جستجوی استاد راهنمای دانشگاهی

Fabio Peroccoمشاهده پروفایل

دانشیار

• Migration Studies
• Sociology
• Social Inequality
• +۴ مورد دیگر

Fabio Perocco is an Associate Professor at the Department of Philosophy and Cultural Heritage at Ca' Foscari University of Venice. His work focuses on migration, social inequality, racism, and labor precarity. He has conducted extensive research on racialized welfare discourses, migrant labor conditions, and Islamophobia in Europe. Key research interests include the intersection of migration and social policy, structural violence against migrants, and the precarization of labor in the digital economy. His studies often highlight systemic discrimination within welfare systems and analyze the socioeconomic impact of migration policies. Recent publications examine topics such as the racialized discourse on social welfare, gig economy labor dynamics, and the structural roots of torture against migrants. He is affiliated with the Research Institute for Social Innovation, contributing to projects addressing territorial inequalities and global migration challenges.

Stefano CAMPOSTRINIمشاهده پروفایل

استاد

• Social Statistics
• Public Health
• Healthcare Systems
• +۶ مورد دیگر

Stefano CAMPOSTRINI is a Full Professor in the Department of Economics at Ca' Foscari University of Venice, specializing in Social Statistics (STAT-03/B). He serves as a Member of the technical-scientific Committee of the Ca' Foscari Challenge School and the Department of Economics' Committee. His research activities are supported by affiliations with the Research Institute for Social Innovation and the Research Institute for Innovation Management. Professor CAMPOSTRINI's research spans the intersection of statistical methodology, public health, and social policy. His work demonstrates expertise in advanced statistical techniques including Bayesian modeling, spatial analysis, and complex survey methodology. His primary focus areas include healthcare systems analysis, social innovation, public administration, and the economic aspects of health policy. He frequently addresses issues related to comorbidity patterns, healthcare service accessibility, and the application of artificial intelligence in healthcare settings. His publication record from 2021-2025 reveals significant trends in healthcare innovation, with particular emphasis on virtual hospital systems, AI applications in medicine, sustainable healthcare practices, and the statistical analysis of social services like early childhood education. His methodological contributions include novel approaches to analyzing regional health disparities and developing web-based tools for disease prevalence estimation. His research often employs expert consensus methods like Delphi techniques to address complex healthcare organizational challenges. Professor CAMPOSTRINI maintains active involvement in research initiatives through the Research Institute for Social Innovation and the Research Institute for Innovation Management. His work bridges advanced statistical methodology with practical applications in healthcare policy and social service delivery, making significant contributions to evidence-based decision making in public health and social policy domains across Italy and European contexts.

Gaby Umbachمشاهده پروفایل

مدرس پاره‌وقت

• Global governance
• EU governance and Europeanisation
• Evidence-based policy-making
• +۸ مورد دیگر

Gaby Umbach is a Part-time Professor and Founding Director of GlobalStat at the European University Institute's Robert Schuman Centre for Advanced Studies . She serves as a non-resident Visiting Fellow for the European Parliament, Adjunct Professor at the Universities of Cologne and Innsbruck, and Board member of the Institute for European Politics Berlin. Her research focuses on knowledge-evidence-data interactions in governance, analyzing measuring/statistics as governance techniques , data literacy in policy-making, and transformations of politics through multilevel/anticipatory governance and sustainable development . She designed the GlobalStat database, linking it to the European Parliamentary Research Service and OECD. Scientific awards: Stiftung Demokratie Best PhD Thesis Award (2009) Key article trends include: global governance frameworks, data-driven EU policy innovations, open science impacts, and strategic foresight mechanisms. Her 2023-2024 publications emphasize economic indicators in international trade, policy evaluation methodologies, and database design for global governance.

