Antonio Pietrabissa is an Associate Professor at the Department of Computer, Control, and Management Engineering “Antonio Ruberti” (DIAG) of the University of Rome Sapienza, where he earned his degree in Electronics Engineering (2000) and PhD in Systems Engineering (2004). He has been teaching Automatic Control and Process Automation since 2010 and holds the National Scientific Qualification as Full Professor in Systems and Control Engineering (09/G1). Research interests include networked systems, robust control, Markov decision processes, and deep reinforcement learning. His work spans telecommunications, biomedical applications, and space systems, with a focus on federated learning and decentralized control. He has authored ~70 journal papers (Scopus h-index 22) and co-invented a patent for model predictive control in motor disability assistance. Awards include the 2021 Cybersecurity Award and ETRI Journal Best Paper. Current projects are NANCY (6G networks) and CADUCEO (AI-driven medical diagnostics). He is also CEO of Sapienza startup Automation Intelligence and Control (AICO), commercializing AI solutions for space, telecom, and biomedical sectors.
Angela Andreella is an Assistant Professor in the Department of Economics and Management at the University of Trento. She holds a Ph.D., M.Sc., and B.Sc. in Statistics from the University of Padova. Her prior roles include Assistant Professor at Ca' Foscari University of Venice (2022–2024) and postdoctoral positions at the Universities of Padova and Insubria. Research Interests: Her work spans multivariate analysis, selective inference, social statistics, and permutation tests, with applications in biostatistics, neuroscience, and data analytics. She specializes in high-dimensional data, robust statistical methods, and quantitative approaches to social and medical research. Professional Memberships: Italian Statistical Society Italian Society of Biometry International Society of Biometry International Organization for Human Brain Mapping Institute of Mathematical Statistics Italian Association of Psychology
Donato Posa is a Full Professor in Statistics at the Department of Economic Sciences, University of Salento. He holds the academic position of Professor Ordinario (Full Professor) in the field of Statistics (SECS-S/01) and is actively engaged in research and academic leadership. His work bridges economics, environmental science, and advanced statistical modeling. University: University of Salento Department: Department of Economic Sciences Academic Rank: Professor Email: donato.posa@unisalento.it Office: Centro Ecotekne Pal. C, S.P. 6, Lecce - Monteroni, LECCE (LE) Phone: +39 0832 29 8737 Donato Posa earned his degree in Physics, cum laude, from the University of Bari with a thesis conducted at CERN, Geneva, and completed a specialization in Physics. His international academic experience includes extended research stays at Stanford University (USA), the University of Arizona, and the University of North Carolina. His research focuses on spatial and spatio-temporal statistics, with major contributions in geostatistics, multivariate geostatistics, stochastic simulation, and time series analysis. He has developed theoretical and applied models for environmental monitoring, pollution assessment, and socioeconomic data analysis. His work has been applied in risk mapping, environmental policy, and urban planning. The 15 most recent articles reflect a consistent trend in spatio-temporal modeling and geostatistical innovation. They span theoretical developments in covariance modeling and variogram analysis to practical applications in environmental monitoring, pollution dispersion, and ecosystem well-being. The research demonstrates a strong interdisciplinary focus, integrating statistical theory with environmental, economic, and computational sciences. His scientific recognition includes multiple CNR and NATO research grants, CERN awards, and an International Diploma of Honour from the American Biographical Institute for contributions to geostatistics. He has served on editorial boards, chaired international conferences (e.g., GeoEnv 2012), and participated in national scientific qualification committees. Posa has supervised numerous research projects funded by CNR, MIUR, Fondazione Caripuglia, and EU programs. He has acted as a scientific referee for leading journals such as Stochastic Environmental Research and Risk Assessment and Computational Statistics and Data Analysis . He has also led educational initiatives in statistical methods and GIS for environmental and cultural heritage applications. He has been actively involved in academic governance, serving as President of the Research Observatory at the University of Salento (2013–2017) and as a member of national evaluation committees. He has chaired international conferences and contributed to major scientific associations including the Bernoulli Society, the International Association for Statistical Computing, and the American Statistical Association.
