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Hugo Georges Victor LavenantView profile

Assistant Professor

• Optimal Transport
• Calculus of Variations
• Convex Analysis
• +3 more

Hugo Georges Victor Lavenant serves as Assistant Professor in the Department of Decision Sciences at Bocconi University, Milan, where he has held a faculty position since 2020. Previously, he completed a postdoctoral fellowship at the University of British Columbia (2019-2020) under the Pacific Institute of Mathematical Sciences and earned his PhD in Mathematics from Université Paris-Sud (2016-2019) under Filippo Santambrogio's supervision. His academic foundation includes: PhD in Mathematics, Université Paris-Sud (2016-2019) Studies at École Normale Supérieure (2012-2016) covering mathematics, physics, history, and philosophy of science Classes préparatoires in mathematics and physics (2010-2012) Lavenant's research centers on optimal transport theory and its applications across mathematical disciplines. He investigates geometric structures in Wasserstein spaces, develops numerical methods for dynamical optimal transport, and bridges theoretical advances with Bayesian statistics. His work demonstrates particular innovation in trajectory inference for biological data and dependence measures for random measures, connecting pure mathematics with computational statistics. Recent publications reveal accelerating interdisciplinary impact, with 2024-2025 works extending optimal transport to machine learning (kernel methods, variational inference) and data science (opinion dynamics, single-cell analysis). This trajectory shows increasing methodological sophistication in handling measure-valued mappings and non-smooth geometries while maintaining computational tractability. Award recognition includes: Pacific Institute of Mathematical Sciences Postdoctoral Fellowship Lavenant actively mentors early-career researchers through formal advising relationships and collaborative projects. He currently supervises two PhD candidates (George Kanchaveli and Francesco Mascari, co-advised with Marta Catalano) and has guided Master's students including Mathis Hardion and Niccolò Bargellini. His teaching portfolio spans advanced analysis, optimization, and real analysis courses at Bocconi, reflecting his commitment to mathematical rigor in education. He operates within Bocconi's Decision Sciences ecosystem while maintaining international collaborations with researchers at UBC, Université Paris-Sud, and statistical groups worldwide. Current projects focus on entropy-based transport methods and geometric approaches to nonparametric statistics, positioning his work at the intersection of theoretical mathematics and data-driven applications.

Roberto Ghiselli RicciView profile

Professor

• Probability
• Mathematical Statistics
• Copula Theory
• +3 more

Roberto Ghiselli Ricci is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Informatics and Statistics. His academic career includes extensive teaching and research in mathematical statistics and probability, with a focus on copula theory, aggregation functions, and econometric applications. He currently teaches courses such as Calculus, Linear Algebra, and Mathematics for Environmental Sciences. His research explores advanced topics in probability theory, including copula properties, fixed-point theorems, and axiomatic characterizations of mobility measures. Recent publications highlight contributions to fuzzy set theory, optimization penalties, and financial securities modeling. His work bridges mathematical rigor with practical applications in economics and environmental policy analysis. Publications trends emphasize interdisciplinary approaches, with notable contributions to Fuzzy Sets and Systems , International Journal of Game Theory , and Social Choice and Welfare . He actively participates in academic activities through courses, research collaborations, and advisory roles within his department.

Maria Giuseppina BrunoView profile

Associate Professor

• Financial and Actuarial Mathematics
• Quantitative Methods for Economics, Finance and Insurance
• Valuation of Derivative Financial Instruments
• +7 more