• Public Contract Law
• Administrative Liability
• Constitutional Principles
• +۴ مورد دیگر

Alessandra Amore is a permanent faculty member at the University of Palermo's Department of Law , holding the academic rank of Researcher (GIUR-06/A). Her research focuses on public contract law, administrative liability, constitutional principles, and anti-mafia legislation. She maintains regular office hours and can be contacted via email at alessandra.amore@unipa.it. Research Interests Amore's work explores the intersection of administrative law with contemporary governance challenges, including: Public contract law anomalies and jurisdictional review Administrative liability for lawful acts Anti-mafia interdiction legal frameworks PNRR implementation in socio-health sectors Privacy vs. transparency in judicial proceedings Human dignity in vaccination-related liability Publications Trends Her publications (2017–2024) reflect deep engagement with Italian administrative law, particularly: Evolution of public procurement regulations Balancing constitutional principles in anti-mafia enforcement State responsibility in health policy Interplay between administrative discretion and judicial review Human rights protection in migration governance Procedural autonomy in EU contexts

• Survey Methodology
• Economic Statistics
• Big Data Analysis
• +۳ مورد دیگر

Daniele Toninelli is an Associate Professor of Economic Statistics (SECS-S/03) at the University of Bergamo's Department of Economics, where he also serves as Director of the 'Data Analyst for Strategic Decisions' program, Internship Manager for the department, and member of the School of Economics and Management's Joint Teacher-Student Commission. His educational background includes a PhD in Marketing for Business Strategies (University of Bergamo, 2009), Master's in Statistics for Market Research (University of Milan-Bicocca, 2004), and Degree in Statistical and Economic Sciences (University of Milan-Bicocca, 2003). Toninelli's research focuses on: Survey and web survey methodology design and optimization Integration of big data for economic and social indicators Development of price indexes and composite indicators Social media analytics for economic measurement His work bridges statistical theory with applications in labor markets, sustainability metrics, and environmental data analysis. Teaching activities encompass undergraduate and graduate courses including Economic Statistics, Quantitative Methods for Business Data Analysis, Advanced Business Statistics, and specialized 'Data Skills' modules covering visualization, survey methods, and SAS certification preparation. International research collaborations include visiting positions at Statistics Canada (2008-2013), University of Ottawa (2012-2013), VŠB-Technical University of Ostrava (2012-2013), RECSM at Universitat Pompeu Fabra (2014), and guest lectures at University of Ljubljana (2018). He previously served on the management committee of the WEBDATANET network (COST Action IS1004). Professional experience includes roles at PiTre Milan, IBM Semea/Celestica, and Multiplex Arcadia, applying statistical expertise in industrial settings.

Giorgia Mariniمشاهده پروفایل

استادیار

• Health economics
• Policy impact evaluation
• Performance evaluation
• +۶ مورد دیگر

Giorgia Marini is an Assistant Professor of Public Economics at the Department of Legal and Economic Studies (DSGE) at Sapienza University of Rome. She holds National Scientific Qualifications for Associate Professor positions in both Public Economics (valid 2025-2037) and Economic Policy (valid 2025-2037). Dr. Marini earned her PhD in Economics from the University of Rome Tor Vergata in 2005, following an MSc in Econometrics and Economics from the same institution in 2001 and a BA in Economics from Sapienza University of Rome in 2000. Her academic journey includes research positions at the Centre for Health Economics at the University of York and visiting scholar positions at Stanford University and Imperial College London. Her extensive research focuses on health economics, policy impact evaluation, performance measurement, digital health, hospital mergers, and migration economics. Recent work examines institutional impacts on health status, hospital merger effects, environmental crime consequences, and the economic dimensions of migration in Italy. Her publications appear in leading journals including Health Economics, European Journal of Health Economics, and International Journal of Computational Economics and Econometrics. Dr. Marini has secured multiple research grants, including a €224,338 PRIN 2022 grant on migration and religion. She serves on the Executive Council of the Italian Association of Health Economics (AIES) and co-founded the Economics of Digital Health Technology Special Interest Group within the International Health Economics Association. She actively supervises PhD, Master's, and undergraduate students, with numerous BA students listed from 2014-2024. Her teaching includes undergraduate courses in Regulatory Impact Analysis, Public Policy Analysis, and Public Economics. Dr. Marini also serves on various university committees including the Departmental Board and Faculty Board.