Maurizio Galetto serves as Full Professor and Director of the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin. He holds multiple leadership positions including membership in the Academic Senate, Regulations Commission, and University Committee for Research, Technology Transfer and Services to the Territory. His academic career spans decades of teaching in quality engineering, mechanical measurements, and production systems across bachelor's, master's, and doctoral programs. Professor Galetto's research focuses on industrial metrology, instrumented indentation testing, performance measurement systems, quality engineering, and technological surface characterization. His work bridges theoretical metrology with practical industrial applications, particularly in manufacturing technologies and systems. His research intersects with key Sustainable Development Goals including Quality Education, Industry Innovation, and Responsible Consumption and Production. His publication record from 2023-2025 reveals strong emphasis on surface characterization techniques, quality control systems in manufacturing, collaborative robotics applications, and sustainable production methods. The research demonstrates consistent application of metrology principles to solve real-world industrial problems across diverse sectors including automotive, electronics, food processing, and additive manufacturing. Professor Galetto actively supervises PhD students working on quality engineering applications, with current research focusing on sustainable agri-food processes, collaborative robotics in quality control, and digital traceability systems. His research group has secured significant funding through competitive tenders, EU projects, and commercial contracts with major industrial partners including Electrolux and Lavazza. His laboratory work centers around the Quality Engineering research group (DIGEP), with special focus on metrology systems, surface characterization, and quality control methodologies. The research integrates advanced measurement techniques with statistical process control and digital twin technologies for enhanced manufacturing quality assurance.
Emanuele Taufer is a Full Professor of Statistics at the Department of Economics and Management of the University of Trento. His academic career includes roles as Vice Director of the Department of Computer Science and Business Studies and Faculty Delegate for International Relations. He holds a Ph.D. in Statistics from Cardiff University, an M.Sc. in Mathematical Statistics from George Washington University, and a Laurea in Economics from the University of Trento. His research focuses on statistical inference, stochastic processes, goodness-of-fit tests, and applications in ESG analysis. Notable contributions include work on exponentiality testing, graphical models, and financial dependence modeling. He has been recognized for his 2002 paper on mean residual life characterization at the SIS2002 conference. Recent research trends emphasize methodological advancements in ESG performance measurement, sparse network estimation for heavy-tailed data, and generalized precision matrices for financial risk modeling. His work spans theoretical statistics, applied econometrics, and interdisciplinary topics like environmental governance. Education: Ph.D. in Statistics, Cardiff University (UK) M.Sc. in Mathematical Statistics, George Washington University (USA) Laurea in Economics, University of Trento (Italy) Professional Roles: Full Professor of Statistics at University of Trento (2003–present) Associate Professor (2003–2003), Assistant Professor (1996–2002) Awards: 2002 SIS2002 Recognition for innovative statistical testing methodology Key Research Themes: Stochastic processes and estimation ESG methodology and financial reporting High-dimensional data analysis Goodness-of-fit tests and tail index estimation
Aldo Solari is a Full Professor at the Department of Economics of Ca' Foscari University of Venice. His research focuses on statistical inference, conformal prediction, and biostatistics, with applications in genomics, medical decision-making, and neuroscience. He teaches courses in statistics for economics, probability, and data science. Recent publications include advancements in false discovery rate control and hybrid human-AI collaboration in medical diagnostics. Solari co-edits the Proceedings of Machine Learning Research (PMLR) and serves as a referee for the US-Israel Binational Science Foundation. His work integrates theoretical developments with practical software tools for statistical analysis. Teaching: STATISTICA, INTRODUCTION TO PROBABILITY FOR ECONOMICS, DATA ANALYTICS FOR BUSINESS AND SOCIETY Research Themes: Multiple Testing, Conformal Prediction, Biomedical Applications, Neuroimaging Analysis Publications span peer-reviewed journals like Biometrika and Journal of the Royal Statistical Society , emphasizing methodological contributions with real-world impact. Solari’s projects include funding from Italy-Israel collaborations on high-dimensional inference in neuroscience and genomics.
