جست‌وجوی استاد و پژوهشگر

Antoine Lemenantمشاهده پروفایل

استاد

• Calculus of Variations
• Partial Differential Equations
• Geometric Measure Theory
• +۳ مورد دیگر

Antoine Lemenant is a Full Professor at Université de Lorraine (Nancy, France). He holds an IUF (Institut Universitaire de France) membership since 2023. His research focuses on calculus of variations, geometric measure theory, and partial differential equations, with applications to fracture mechanics and optimal design. He has held positions at University Paris 7 (2010-2018) and was a postdoc at the Centro De Giorgi in Pisa (2009-2010). He completed his PhD at Université Paris-Saclay under Guy David in 2008. Key research interests include: Energy minimization problems (Griffith energy, optimal compliance) Regularity theory for free boundaries and crack sets Numerical methods for geometric optimization Spectral optimization and domain perturbations His recent work (2023-2025) explores regularity properties of Griffith almost-minimizers, optimal design of elastic structures, and phase-field approximations of minimal surfaces. He has co-authored over 40 papers in top journals including J. Math. Pures Appl. and Arch. Ration. Mech. Anal. Awards: Member of Institut Universitaire de France (2023-) Current activities: Organizer of international workshops on calculus of variations Supervises a postdoc position starting September 2024 Laboratory affiliation: Institut Elie Cartan de Lorraine (IECL), a CNRS-affiliated mathematics institute.

• Solvency II
• Insurance Contract Valuation
• Monte Carlo Simulation
• +۷ مورد دیگر

Anna Maria Gambaro is an Associate Professor at the Department of Economics and Business Studies of Università degli Studi del Piemonte Orientale "Amedeo Avogadro". Her research focuses on actuarial science, financial engineering, and stochastic modeling with applications to insurance regulation (Solvency II), healthcare operations, and commodity markets. She has contributed to developing methodologies for risk margin calculation, capacity expansion under uncertainty, and Monte Carlo simulation techniques. Her recent projects include measuring climate-transition risks (funded by MUR) and studying insurance capital requirements (collaboration with Prof. Fusai). She has published extensively in journals like European Actuarial Journal, Production and Operations Management, and The Journal of Derivatives. Expertise: Solvency II compliance, stochastic optimization, Monte Carlo methods, pandemic planning Notable Works: ICU capacity expansion under uncertainty (2023), Risk margin capital-on-capital cost (2025), Pricing on Trees using new risk-free rates (2024) Awards: No specific prizes mentioned, but her work aligns with UN Sustainable Development Goals related to resilient infrastructure and financial inclusion. Grants/Projects: Led or co-led 2 major research projects (2023-2025) totaling €1.2M in funding. Her work on climate-transition risk integrates supply chain and risk management frameworks.

• Numerical Analysis
• Scientific Computing
• Fractional Calculus
• +۲ مورد دیگر

Carlo Marcati is a Researcher in the Department of Mathematics at the University of Pavia, specializing in numerical methods and scientific computing. His research develops advanced finite element methods for fractional partial differential equations and investigates approximation theory for neural operators. Recent work focuses on hp-FEM techniques for integral fractional Laplacians, optimization methods for physics-informed neural networks, and expression rates of deep learning operators for elliptic PDEs in polyhedral domains.

• Biomedical Engineering
• Artificial Intelligence
• Robotics
• +۳ مورد دیگر

Giovanni Corvini is a Research Fellow at the University of Roma Tre, Department of Industrial, Electromechanical and Mechanical Engineering (DIIEM), working within the Applied Electronics BioLab 3. He received his Ph.D. in Applied Electronics (Biomedical Engineering) in 2024 and has established himself as a researcher in biomedical engineering, artificial intelligence, and robotics. Dr. Corvini's research focuses on the neuromuscular system with the aim of advancing robotic neurorehabilitation for both upper and lower limbs. His expertise includes: Analysis of surface electromyography (sEMG) for muscle fatigue assessment Development of novel metrics for high-density sEMG analysis in the time-space domain Human-robot collaboration systems for rehabilitation EMG-based prediction of movement intentions Biomechanical analysis of human-robot interaction His recent publications (2022-2025) demonstrate a strong focus on the intersection of robotics, biomechanics, and neurorehabilitation. Approximately 60% of his work centers on human-robot collaboration systems for upper limb rehabilitation, 30% focuses on advanced sEMG signal processing techniques, and 10% explores applications in epidemiological modeling and workplace ergonomics. His research shows a clear trajectory toward developing more effective neurorehabilitation technologies through the integration of robotics, signal processing, and biomechanical analysis. Dr. Corvini is actively involved in the HYBR-ID project, which aims to develop an upper limb rehabilitation system integrating exoskeleton assistance and functional electrical stimulation driven by user-tailored synergy-based intention detection. He has also developed Matlab code for high-density sEMG analysis in the time-space domain, which is publicly available. His laboratory work is centered at the Applied Electronics BioLab 3 at Roma Tre University, where he collaborates with researchers including S. Conforto, M. Schmid, D. Bibbo, and S. Ranaldi on various aspects of neurorehabilitation robotics and biomechanical analysis. His research has applications in both clinical rehabilitation settings and workplace ergonomics.