• Group dynamics
• Inclusion and diversity management
• Industrial and organizational psychology
• +۱۱ مورد دیگر

Filip Agneessens serves as a Teaching Fellow in the Department of Sociology and Social Research at the University of Trento, Italy, with contact details including office location at Via Verdi, 26 - 38122 Trento and email filip.agneessens@unitn.it. His academic role focuses on advancing social network methodologies within sociological and organizational contexts. His research expertise encompasses Group dynamics, Social network analysis, Organizational behavior, and Diversity management, with particular emphasis on negative ties in networks, ethnic diversity effects, and methodological innovations for workplace network studies. This interdisciplinary focus bridges sociology, psychology, and organizational science to examine how network structures shape group processes and individual outcomes. Agneessens' recent publications reveal consistent scholarly contributions in social network analysis across domains including education (e.g., bullying dynamics in schools), public administration (governance networks), and organizational behavior (workplace conflict). His work demonstrates methodological leadership through the 2022 book Analyzing Social Networks Using R and empirical studies applying longitudinal and multilevel network approaches to real-world group phenomena.

• Work Psychology
• Wearable Technology
• Sleep Health
• +۴ مورد دیگر

Luca Menghini is an Assistant Professor at the University of Padova, specializing in occupational health psychology, wearable technology applications, and work-related stress. His research focuses on leveraging digital tools such as wearable devices and mobile sensors to study sleep patterns, workplace behavior, and psychosocial risk factors. Key areas include workaholism impacts, healthcare worker well-being, and the validation of new technologies for health monitoring. His research interests span the intersection of technology and psychology, particularly in: Wearable sensor validation for sleep and physiological monitoring Workplace stress and its physiological correlates (e.g., blood pressure, emotional exhaustion) Multilevel analyses of healthcare environments Experience sampling methodologies for real-time psychological assessment Recent work emphasizes standardized evaluation frameworks for sleep-tracking devices and explores how emerging technologies like VR controllers can integrate physiological sensing. His studies often address contemporary challenges such as digital transformation's mental health implications and menopause management in workplaces. Publications consistently highlight innovative applications of data science in occupational health, with a focus on actionable insights for improving worker well-being through validated technological solutions.

• Financial Risk Management
• Quantitative Finance
• Econometrics
• +۴ مورد دیگر

Arturo Leccadito serves as Associate Professor in the Department of Economics, Statistics and Finance (DESF) at the University of Calabria, where he has held academic positions since 2009. His current role builds on prior experience as Assistant Professor (2009-2018) and multiple visiting appointments at Cass Business School in London. As Course Director for the Master Programme in Finance and Insurance (2020-2023), he oversees advanced financial education while maintaining active research and teaching responsibilities in Financial Econometrics and Risk Management courses. Ph.D. in Computational Methods for Financial and Economic Forecasting (University of Bergamo, 2008) Marie Curie Fellow at Cass Business School (2005) Degree in Statistics and Actuarial Science (University of Calabria, 2004; 110/110 cum Laude) Leccadito's research focuses on quantitative financial modeling with specialization in risk management frameworks, commodity market dynamics, and cryptocurrency forecasting methodologies. His work integrates advanced econometric techniques with practical financial applications, particularly in covariance matrix estimation, tail risk prediction, and derivative pricing. Recent publications demonstrate increasing emphasis on sustainable finance applications including green bonds and energy markets. Analysis of his 15 most recent publications reveals strong methodological consistency in nonlinear time series modeling and extreme value theory , with expanding applications from traditional commodities to digital assets. The research portfolio shows progressive complexity from early binomial tree models to current wavelet-based geopolitical risk analysis, maintaining focus on practical risk management solutions. As member of the Metodi quantitativi per l'economia, la finanza ed il management research group, Leccadito collaborates on developing quantitative models for decision-making across finance, actuarial science, and industrial economics. His teaching portfolio spans undergraduate Probability and Financial Mathematics courses to graduate-level Financial Risk Management instruction in English.