Maria Giuseppina Bruno is an Associate Professor in the Department of Methods and Models for Economy, Territory, and Finance (MEMOTEF) at Sapienza University of Rome's Faculty of Economics. She has been serving in this capacity since December 29, 2003, specializing in the scientific disciplinary sector STAT-04/A (Mathematical Methods of Economics and Actuarial and Financial Sciences). Her institutional email is Giuseppina.Bruno@uniroma1.it and she maintains office hours at room 149 on the first floor, wing B of the MEMOTEF Department. Her academic background includes a PhD in 'Mathematics for Financial Market Analysis' from the University of Brescia (1995), where she defended her thesis 'Memory functions as a tool for evaluating American options,' and a first-class honors degree in Economics and Commerce from LUISS University of Rome (1990) with thesis 'Valuation of convertible bonds. An interpretation using physics models.' Professor Bruno's research spans financial and actuarial mathematics, quantitative methods for economics and finance, derivative instrument valuation, risk management models, stochastic processes, and computational methods. Her work demonstrates strong interdisciplinary connections between mathematics, finance, insurance, and even physics through her interest in econophysics and applications of physical models to financial problems. Her recent publications show a consistent focus on innovative insurance products, risk modeling, and financial engineering. From Tailor-made CDOs (2024) to Pay-as-you-drive insurance models (2023) and specialized insurance products like ALEA and MICROTAKAFUL (2021), her research addresses contemporary challenges in risk transfer mechanisms and insurance market dynamics. Her work on long-term care annuities (2020) and option pricing with stochastic volatility (2019) demonstrates expertise in both theoretical and practical aspects of financial mathematics. As a respected academic, she serves as Managing Editor of Annali MEMOTEF and referees for prestigious journals including Insurance: Mathematics and Economics. She has been actively involved in professional organizations including AMASES, AAI, and Istituto Italiano degli Attuari. Professor Bruno currently teaches Actuarial Mathematics for Private Insurance (Master's Degree in Finance and Insurance) and Basic Mathematics course (Bachelor's Degree in Economics and Finance). She has extensive experience in curriculum development, serving as reference teacher for the Master's Degree Course FINASS and as tutor for the Bachelor's Degree in Economics and Finance. Her institutional service includes membership on various committees related to quality assurance, publications, and doctoral programs. Her professional activities extend beyond academia, with participation in Bank of Italy examination boards (2016, 2019, 2023) and previous teaching roles for financial professionals at INPDAP and Banca di Roma. Her technical expertise includes programming in C++, VBA, and Python, which supports her computational research in financial mathematics.

• Statistics for Experimental and Technological Research
• Urban Mobility Analysis
• Sports Analytics
• +3 more

Rodolfo Metulini is a Researcher (RTD-B) in Statistics for Experimental and Technological Research (SECS-S/02) at the Department of Economics, University of Bergamo. He serves as Principal Investigator for the PRIN/PNRR project 'SIGNUM: Study of mobile phone signals for evaluating mobility-environment interconnections in Lombardy'. His career includes postdoctoral positions at the University of Brescia, Scuola Superiore Sant'Anna Pisa, and IMT Lucca. PhD in Statistical Methodology for Scientific Research (2013), University of Bologna Former Researcher at University of Salerno (RTD-A) Metulini's research spans three primary domains: travel flow analysis using gravity models and spatial interaction approaches for international trade studies; sports analytics focusing on player movement dynamics and marginal utility in football/basketball; and urban mobility modeling through mobile phone data with complex seasonality time series models. His methodological innovations combine matrix completion techniques with functional data clustering for environmental-socioeconomic applications. Recent research trends demonstrate cross-sectoral expertise in applying statistical learning to diverse domains: 1) environmental risk assessment using mobile network data for flood exposure forecasting; 2) urban policy analysis through counterfactual modeling of traffic restrictions; and 3) economic modeling for CO2 emissions prediction. His technical approach integrates dynamic harmonic regression with VARX models for mobility forecasting. As thesis advisor for Computer/Mechanical Engineering students, Metulini promotes data-driven approaches in mobility and sports domains. His publications in journals like Annals of Operations Research and Optimization Letters showcase interdisciplinary methodology combining statistical theory with practical applications in environmental risk management and sports performance analysis.

Sabrina GiordanoView profile

Associate Professor

• Categorical Data Analysis
• Longitudinal Data Analysis
• Copula Functions
• +7 more

Sabrina Giordano is Associate Professor of Statistics at the University of Calabria , where she teaches Statistics and Data Science courses in both Italian and English. She holds a PhD in Methodological Statistics from the University of Milano-Bicocca and has held visiting positions at RWTH Aachen University, University of Florida, and University of Plymouth. Her research focuses on Statistical modeling of categorical and ordinal data Latent variable models and copula functions Longitudinal analysis and hidden Markov chains Applications in finance, health, and environmental statistics Her methodological contributions are implemented in the hmmm R-package and supported by grants like the PRIN2022 project "SMILE: Statistical Modelling and Inference to Live the Environment". She serves as Associate Editor for Biometrical Journal and Statistical Methods & Applications Director of the Post-Graduate Master in Artificial Intelligence & Data Science Local coordinator for the COST Fin-AI research group Her recent collaborative work explores Dynamic response styles in longitudinal data Fairness-aware classification algorithms Copula-based dependence structures Applications to financial vulnerability and risk perception