• Control Systems
• Game Theory
• Robotics
• +۳ مورد دیگر

Filippo Fabiani is an Assistant Professor at the IMT School. His research focuses on control systems, game theory, and optimization, with applications to robotics, multi-agent systems, and nonlinear dynamics. He explores topics such as Nash equilibrium seeking in strategic environments, fault-tolerant control, and neural network-based system identification. His work combines theoretical advancements in distributed algorithms with practical implementations in aerospace and robotic systems. Notable areas include spacecraft proximity guidance, resilient control for nonlinear systems, and adaptive strategies in competitive multi-agent scenarios. He also investigates belief-sharing mechanisms and robust stabilization under uncertainty. Publications highlight contributions to generalized Nash games, distributed equilibrium-seeking algorithms, and model predictive control. Research spans both foundational theory and applied engineering solutions, emphasizing the interplay between strategic decision-making and control system design.

Antonio Cammiمشاهده پروفایل

استاد

• Nuclear Engineering
• Thermal Fluid Dynamics
• Fusion Energy Systems
• +۴ مورد دیگر

Prof. Antonio Cammi is a distinguished academic focusing on advanced nuclear technologies and thermal-fluid systems. His research integrates computational modeling, experimental validation, and innovative engineering solutions for fusion energy systems, molten salt reactors, and high-performance thermal management. Key areas include gyrotron design for plasma heating, remote maintenance systems for fusion facilities, and reactor safety through multiphysics analysis. He actively contributes to international projects like JUNO (neutrino detection), IFMIF-DONES (fusion materials testing), and EU-DEMO (demonstration fusion reactor). His work bridges fundamental physics with applied engineering, addressing challenges in reactor core dynamics, fuel cycle optimization, and computational efficiency. Notable methodologies include reduced order modeling (ROM), data assimilation techniques, and hybrid simulation approaches. Cammi collaborates with institutions like ENEA (Italian National Agency for New Technologies), ITER, and the University of Pavia (TRIGA reactor). Research interests span fusion plasma physics, advanced reactor materials, neutron radiation effects, and sustainable nuclear energy economics. His team develops novel tools for reactor safety assessment, including digital twins and real-time monitoring systems. Current projects emphasize high-flux testing infrastructure, passive safety systems, and modular reactor designs for next-generation energy systems.

Matteo Barigozziمشاهده پروفایل

استاد

• Political Economy
• Econometrics
• Time Series Analysis
• +۴ مورد دیگر

Matteo Barigozzi is a Full Professor in the Department of Economic Sciences at the University of Bologna. He holds a PhD in Economics and Management from Scuola Superiore Sant'Anna and a Physics degree from the University of Milan. Previously, he was an Associate Professor at the London School of Economics (LSE) and held post-doctoral positions at Université libre de Bruxelles and the Max Planck Institute. His research focuses on econometrics, dynamic factor models, high-dimensional data analysis, and macroeconomic policy. He has developed influential methodologies for analyzing large datasets and their applications in economics and finance. Education : PhD in Economics and Management, Scuola Superiore Sant'Anna (2008) Master's in Physics, University of Milan (2002) Advanced Studies in Mathematical Modelling at ICTP Trieste (2003) Research Interests : Dr. Barigozzi specializes in dynamic factor models, high-dimensional time series analysis, and their applications to macroeconomic and financial systems. His work bridges econometric theory and practical policy analysis, with contributions to output gap measurement, monetary policy effects, and energy demand forecasting. Recent projects emphasize robustness in factor models and network-based approaches. Articles Trends : His recent work emphasizes methodological advancements in factor models, including tail-robust estimation, tensor factor models, and dynamic network autoregressions. Applications span euro area economic policy, energy systems, and financial volatility analysis. Awards : No specific awards listed, but recognized for contributions to econometric methodology. Advising/Grants : Active in academic advising and research grants, though specific details are not provided in the text. Labs/Teams : Affiliated with CREST (ENSAE) and ECARES (ULB). Collaborates with institutions like the Federal Reserve Board and Sciences Po.

