-consistency of rates of return, project valuation methodologies, and financial modeling techniques. His publication record shows a consistent output of high-quality research, with numerous articles in top journals. His work demonstrates a strong integration between theoretical finance concepts and practical applications, particularly in Excel-based financial modeling. The Split-Screen Approach represents his signature contribution to the field, providing innovative methods for project appraisal and financial planning. Professor MAGNI has developed comprehensive teaching materials, including a videobook for his courses that combines video lectures with texts related to course topics. His educational approach emphasizes the application of mathematical tools in economic and business analysis, with focus on developing students' ability to model and evaluate long-term managerial decisions.