Marta Nai RusconeView profile

Associate Professor

• Statistics
• Data Analysis
• Environmental Economics
• +3 more

Marta Nai Ruscone is an Associate Professor in the Department of Economics at the University of Genoa. She specializes in statistical methodologies, particularly focusing on copula models, data analysis, and their applications in environmental economics and econometrics. Her teaching responsibilities include courses such as Advanced Data Analytics, Statistical Forecasting, and Statistics for Business Economics. Her research emphasizes developing and applying copula-based techniques for clustering, dependence analysis, and modeling complex economic and environmental datasets. Key areas include studying the influence of economic sectors on financial markets, analyzing the dynamics of human development indicators, and exploring relationships between environmental factors and pandemic outcomes. She has also contributed to open-source statistical software like the R package OBsMD for Bayesian model discrimination. Dr. Nai Ruscone’s work bridges theoretical statistical advancements with practical applications, addressing challenges in multivariate analysis, ordinal data modeling, and interdisciplinary problem-solving. Her publications reflect a strong commitment to advancing methodologies in statistics and their relevance to real-world economic and environmental issues.

Moreno BevilacquaView profile

Associate Professor

• Spatial Statistics
• Covariance Modeling
• Geostatistics
• +3 more

Moreno Bevilacqua is an Associate Professor in the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari University of Venice. His research focuses on spatial statistics, covariance modeling, and geostatistical methods, with applications in environmental and multivariate analysis. He has contributed to advancing covariance functions, composite likelihood approaches, and spatial data modeling techniques. Recent publications emphasize statistical methodologies for spatial and spatiotemporal data, including extensions of the Matérn model, composite likelihood for massive datasets, and copula-based approaches for bounded support data. His work bridges theoretical advancements and practical applications in environmental science and statistical computing. No scientific awards or grants are explicitly mentioned in the provided texts. Teaching activities include courses in statistics for undergraduate programs in Business Economics, covering foundational and advanced statistical methods. Current office location: Assegnisti A1 office (Zeta A building, 1st floor), Campus via Torino.

• Mathematical Finance
• Probability Theory
• Statistics
• +7 more

Patrizia Semeraro is a Full Professor at the Department of Mathematical Sciences "GL Lagrange" (DISMA), Polytechnic University of Turin. She is a member of the Interdepartmental Center R3C - Responsible Risk Resilience Center and the Master's and Continuing Education School. Her research and teaching are centered in mathematical finance, probability, and statistics, with applications in financial modeling and risk analysis. Polytechnic University of Turin, Department of Mathematical Sciences (Current) Her primary research interests include mathematical finance, stochastic processes, multivariate modeling, and statistical methods in economics and finance. She focuses on advanced topics such as multivariate Lévy models, tempered stable processes, subordination, and high-dimensional Bernoulli distributions. Her work bridges theoretical probability with practical applications in credit risk, derivative pricing, and financial engineering. Recent publications demonstrate a strong trend in developing and calibrating multivariate financial models, analyzing dependence structures, and applying probabilistic methods to real-world economic problems. Her work spans journals in operations research, statistics, probability, and financial economics, reflecting interdisciplinary expertise. Scientific recognitions include: Outstanding paper awarded by Emerald Literati Network, Italy (2016) Fellow - INDAM, Italy (2019–present) Fellow - AMASES, Italy (2017–present) She supervises PhD students including Chen Zhang, Alessandro Mutti, and Giovanni Amici. She has been involved in nationally funded research projects such as PRIN and SUP-CHAIN-DIS (2023–2025), focusing on supply chain disruptions and financial losses. She teaches in the Financial Engineering program and has previously taught courses such as Complements of Mathematics and Fundamentals of Physics and Mathematical Principles. She is a member of the Probability and Applications research group and contributes to the Mathematical Models in Finance research area at DISMA.