Antonio Cicone is a Professor of Numerical Analysis at the University of L'Aquila, Italy. He holds the position of Research Associate at the Istituto di Astrofisica e Planetologia Spaziali (INAF) and Istituto Nazionale di Geofisica e Vulcanologia (Rome). His research focuses on signal processing, numerical linear algebra, and their applications in geophysics, astrophysics, medicine, and economics. He leads projects funded by the Italian Ministry and coordinates international initiatives like the MaSAG and NoSAG summer schools. He serves as an editor for journals such as Applied and Computational Harmonic Analysis and Frontiers in Applied Mathematics. His work includes developing algorithms like Fast Iterative Filtering (FIF) and the IMFogram for nonstationary signal analysis. Key collaborations involve universities and institutions worldwide, addressing challenges in plasma dynamics, GNSS signals, and cultural heritage preservation. Education: Holds an Abilitazione Scientifica Nazionale (ASN) for Full Professor in Numerical Analysis (2023) and Associate Professor (2020). Member of the Ph.D. program in Computer Science and Mathematics at the University of Insubria. Extensive teaching in signal processing and numerical analysis. Research Interests: Signal decomposition, time-frequency analysis, applications in geophysics/astrophysics, circular economy through signal processing, and interdisciplinary collaborations. His methods are applied to biomedical signals, optical fringe patterns, and environmental data analysis. Grants & Leadership: PI of the PRIN PNRR 2023 project on circular economy. Organized multiple international conferences and summer schools. Editorships and advisory roles in academic journals highlight his leadership in computational mathematics and signal processing. Labs/Teams: Involved with the Mathematics for Signal Processing group at the University of L'Aquila and collaborates with global institutions like Duke University and Georgia Tech.
Carlo Orsi is an Assistant Professor in Statistics at IMT School for Advanced Studies Lucca since November 2023. He holds a Ph.D. in Statistics (2014) from the University of Milan-Bicocca, preceded by a Master's (2011) and Bachelor's (2005) in Statistics from the same institution. Education: Bachelor's in Statistics, University of Milan-Bicocca (2005) Master's in Biostatistics & Experimental Statistics, University of Milan-Bicocca (2011) Ph.D. in Statistics, University of Milan-Bicocca (2014) His research focuses on non-central probability distributions over the unit simplex, multi-output Gaussian process regression, change point analysis, and applied statistics in tourism, medicine, and engineering. He has held adjunct professor roles at multiple universities, including teaching Mathematical Analysis and Probability, and served as a research collaborator at institutions like the National Research Council. His recent publications explore theoretical advancements in non-central distributions, with implications for statistical computation and simulation. He has held diverse roles in academia and industry, including statistical work at pharmaceutical and market research firms, and organizational roles like membership in the Local Organizing Committee for an international statistical conference (2008).
Carlo Gaetan is a Full Professor at the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari University of Venice. His research focuses on statistical modeling for environmental applications, including extremes in climate data, spatial-temporal analysis, and environmental risk assessment. He contributes to editorial roles, such as Associate Editor of the Journal of the Royal Statistical Society, Series C. His work spans environmental statistics, spatial modeling, and applications in climate change and health. Gaetan is actively involved in projects like the Venice 2021 climate scenario initiative and collaborates on studies assessing air pollution impacts and disease modeling. His teaching includes office hours for students, emphasizing accessibility and academic guidance.
Cristiano Varin is a Full Professor in Statistics at the Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Computer Science and Statistics (DAIS). He works at the Scientific Campus in via Torino and maintains the DAIS website for research and teaching updates. His research focuses on: Composite likelihood inference - A key methodological contributor with seminal papers in Biometrika and Statistica Sinica Copula regression - With practical implementations in R software Meta-analysis - Including improved likelihood inference techniques Spatial statistics - With applications to environmental data Paired comparison modeling - Applied to sports analytics and behavioral studies Recent publications demonstrate expertise in crossed random effects models (2025), ridge regression for paired comparisons (2024), and thermal comfort range analysis (2023). Scientific recognition includes: Royal Statistical Society Read Paper (2015) on journal citation modeling Gumbel Lecture (2006) by German Statistical Society Ca' Foscari Teaching Award (2020) He has collaborated with institutions including: Swiss National Science Foundation Natural Sciences and Engineering Research Council of Canada Norwegian Council of Research
