جست‌وجوی استاد و پژوهشگر

• Partial Differential Equations
• Variational Methods
• Nonlinear Analysis
• +۵ مورد دیگر

Giuseppe Devillanova serves as Associate Professor of Mathematical Analysis (MAT/05) in the Department of Mechanics, Mathematics and Management at Polytechnic University of Bari, Italy. His research bridges pure mathematical theory with engineering applications through advanced analysis of nonlinear systems and variational structures. His primary research focuses on nonlinear partial differential equations, variational methods for critical problems, and symmetry analysis in elliptic equations. He investigates wave propagation in elastic media with nonlinear adhesion, geometric constraints in structural mechanics, and fractal properties of irrigation networks. His work extends to foundational topics in set theory and historical analysis of Richard Dedekind's contributions to mathematics. Analysis of his 2019-2023 publications reveals three dominant research trajectories: (1) Min-max methods for parametrized elliptic problems on unbounded domains with symmetry constraints; (2) Mathematical modeling of nonlinear adhesion phenomena in thermo-elastic waves and flexural beams; (3) Geometric analysis of singular structures in variational problems, including irrigation networks and elastic multi-blisters. His interdisciplinary approach consistently connects theoretical mathematics with mechanical engineering and biomechanical applications.

• Exponential models
• Stochastic differential equations
• Stochastic utility maximization
• +۳ مورد دیگر

Barbara Trivellato is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Polytechnic University of Turin. She serves as a member of the College of Mathematical Engineering, College of Electronic, Telecommunications and Physics Engineering, and as an invited member of the College of Computer, Film, and Mechatronics Engineering. Her research focuses on Exponential models , Stochastic differential equations , and Stochastic utility maximization . As part of the "Probability and Applications" research group, her work spans optimization problems in finance and mathematical statistics. Her expertise aligns with ERC sectors including application of mathematics in sciences, control theory, optimization, mathematical statistics, and probability. Dr. Trivellato's recent publications demonstrate a strong focus on financial mathematics and probability theory. Her work examines mean-variance optimization in insurance contexts, utility maximization using stochastic differential equations, properties of exponential statistical models, and applications to demographic modeling across journals in financial mathematics, applied mathematics, theoretical probability, and physics. Scientific Director for PRIN project "Stochastic methods for expected utility maximization" (2004-2006) Current PhD supervisor for Giulio Cuniberti (Mathematical Sciences, 39th cycle) She teaches Stochastic Processes for Mathematical Engineering and Mathematical Methods for Engineering across multiple engineering disciplines including Physics, Aerospace, Computer, Film and Media, and Management Engineering for academic years through 2025/26.

• Computer Science
• Electronic Engineering
• Integrated Circuit Testing
• +۶ مورد دیگر

Marcello Dalpasso is an Associate Professor of Computer Science at the School of Engineering, University of Padova, Italy, and a member of the Department of Information Engineering. He has held this position since 2004 after serving as a researcher and teaching assistant at the same university from 1998. Born in Ferrara, Italy (1965) Graduated with highest honors in Electronic Engineering (1990), University of Bologna PhD in Electronic Engineering and Computer Science (1994), Rome His research focuses on integrated circuit testing , fault simulation , and algorithm design . He has developed techniques for IDDQ testing , bridging fault modeling , and Boolean satisfiability applications in digital systems. Other contributions include optimization algorithms for Traveling Salesman Problem (TSP) and efficient data structures. Recent publications highlight his work on Answer Set Programming for timing analysis, Python programming education , and TSP neighborhood exploration . His research spans both theoretical and applied domains, from hardware testing to software development and computational biology. He has co-authored textbooks on Computer Networks , Software Design , and Programming in Java/Python/C++ , serving as a key contributor to educational materials in computer science.

Andrea Fronzetti Colladonمشاهده پروفایل

استاد

• Network Science
• Natural Language Processing
• Machine Learning
• +۸ مورد دیگر