• Statistics
• Distribution Theory
• Reliability Models
• +5 more

Filippo DOMMA is a Full Professor in Statistics (STAT-01/A) at the Department of Economics, Statistics, and Finance "Giovanni Anania" (DESF) at the University of Calabria. He serves as Manager of the Statistical Computer Laboratory and is an active member of the "Statistica & Demografia" research group. Professor DOMMA teaches advanced courses including Statistical Models and Statistical Learning for Data Science for Business Analytics and Computer Engineering programs, as well as Statistical Methods for Economics for the Economics, Business and Sustainability program. Professor DOMMA's research focuses on statistical methodology development with particular emphasis on distribution theory, reliability models, and applications in economic and demographic analysis. His work spans several key areas: construction and application of new distribution models for continuous and bounded support variables; analysis of relationships between variables of any nature; copula-based dependence modeling; survival analysis; and environmental data analysis. He has developed innovative approaches for constructing distribution classes through hazard function transformations and has made significant contributions to order statistics theory and stress-strength reliability models. His research methodology often involves creating specialized distributions that address limitations of existing models while maintaining mathematical tractability. His extensive publication record spanning over two decades demonstrates consistent theoretical contributions to distribution theory with diverse practical applications. DOMMA has pioneered specialized distributions including Unit-Dagum models and reflected Generalized Topp-Leone Power Series distributions. His work bridges theoretical statistics with applications in income inequality measurement, household financial fragility, environmental monitoring, and medical statistics. A distinctive pattern in his research is the development of distributional frameworks that precisely model real-world phenomena while providing analytical tractability for estimation and inference. As Manager of the Statistical Computer Laboratory, Professor DOMMA oversees research infrastructure supporting advanced statistical computing and methodological development. His laboratory serves as a hub for applying sophisticated statistical techniques to complex problems across multiple disciplines. He maintains extensive collaborative networks with researchers both nationally and internationally, particularly with Francesca Condino, Graziella Bonanno, and Lucia Errico on projects spanning economic inequality analysis, reliability modeling, and environmental statistics. His teaching portfolio reflects his research expertise, focusing on statistical learning models and advanced statistical methods for business and economic applications.

• Statistics
• Randomized Response Techniques
• Survey Sampling
• +5 more

Pier Francesco Perri is a Full Professor of Statistics (SSD STAT-01/A) at the Department of Economics, Statistics, and Finance 'Giovanni Anania' (DESF) of the University of Calabria (Unical). He has held academic positions since 2002 and coordinates institutional activities such as the National Plan for Scientific Degrees (L-41, Statistics) and editorial roles in journals like Metron and Model Assisted Statistics and Applications . His research focuses on survey methodology, sensitive data estimation, and statistical modeling. Education: Ph.D. in Methodological Statistics (University of Trento, 2002), Honors Degree in Statistical and Actuarial Sciences (University of Calabria, 1997) Perri’s research spans randomized response techniques for sensitive populations, copula modeling for financial data, and inequality index linearization. He explores indirect questioning methods to detect truthfulness and improve survey accuracy, particularly for stigmatized behaviors like abortion, migration, and non-heterosexual identities. His work integrates auxiliary information and complex sampling designs to enhance estimation efficiency. Recent publications emphasize innovations in sample survey traditions, including the 2025 editorial on methodological advancements and 2024 studies on adjusting self-protective behaviors in prevalence estimation. His 2023–2021 research includes logistic regression extensions for randomized response models, prevalence estimates for health behaviors, and crossed model applications for sensitive topics. Earlier work (2020–2000) covers item sum techniques, financial copula modeling, and environmental sensitivity analysis. He serves on editorial boards and institutional committees, including the Italian Statistical Society’s Council and the Ph.D. Teaching Board at Unical. The Laboratorio Statistico Informatico supports his research in statistical computing and survey design.

ANNALISA DI CLEMENTEView profile

Associate Professor

• Financial Risk Management
• Systemic Risk
• Sustainable Finance
• +5 more

Annalisa Di Clemente is a confirmed Associate Professor in "Economia degli Intermediari Finanziari" at the Department of Social and Economic Sciences (DISSE) , Sapienza University of Rome . She teaches Mercati e Intermediari Finanziari (L-33) and Policies and Management for Sustainable Finance (LM-56). Her academic career spans since 2000 with previous teaching roles in "Economia dei mercati monetari e finanziari" (2000-2012), "Economia e Gestione delle imprese" (2008-2012), and "Banca e Gestione del Rischio" (2013-2022). SSD: ECON-09/B Researcher in financial intermediation economics and corporate finance Director of the "Finance & Development: A New Finance for Global Growth" scientific series Research Interests focus on: Systemic risk measurement and management Bank capital allocation techniques Financial stability analysis Sustainable finance and ESG portfolio performance Copula-based risk modeling Macroprudential regulation Climate risk and financial asset valuation Recent Publications demonstrate expertise in: 2025: Financial System and Systemic Risk monograph 2024: Climate risk analysis and sustainable finance 2023: Credit risk modeling with copula approaches 2022: Pandemic crisis impact on markets 2021: Financial system resilience and sovereign risk Key Projects : 2024-2025: Academic Coordinator for LM-56 Master's program 2024: Member of DISSE Didactic Innovation Commission 2022: Academic Coordinator for Erasmus+ programs (L-33/LM-56) 2019: Co-director of PCTO project "Laboratorio di Diritto Europeo, dell'Economia e della Finanza"