• Numerical Analysis
• Geometric Modeling
• Approximation Theory
• +۳ مورد دیگر

Lucia Romani is a Full Professor in Numerical Analysis at the Department of Mathematics, University of Bologna. She holds a PhD from the University of Padua (2004) and a Master's Degree in Mathematics (summa cum laude) from the University of Bologna (2000). Her research focuses on geometric modeling, approximation theory, numerical linear algebra, and applications in computer-aided design and image processing. She has authored over 80 scientific publications and serves on editorial boards of journals like Computer-Aided Design and Computer Aided Geometric Design . She actively participates in SIAM and the Solid Modeling Association (SMA), holding leadership roles such as Vice Chair of the SIAM Activity Group on Geometric Design (2023-2024) and Program Co-Chair of SPM 2025. Her work includes organizing international conferences and supervising numerous theses across PhD, Master's, and Bachelor's levels. Her professional journey includes roles at the University of Milan-Bicocca (2007-2022) and postdoctoral fellowships at the University of Bologna (2003-2007) and the University of Cambridge (2002). She has conducted research visits at institutions like the University of Cambridge, EPFL, and ICTP Havana. She has also served on evaluation committees for doctoral theses and research projects in Italy and abroad. Research interests span subdivision schemes, Pythagorean Hodograph curves, and spline-based interpolation. Her recent work includes advancements in algebraic characterizations of curves, non-stationary subdivision algorithms, and applications in biomedical imaging and computer graphics.

• Numerical Analysis
• Image Processing
• 3D Reconstruction
• +۵ مورد دیگر

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

Sandra Fortiniمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Machine Learning
• Predictive Inference
• +۲ مورد دیگر

Dr. Sandra Fortini is Associate Professor of Statistics in the Department of Decision Sciences at Bocconi University. With research spanning Bayesian statistics, machine learning, and nonparametric models, she investigates asymptotic properties of statistical procedures and predictive inference frameworks. Her methodological work has applications in biostatistics, neural network theory, and clinical trial design. Core research domains include: Asymptotic behavior of Bayesian and machine learning algorithms Deep neural network theory and infinite-width limits Exchangeability principles in predictive modeling Non-asymptotic approximations in statistical learning Bayesian nonparametric methods Recent publications demonstrate strong focus on neural network theory (60% of 2023-2024 works) and Bayesian clinical trial methodologies (40%). Her 2024 Biostatistics article introduces innovative uncertainty-directed factorial designs, while 2023-2024 neural network publications establish fundamental limit theorems for deep learning architectures. Significant recognitions include fellowship status in four prestigious societies: Institute of Mathematical Statistics, International Society for Bayesian Analysis, Italian Statistical Society, and Italian Mathematical Society. Teaching responsibilities encompass probability theory and stochastic processes for undergraduate and graduate programs at Bocconi.

Alessandro Farinelliمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Multi-Agent Systems
• +۴ مورد دیگر

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

Marek Eliasمشاهده پروفایل

استادیار

• Algorithms
• Online Algorithms
• Differential Privacy
• +۹ مورد دیگر

Marek Elias is an Assistant Professor at Bocconi University in Milan, where he is affiliated with the Theory Group . Prior to joining Bocconi, he held postdoctoral positions at CWI (Amsterdam) and EPFL (Lausanne), following a PhD at TU Eindhoven under the supervision of Nikhil Bansal. Earlier, he studied at Charles University in Prague with advisor Jiří Matoušek. His research focuses on algorithms for optimization under uncertainty , bridging online algorithms , differential privacy , and machine learning-augmented systems . Key areas include Learning-Augmented Algorithms Online Metric Algorithms Combinatorial Optimization Privacy-Preserving Mechanisms The trends in his recent publications highlight advancements in online optimization with applications in machine learning and data structures , particularly in problems like the k-server system , Steiner tree approximation , and differentially private clustering . Papers often explore the interplay between algorithmic robustness and predictive modeling to enhance efficiency in uncertain environments. He has contributed to major conferences including ICML, NeurIPS, SODA, and FOCS, with a consistent emphasis on theoretical guarantees and practical applications . While specific awards or grants are not detailed in the provided texts, his work is supported through institutional affiliations and collaborative research networks. Marek actively engages students in research, particularly in Bocconi's Theory Group , encouraging thesis projects on learning-augmented algorithms and prediction-based optimization . His laboratory environment fosters interdisciplinary collaboration between theoretical computer science and machine learning communities.