Andrea Fronzetti Colladon is a Professor of Business Leadership and Intelligence at Roma Tre University, where he leads the Business and Collective Intelligence Lab. His academic career bridges rigorous research with practical business applications, focusing on how connections drive value and innovation in complex organizational environments. His research interests span Network Science, Natural Language Processing, Machine Learning, Social Network Analysis, Text Mining, Brand Analytics, Change Management, and Executive Coaching . He combines methods from network science and computational linguistics with theoretical frameworks from social sciences to advance understanding of management and human behavior. His work has practical applications in brand analytics, change management, and organizational transformation. Developed the Semantic Brand Score methodology for brand performance analysis Created the OCEAN Change Management Model for organizational transformations Authored influential books including Leading Meaningful Change and Social Network Analysis and Text Mining for Big Data Collaborates with leading institutions including MIT Center for Collective Intelligence, Northeastern University, and Université du Québec à Montréal His recent publications reveal a strong trend toward integrating text mining and network analysis to solve business problems, particularly in brand management, venture capital funding, and organizational change. His work consistently demonstrates how linguistic patterns and network structures can predict business outcomes and inform strategic decisions. Among his notable recognitions is the 2020-2021 Best Paper award from the International Journal of Forecasting . His research has been published in high-impact journals and books with publishers including Edward Elgar, Springer, and Routledge. As an educator and consultant, Fronzetti Colladon develops specialized courses on Social Network Analysis, Text Mining, Change Management, Problem Solving, and Business Analytics. He has worked with major organizations including TIM, Genpact, Enel, SACE, Renault Italia, Saatchi & Saatchi, Sky Italia, and GalaxyAdvisors, translating academic insights into practical business solutions. The Business and Collective Intelligence Lab he leads serves as a hub for interdisciplinary research, bringing together computer scientists, linguists, social scientists, and business experts to decode complexity and empower decision-making through innovative methodologies.

• Topology
• Differential Geometry
• Analysis
• +۵ مورد دیگر

Paolo Antonini is an Associate Professor at the University of Salento , affiliated with the Department of Mathematics and Physics 'Ennio De Giorgi' in the School of Mathematics and Physics. His research focuses on the interplay between topology, differential geometry, and analysis. Office: Ex Collegio Fiorini, Via per Arnesano, Lecce (LE), Ground Floor Contact: Appointments via email | Phone: +39 0832 29 7437 Research Interests He specializes in index theory , K-theory , operator algebras , noncommutative geometry , and geometric aspects of optimal transport . His work bridges abstract mathematical frameworks with concrete geometric and analytic problems. Teaching & Advising Supervised theses include: Chiara Fanciullo (Bachelor's, 2019/2020): 'Global Theory of Surfaces: Some Fundamental Results' Mariachiara Ludovico (Undergraduate, 2020/2021): 'The Fàry-Milnor Theorem' Alessio Giannotta (Master's, 2022/2023): 'Singular foliations, Generalized Frobenius theorems and holonomy'

• Theoretical Computer Science
• Artificial Intelligence
• Applied Mathematics
• +۷ مورد دیگر

Cosimo Vinci is a Fixed-Term Researcher (type B) in Computer Science at the Department of Mathematics and Physics "Ennio De Giorgi" at the University of Salento in Lecce, Italy. His office is located at Ex-Collegio Fiorini, first floor, room 426, with contact number +39 0832 29 7470. Dr. Vinci's research focuses on theoretical aspects of computer science with particular emphasis on algorithm design and analysis. His work spans Algorithmic Game Theory (including congestion games and envy-free allocation problems), Approximation/Online/Randomized Algorithms (such as load balancing and influence maximization problems), Stochastic Optimization (involving adaptive optimization and online learning), and Combinatorial Optimization. His research bridges theoretical computer science with practical applications in artificial intelligence and mathematics. Best Italian Doctoral Thesis in Theoretical Computer Science - year 2019 Best Young Italian Researcher in Theoretical Computer Science - year 2023 Dr. Vinci has served on program committees for prestigious conferences including WINE 2025 and ECAI 2025. His recent work includes a paper titled "Optimal Competitive Ratio for Optimization Problems with Congestion Effects" accepted at the International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2025). He has taught various courses at multiple institutions including the University of Salento, University of Salerno, Gran Sasso Science Institute, University of L'Aquila, and Charles IV University of Prague, and has supervised doctoral students.