• Machine learning
• Numerical analysis
• Numerical methods
• +۱۰ مورد دیگر

Sandra Pieraccini is a Full Professor in the Department of Mathematical Sciences "GL Lagrange" (DISMA) at the Politecnico di Torino, where she also serves as Deputy Director of the department, Contact Person for student orientation, and Coordinator of the basic subjects for first-year engineering programs. She is a member of the University Open Access Commission and actively contributes to academic governance. Her research interests include machine learning, numerical analysis, scientific computing, uncertainty quantification, and numerical optimization . She is a key member of the research group Numerical Analysis and Scientific Computing and leads the national research project FaReX (2023–2025) on reduced-order modeling and automatic learning. Her work integrates advanced numerical methods with AI techniques, particularly in modeling discrete fracture networks and fluid dynamics. The most recent publications reflect a strong trend in combining graph-informed neural networks , explainable AI , and meshless computational methods to solve complex problems in geophysics, fluid mechanics, and data science. Her research bridges applied mathematics with real-world engineering and environmental challenges. She is an active member of the scientific community, serving on the editorial boards of Journal of Machine Learning for Modeling and Computing and GEM , and participating in steering committees of UMI groups on AI and machine learning. She has also contributed to organizing major workshops and conferences. Sandra Pieraccini teaches across multiple programs, including doctoral courses in Mathematical Sciences and Aerospace Engineering, master’s courses in Mathematical Engineering and Data Science, and bachelor’s courses such as Linear Algebra and Problem Solving Lab. She is deeply involved in curriculum development and academic leadership.

• Multivariate Statistics
• Data Analysis
• Clustering Algorithms
• +۴ مورد دیگر

Laura Bocci has been an Associate Professor of Statistics at Sapienza University of Rome since 2022. Previously, she worked as a researcher at Sapienza University from 1998–2000 in the Department of Communication and Social Research, later moving to the Department of Social and Economic Sciences in 2020. She earned her PhD in Methodological Statistics (XII Cycle, 2000) from Sapienza University, where she also graduated with honors in Statistical and Economic Sciences. Current Department: Department of Social and Economic Sciences Faculty: Faculty of Political Science, Sociology, Communication Office Location: Room 107, Building CU002 (Political Sciences), Sapienza University Campus Teaching: Statistics (A-K) and Data Science for Social Research Her research focuses on Multivariate Statistics , Data Analysis , and Statistical Methods with applications in social sciences, economics, and data clustering. She has developed novel techniques in dimensional reduction , model-based clustering , unsupervised classification , multidimensional scaling , and genetic algorithms . Her work often addresses complex data structures , including three-way data and multilevel models. Publications highlight trends in regional competitiveness , well-being analysis , clustering methodologies , and genetic algorithm applications . Key subfields include three-way data analysis , spatial clustering , and categorical variable optimization . Office hours are held Tuesdays 14:00–16:00 in person or via Google Meet (by appointment). She teaches courses in Statistics and Data Science for Social Research using Sapienza’s e-learning platform.

• gender inequality
• European values
• transformations in the world of work
• +۳ مورد دیگر

Vera Lomazzi is an Associate Professor of Sociology at the Department of Management, University of Bergamo. She holds leadership roles in the Center on Economic, Social and Cooperative Dynamics (CESC) and Center for Teaching Quality, Innovation and Learning (CQIIA). President of the European Survey Research Association Secretary of the Executive Committee of the European Values Study Member of OECD Global Technical Advisory Group on masculinities Her research focuses on: Comparative analysis of European values Evolution of gender role attitudes Workplace transformation and labor values Survey methodology and cross-national data harmonization Current projects include: PoweR - Promoting inclusive companies (Coordinator) MEN4DEM - Masculinity and European democracy (Work Package Leader) Missione Bergamo - Sociological investigation (Co-coordinator) European Values Study Wave 6 (Co-coordinator) Her recent publications address immigration attitudes, gender inequality measurement, work values transformation, and survey methodological challenges across European countries. Key scientific contributions: Measurement invariance testing in cross-national surveys Gender role attitude polarization analysis Pandemic impact on work-life balance Conceptualization of solidarity in European contexts