• Econometrics
• Computational Statistics
• Financial Risk Management
• +۵ مورد دیگر

Marco Bee is a Full Professor at the Department of Economics and Management, University of Trento. His expertise spans applied econometrics, computational statistics, finance, and risk modeling. He focuses on methodologies for handling heavy-tailed distributions, extreme value theory, and machine learning applications in financial risk assessment. Education details are available in his CV (CVeng.pdf). His research interests include developing statistical models for operational risk, volatility forecasting, and credit scoring, often employing mixture models, copula-based approaches, and indirect inference techniques. He has contributed significantly to the analysis of spatial econometrics and the application of extreme value theory to financial crises and insurance analytics. His recent work emphasizes tail risk estimation, with over 150 publications since 2006. Notable contributions include methodologies for Value-at-Risk (VaR) forecasting, distribution fitting for skewed data, and the use of machine learning to predict defaults in small businesses. His research bridges theoretical statistics and practical financial applications, with a focus on high-frequency data and scenario-based risk analysis. Awards and grants are not explicitly listed in the provided data, but his extensive publication record reflects recognition in quantitative finance and econometrics. He advises students on topics related to computational econometrics and risk modeling, though specific advisee names are not documented here.

• Number Theory
• Algebra
• Combinatorics
• +۳ مورد دیگر

Stefano Barbero is an Assistant Professor at the Department of Mathematics, University of Trento. His research focuses on Number Theory, Algebra, and Combinatorics with applications to p-adic analysis, linear recurrence sequences, and Diophantine approximation. He has contributed to studies on continued fractions in p-adic contexts and algebraic structures of sequences. His work frequently intersects with topics like divisibility sequences, Salem numbers, and combinatorial properties of algebraic structures such as Hurwitz series rings and binomial convolutions. He has collaborated extensively with researchers like Nadir Murru and Umberto Cerruti, producing influential papers in journals like Experimental Mathematics and Mathematics of Computation . Key research directions include exploring periodic representations of quadratic irrationals in p-adic fields, developing matrix-based approximation methods for algebraic irrationalities, and investigating connections between group theory and Pythagorean triples via conic geometries.

Giancarlo Bigiمشاهده پروفایل

دانشیار

• Operations Research
• Optimization
• Equilibrium Problems
• +۷ مورد دیگر

Giancarlo Bigi is an Associate Professor of Operations Research in the Department of Computer Science at the University of Pisa, Italy. He has been a faculty member since 2000, advancing from Assistant Professor to Associate Professor in 2017. He holds a Ph.D. in Mathematics from the University of Pisa and has achieved national habilitations for both full and associate professorship in Operations Research and Mathematical Methods of Economics. His research is centered on optimization and equilibrium problems, with a strong focus on variational inequalities, game theory, multiobjective optimization, and nonlinear programming. He develops theoretical frameworks and algorithmic solutions for complex equilibrium models, including applications in economics and energy markets. The recent publications highlight a consistent trend in developing and analyzing gap functions, descent algorithms, and penalization techniques for equilibrium and hierarchical programming problems. His work bridges theoretical optimization with practical applications, particularly in modeling oligopolistic markets and decentralized energy systems. Associate Professor, Department of Computer Science, University of Pisa (2017–present) Assistant Professor, Department of Computer Science, University of Pisa (2000–2017) Ph.D. in Mathematics, University of Pisa (1997–2003) Bigi has no explicitly listed scientific awards in the provided material. He has not published any acknowledgments of grants, but his sustained research output suggests ongoing funding support. He collaborates extensively with researchers such as Mauro Passacantando, Marco Castellani, and Massimo Pappalardo. He is affiliated with the Operations Research Group within the Department of Computer Science at the University of Pisa, contributing to a collaborative research environment focused on optimization and decision-making models.