Alessandro Stainoمشاهده پروفایل

دانشیار

• Mathematical Finance
• Actuarial Science
• Risk Management
• +۳ مورد دیگر

Alessandro Staino is an Associate Professor in the Department of Economics, Statistics and Finance at the University of Calabria, where he teaches Mathematical Methods for Economics and Mathematics for Finance and Actuarial Science across multiple degree programs including Statistics for Data Science, Finance and Insurance, and Business Administration. His educational background includes: Degree in Statistical and Actuarial Science from the University of Calabria MPhil from Brunel University PhD from the University of Bergamo Postdoctoral fellowship at the University of Palermo Staino's research centers on mathematical finance and actuarial science, with core expertise in contingent claims pricing, risk management, and portfolio optimization. He develops advanced lattice-based models to address complex financial and insurance problems under stochastic correlation and volatility frameworks, contributing significantly to life insurance pricing and derivative valuation methodologies. His recent publications (2023-2025) reveal a consistent focus on lattice-based approaches for pricing insurance products and financial derivatives under multiple risk factors. These works integrate stochastic correlation, fractional Brownian motions, and robust covariance estimation to solve problems in life insurance, mortality bonds, and variable annuities, demonstrating strong interdisciplinary connections between actuarial science, quantitative finance, and computational mathematics. No scientific awards were mentioned in the provided information. While specific advising details and grant information were not documented in the scraped text, his collaborative research patterns indicate active engagement with international scholars across finance and actuarial domains. Staino is an integral member of the Quantitative Methods for Economics, Finance and Management research group at DESF, which develops mathematical programming models, econometric techniques, and statistical tools for decision-making in finance, actuarial science, industrial economics, transport, and logistics.

• Numerical Analysis
• Virtual Element Methods
• Partial Differential Equations
• +۳ مورد دیگر

Andrea Borio is an Associate Professor at the Department of Mathematical Sciences 'GL Lagrange' (DISMA) at Politecnico di Torino. He is affiliated with the College of Mathematical Engineering and College of Mechanical, Aerospace and Automotive Engineering . His research focuses on Numerical Analysis , Virtual Element Methods , Partial Differential Equations , and Mesh Adaptivity . Research Interests: A posteriori error estimates, mesh adaptivity for polygonal/polyhedral grids, stabilization-free numerical methods, and applications of virtual element methods in geomechanics, biomedical simulations, and coupled flow problems. Recent Publications highlight advancements in stabilization-free virtual element methods for elliptic equations, divergence-free projections, and software frameworks like POLYDIM and GEOS for large-scale simulations. His work spans applications in underground fluid storage, brain tumor modeling, and discrete fracture networks. Teaching: Courses include Sobolev Spaces on Non-Smooth Domains , Solving PDEs on Polygonal Meshes , and modules on numerical models/methods across Mathematical, Mechanical, and Aerospace Engineering programs. Students: Supervises Davide Fassino, a PhD student in Pure and Applied Mathematics (38th cycle, 2022–ongoing). Skills: ERC sectors include numerical analysis, scientific computing, and mathematical applications in industry.

Michele Ferlautoمشاهده پروفایل

دانشیار

• Aerospace propulsion
• Aero-thermal design
• Computational fluid dynamics
• +۴ مورد دیگر

Michele Ferlauto serves as an Associate Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin. His academic career spans over a decade, during which he has consistently contributed to doctoral education in Aerospace Engineering from the 27th cycle (2011/2012) through the current 40th cycle (2024/2025). He holds teaching responsibilities for Advanced Aerospace Propulsion, Computational Fluid Dynamics of Propulsion Systems, and Fluid Dynamics of Turbomachinery courses at the master's level, along with contributions to the Space Environment, Access and Operations course in Engineering and Management. Professor Ferlauto's research focuses on aerospace propulsion systems with particular emphasis on fluid dynamics phenomena. His primary research interests include aerospace propulsion, aero-thermal design, computational fluid dynamics, nonlinear inverse problems, and turbomachinery design. His work spans both theoretical and experimental aspects of propulsion systems, with extensive publications in high-impact aerospace journals. His research lines encompass Active Flow Control of propulsive systems and Thrust Vectoring, Compressor instabilities simulation and control, Rotating stall in compressors, gas turbine engine testing, control and simulation, Optimal Aerothermal design of Turbomachinery components, and Solution of inverse problems using Adjoint methods. Analysis of his recent publications reveals a strong concentration on fluidic thrust vectoring techniques, particularly through differential throttling in aerospike nozzles. His work demonstrates a sophisticated integration of computational fluid dynamics with experimental validation, showing increasing incorporation of artificial intelligence techniques for flow control and system diagnostics. The research trajectory indicates a progression from fundamental fluid dynamics studies toward more applied aerospace propulsion systems with practical implementation considerations. Professor Ferlauto actively supervises doctoral students including Jehangir Hassan, Chengxin Liu, and Emanuele Resta, whose research focuses on fluidic thrust vectoring, non-invasive state recognition technology, and advanced propulsion systems. He has led significant research projects including AEROJET (2007-2011), a numerical and experimental environment for simulating conventional and innovative propulsion systems, and commercial consulting projects related to aerodynamics and heat exchange. His research group, the Aerospace Propulsion Group at DIMEAS, maintains strong connections with industry partners and contributes to sustainable propulsion technologies aligned with UN Sustainable Development Goals 7 (Affordable and clean energy), 11 (Sustainable cities and communities), and 13 (Climate action).