• Economic Policy
• Data Analysis
• Longitudinal Analysis
• +۱۱ مورد دیگر

Luca Piccoli is an Associate Professor at the University of Trento , affiliated with the Department of Sociology and Social Research . His expertise spans economic policy, quantitative methods, and welfare economics. Research Focus: Data Analysis Gender Inequalities Behavioral Economics Welfare Regimes Labor Market Dynamics Teaching: Political Economy (tools for economic analysis) Welfare & Labor Economics (welfare regimes, labor market mechanisms) Methodological Skills: Multivariate Statistical Analysis Causal Inference Structural Modeling Measurement Error Correction

Roberto Di Mariمشاهده پروفایل

استادیار

• Model-Based Clustering
• Finite Mixture Models
• Latent Variable Models
• +۴ مورد دیگر

Roberto Di Mari is an Assistant Professor at the Department of Economics and Business , University of Catania, Italy. His research focuses on advanced statistical methodologies, particularly model-based clustering, finite mixture models, latent variable models, and latent Markov models. He holds a Ph.D. in Economics and Finance from the University of Rome Tor Vergata (2017) and has conducted research at Tilburg University (Netherlands) as a visiting scholar. Education: Ph.D. in Economics and Finance (2017), University of Rome Tor Vergata M.Sc. in Economics (2013), University of Rome Tor Vergata Bachelor's Degree in Economics (2011), University of Catania Erasmus Exchange, University of Lille 1 (France), 2009–2010 Research Interests: Di Mari specializes in developing and applying statistical models to analyze complex data structures. His work bridges methodological advancements in latent variable modeling (e.g., mixture models, latent Markov approaches) with applications in economics, business, and social sciences. Key themes include robustness in modeling outlier risk, multilevel latent class analysis, and measurement invariance across longitudinal studies. Publications: His research emphasizes methodological contributions to latent variable modeling, including advancements in bias correction, R package development (e.g., multilevLCA ), and applications to high-frequency financial data and SME risk assessment. His work is published in journals like Journal of Econometrics , Structural Equation Modeling , and International Journal of Approximate Reasoning . Grants & Collaborations: Di Mari’s academic trajectory includes collaborations with Tilburg University and the Einaudi Institute for Economics and Finance. His research often integrates computational tools (e.g., LASSO penalization, dynamic mixtures) to address real-world challenges in data analysis.

• Machine Learning
• Non-parametric Methods
• Applied Statistics
• +۳ مورد دیگر

Simone Borra is an Associate Professor at the University of Rome Tor Vergata, specializing in Statistics (SECS-S/01). He teaches courses in Big Data Analytics, Business Analytics, and Statistical Methods for Management at both bachelor's and master's levels. His research focuses on machine learning, non-parametric methods, and applied statistics, with applications in public administration evaluation, environmental science, and management consulting. Current courses: BIG DATA ANALYTICS, BUSINESS ANALYTICS, METODI STATISTICI PER IL MANAGEMENT Office hours: Thursdays 14:00-15:30 in Room P3 SB5 Contact: borra@economia.uniroma2.it His research interests include statistical methodologies for economic and social sciences, data mining, and the application of neural networks. He has published extensively on topics such as credit scoring models, survey methodology, and remote sensing for environmental monitoring. Recent work includes analyses of solar power plant detection using Sentinel data and studies on management consulting trends in Italy. Notable contributions span academic publications in computational statistics, multilevel modeling, and the evaluation of public administration contracts. His work bridges theoretical statistical methods with practical applications in business, environmental science, and public policy.