Franco PellereyView profile

Professor

• Actuarial Sciences
• Dependence Notions and Orders
• Reliability Theory
• +6 more

Franco Pellerey is a Full Professor at the Department of Mathematical Sciences (DISMA) of the Polytechnic University of Turin. He serves as Coordinator of the College of Mathematical Engineering and is actively involved in teaching and research coordination activities. Co-organizer of the International School on Stochastic Comparisons (2004) Program Chair for the 14th International Conference on Ordered Statistical Data (2022) Scientific Coordinator for multiple national research projects (BRIC-2024, PRIN) Research Interests : Stochastic orders and their applications in risk theory Dependence notions and positive dependence concepts Reliability theory and actuarial sciences Stochastic processes in engineering contexts Applied statistics for technical systems Scientific Leadership : BRIC-2024 Acoustics Research (2025-2027) Supermodularity in Economic Theory (2002-2004) Continuous Financial Market Models (2001-2003) International Engagements : Full Professor at Turin Polytechnic University in Tashkent (2018-2021) Full Professor at ESCP Europe (2016-2018)

Irene CrimaldiView profile

Associate Professor

• Probability
• Statistics
• Economics
• +6 more

Irene Crimaldi is an Associate Professor of Statistics at IMT Lucca (Italy) since 2011. She serves on the Scientific Board of IMT's PhD programs . Her academic journey includes roles as a researcher and part-time professor at the University of Bologna (2006-2011) and a tenured assistant professor at IMT Lucca (2011-2014). Crimaldi holds a cum laude degree in Mathematics from the University of Pisa and a cum laude PhD in Financial Mathematics from the Scuola Normale Superiore (Pisa). She has received scholarships from Istituto Nazionale di Alta Matematica and fellowships from University of Pisa and University of Bologna . Her research focuses on Probability and Statistics with applications in Economics, Social Sciences, Computer Science, and Engineering . Key areas include interacting reinforced stochastic processes , network modeling , urn models , species sampling , and stable convergence . She has co-authored influential works on synchronization phenomena, systemic risk in OTC markets, and latent attribute network models. Crimaldi's peer-reviewed publications span 15 most recent articles (2013-2025) addressing synchronization rates, network dynamics, and systemic risk. These works employ stable convergence, central limit theorems, and reinforcement mechanisms, contributing to disciplines like stochastic processes, financial mathematics, and network science. She actively collaborates with institutions such as the University of Bologna , University of Pisa , and IMT Lucca , integrating mathematical rigor with real-world applications in financial systems and social networks.

• Econometrics
• Computational Statistics
• Financial Risk Management
• +5 more

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.

Valeria D'AmatoView profile

Associate Professor

• Actuarial Science
• Risk Management
• Machine Learning
• +7 more

Valeria D'Amato is an Associate Professor at the Department of Methods and Models for Economy, Territory, and Finance of Sapienza University of Rome . Her academic work focuses on actuarial science, risk management, and statistical modeling. Fields of Interest : Actuarial Science, Risk Management, Machine Learning, Climate Risk, Financial Mathematics, Demographic Economics Email : valeria.damato@uniroma1.it Recent research highlights include: Developing machine learning models to assess climate risk sharing in tourism insurance and ESG score prediction. Analyzing frailty-based mortality models for longevity risk reserving and pandemic-related mortality shocks. Investigating cyber risk dependence using vine copula frameworks and geospatial pricing strategies. Her publications span journals like Frontiers in Applied Mathematics and Statistics , Applied Stochastic Models in Business and Industry , and Risks , reflecting interdisciplinary approaches to modern risk assessment challenges.