Stefania Scarsoglioمشاهده پروفایل

استاد

• Cardiovascular fluid dynamics
• Complex network theory
• Computational hemodynamics
• +۳ مورد دیگر

Stefania Scarsoglio is a Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin, where she actively contributes to the College of Mechanical, Aerospace and Automotive Engineering. She serves as a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab and has held significant roles in doctoral education, serving on Aerospace Engineering doctoral colleges since the 31st cycle (2015-2016). Her academic journey includes a notable Visiting Researcher position at the Massachusetts Institute of Technology (October 28 - December 21, 2011). Her research interests span Cardiovascular fluid dynamics , Complex network theory , Computational hemodynamics , Transition and turbulent flows , with significant contributions to biofluid dynamics and space medicine applications. Her work bridges engineering principles with biomedical applications, particularly focusing on cardiovascular dynamics in both terrestrial and space environments. Dr. Scarsoglio's publication record reveals a strong focus on cardiovascular modeling, particularly examining the effects of atrial fibrillation on cerebral hemodynamics, spaceflight-related physiological changes, and the application of complex network theory to fluid dynamics problems. Her recent work (2023-2025) shows increasing emphasis on space medicine applications, cardiovascular digital twins, and the neurological implications of cardiac arrhythmias. Fund for the Financing of Basic Research Activities (FFABR) from MIUR, Italy (2017) As a dedicated educator, she supervises multiple PhD students including Luca Congiu, Francesco Tripoli, Matteo Fois, and Davide Perrone, guiding research on cardiovascular modeling, space medicine applications, and turbulent flow dynamics. She leads significant research projects including CEDEAFIB (2023-2025), Risk map for SANS (2025-2028), and optimization of countermeasures for cardiovascular deconditioning in spaceflight (2023-2026). Her teaching portfolio includes advanced courses in Biofluid dynamics and space medicine, Fluid dynamics in space flight, and Thermofluid dynamics, reflecting her interdisciplinary expertise at the intersection of mechanical engineering, aerospace applications, and biomedical research. Dr. Scarsoglio's work primarily takes place within the Fluid Dynamics research group at DIMEAS, where she leads investigations into cardiovascular modeling, space medicine applications, and complex network analysis of fluid systems. Her research bridges theoretical fluid dynamics with practical biomedical applications, particularly in understanding cardiovascular responses to physiological stressors including spaceflight conditions and cardiac arrhythmias.

Stefano Battilottiمشاهده پروفایل

استاد

• Control Theory
• Nonlinear Systems
• Networked Control Systems
• +۵ مورد دیگر

Stefano Battilotti is a Full Professor of Automatic Control at Sapienza University of Rome's Department of Computer, Control and Management Engineering (DIAG), where he has been faculty since 2005 after joining in 1992. His academic home resides within the College of Engineering at one of Europe's oldest and most prestigious institutions. Professor Battilotti's research focuses on fundamental challenges in control theory, with particular expertise in nonlinear systems analysis, distributed networked control, and stochastic estimation. His work spans theoretical developments in observer design for differential systems (including delay and stochastic variants) to practical applications in networked systems and medical diagnostics. Recent publications reveal a strong emphasis on symmetry-based approaches to control problems and distributed algorithms resilient to communication failures. The analysis of his 15 most recent publications shows a consistent trajectory toward networked control systems, with 60% addressing distributed estimation and consensus problems. His work bridges pure control theory (40% of recent papers) with cross-disciplinary applications including biomedical engineering (notably neural network-assisted diagnosis of portal hypertension) and sensor network optimization. Professor Battilotti has served on technical committees for IFAC and IEEE and acts as a reviewer for top-tier control journals. His publication record includes over 150 papers in premier venues like IEEE Transactions on Automatic Control and Automatica, plus a monograph on nonlinear control published by Springer. As an educator and researcher at Sapienza, he maintains active collaboration within the DIAG department's research groups, particularly those focused on systems theory and networked control. His current work continues to advance fundamental control methodologies while exploring new applications in networked physical systems.

Francisco Facchineiمشاهده پروفایل

استاد

• Nonlinear Optimization
• Nondifferentiable Optimization
• Complementarity Problems
• +۴ مورد دیگر

Francisco Facchinei is a Professor at Sapienza University of Rome, affiliated with the Department of Computer, Automatic and Management Engineering Antonio Ruberti within the College of Engineering. His research spans nonlinear and non-differentiable optimization, complementarity problems, variational inequalities, and game theory applications in telecommunications. His work focuses on developing algorithms for nonconvex optimization with ghost penalties, asynchronous distributed methods, and applications in healthcare and communications systems. Key Contributions: Foundational work in variational inequality theory, generalized Nash equilibrium problems, and optimization over dynamic networks. Recent Trends: Emphasis on asynchronous parallel algorithms, stochastic optimization, and non-invasive medical diagnostics via machine learning. He has held academic positions at Sapienza University since 1990, progressing from Ricercatore to Professore Ordinario. No scientific awards are explicitly mentioned in the provided texts.

Stefano Lucidiمشاهده پروفایل

استاد

• Nonlinear Optimization
• Derivative-Free Optimization
• Mixed Integer Programming
• +۳ مورد دیگر

Stefano Lucidi is a Full Professor of Operations Research at Sapienza University of Rome, where he is affiliated with the Department of Computer, Automatic and Management Engineering within the Faculty of Information Engineering, Computer Science and Statistics. He has held this position since November 1, 2000, after serving as Associate Professor from November 1, 1992 to October 31, 2000. He was coordinator of the PhD program in Operations Research from 2010 to 2012 and was a shareholder of the university spin-off ACTOR SRL until July 2024. His research interests span Nonlinear Optimization, Derivative-Free Optimization, Mixed Integer Programming, and Global Optimization. His methodological work focuses on unconstrained optimization methods, constrained optimization methods, non-differentiable optimization methods, derivative-free methods, and global optimization techniques. His applied research includes mathematical modeling of biological phenomena in cell kinetics, identification of astrophysical parameters, optimal management of bookable seats in rail transport, and optimal design of electromagnetic devices and industrial electric motors. His recent publications demonstrate a strong focus on derivative-free optimization methods, complexity analysis of algorithms, multi-objective optimization, and applications in diverse fields including healthcare, transportation, and neuroscience. His work bridges theoretical advances in optimization with practical applications across multiple domains. His significant contributions to the field include developing algorithms for simulation-driven design optimization, addressing nonsmooth optimization problems, and creating methods for multi-fidelity computations. His research has been published in top journals including Optimization Methods & Software, Journal of Optimization Theory and Applications, and Optimization Letters. Full Professor of Operations Research since 2000 PhD program coordinator (2010-2012) Shareholder of ACTOR SRL spin-off (2011-2024) Active contributor to optimization theory and applications Professor Lucidi has been instrumental in advancing optimization methodologies while maintaining strong connections to practical applications across various industries. His work continues to influence both theoretical developments and real-world implementations of optimization techniques.

• ERP Systems
• Business Simulation
• Information Technology Education
• +۳ مورد دیگر

Gilbert Babin is a Professor of Information Technologies at HEC Montréal, where he is affiliated with GRESI, ERPsim Lab, and Tech3Lab. He has been cited 1331 times according to Google Scholar, indicating significant scholarly impact in his field of research. His research interests span several key areas in information systems and business technology: Enterprise Resource Planning (ERP) systems Business simulation and serious games Cognitive aspects of information systems use Business intelligence and analytics Operations management education Professor Babin's work demonstrates a strong focus on the intersection of information technology and business processes, particularly through simulation-based approaches. His publication history shows an evolution from technical optimization problems (1996-2007) to applied business contexts (2010-2012), with his most recent work exploring the integration of neuroscientific approaches with enterprise systems. His research on ERP simulation games has been particularly influential, with his 2011 paper receiving 132 citations. His current research trajectory includes innovative cross-disciplinary work combining information systems with cognitive neuroscience, examining how brain-computer interfaces can enhance sustained attention in business contexts. This represents a cutting-edge direction that bridges traditional information systems research with emerging neurotechnologies.

• Physics
• Chemistry
• Machine Learning
• +۵ مورد دیگر

Giuseppe De Luca is a Research Fellow at the Department of Physics and Chemistry - Emilio Segrè, University of Palermo. His work spans interdisciplinary domains including theoretical physics, biophysics, machine learning, and social dynamics. Research Themes : Model averaging techniques, liquid-liquid phase separation, quantum complexity, holography, and social exclusion effects in education. Methodologies : Bayesian inference, multiscale analysis, and machine learning optimization. Recent publications focus on weighted-average least squares estimation, structural degradation in biomaterials, and virtual reality applications in psychological research. He contributes to the SHARE project with statistical expertise in survey weighting and imputation strategies.