Janna Smirnova is Assistant Professor in Economic Policy (SECS-P/02) at the University of Calabria , Department of Economics, Statistics and Finance. She earned her PhD in Firm, State and Market from the same university, preceded by a Master of Arts in Economics from University College Dublin and earlier degrees from the National Research University of Electronic Technology (MIET, Russia). Since 2011 she has taught macroeconomics, growth theory and international economics across Bachelor, Master and PhD curricula and since 2017 has served as Delegate for Internationalization and President of the International Relations Committee of her department. Research Interests Environmental and resource economics, circular economy and renewable energy policies Institutional development, rule of law and governance quality Gender economics and women’s leadership effects on firm productivity Education economics and long-run impacts of remedial programs Foreign direct investment, innovation diffusion and firm efficiency Her empirical work combines panel econometric techniques with large firm-level and cross-national datasets to evaluate policy effectiveness, environmental regulation and the interplay between institutions and economic outcomes. Research Projects & Funding Scientific Coordinator, University of Calabria Local Unit – GPS Education – Green & Pink for Sustainable Education (PNRR-TNE, 2024-2026) Member, CERERE agri-food supply-chain resilience project (PRIMA, 2024-2026) Member, Institutional Systems and Hospital Performance (PRIN-PNRR 2022, 2023-2025) Member, Ecosystems of Innovation – Tech4You PNRR Mission 4 (2023-2025) Coordinator, Erasmus+ KA171 & KA107 programs with Vietnam, Russia, Czech Republic and Slovakia (2014-2027) Editorial & Peer-Review Service Editorial board member, Modern Economy (SCIRP) and Economic and Socio-Humanitarian Research (MIET) Referee for more than 15 SSCI journals including Energy, Sustainability, International Journal of Finance & Economics, Kyklos, Labour Economics Teaching & Doctoral Supervision PhD supervisor (XXXVII cycle) and tutor (XXXII cycle) Lecturer, Advanced Macroeconomics – Theory of Economic Growth (PhD) Course leader for Macroeconomics (BSc), International Economics (MSc), Theory of Growth (MSc) Invited lecturer, University of Hanoi & University of Danang (2024), Mendel University Brno (2022), Pan-European University Bratislava (2014)
Daniela Marella is a Professor at the Department of Social and Economic Sciences, Sapienza University of Rome. She teaches Statistics and holds office hours on Tuesdays from 10:00 AM to 12:00 PM. Her email address is daniela.marella@uniroma1.it . Teaching: Statistics (Sociology, Economics, Development Studies) Research: Statistical matching, Bayesian networks, survey sampling, uncertainty quantification Publications: 15+ articles on non-probability sampling, measurement error, and interrater agreement Her research focuses on statistical matching methodologies, Bayesian network applications in survey data, and handling selection bias in non-probability samples. She explores measurement error modeling, empirical likelihood approaches, and resampling techniques for complex survey designs. Recent publications emphasize uncertainty analysis in statistical matching, graphical models for data integration, and Bayesian structural learning. Key areas include non-ignorable sampling, ordinal categorical data agreement, and pseudo-population resampling frameworks.
Vincenzina Vitale serves as a Tenure-Track Assistant Professor of Statistics within the Department of Social and Economic Sciences at Sapienza University of Rome. Her academic profile centers on advanced statistical methodologies with applications spanning economics, public policy, and sustainability initiatives. She teaches core courses including Statistics and Data Science for Sustainability and Statistical Methods and Models for Economics and Public Policy, maintaining regular office hours on Tuesdays from 12:30 to 14:30 by email appointment. Her research program focuses on multivariate analysis, specializing in innovative fuzzy clustering techniques for complex data structures such as time series, spatial data, and mixed data types. She extensively employs probabilistic graphical models, particularly Bayesian networks, for data integration and modeling challenges. This work bridges theoretical statistics with practical applications in electoral analysis, financial volatility, sports analytics, and public health domains including COVID-19 pandemic response. Analysis of her 15 most recent publications reveals a dominant trend toward developing spatially-aware and robust fuzzy clustering algorithms. These methods increasingly incorporate regularization techniques, entropy principles, and copula models to handle interval-valued data, count data, and tail dependencies. Key application areas include regional competitiveness measurement (NUTS2/NUTS3 frameworks), electoral studies, sports performance analytics, and pandemic modeling, demonstrating consistent contributions to top-tier statistical journals. No scientific awards or fellowships were documented in the available materials. While her publication record indicates significant research productivity, specific details regarding graduate student advising, research grants, or collaborative projects were not explicitly mentioned in the provided texts. Similarly, information about laboratory facilities or dedicated research teams remains undocumented in the current sources.
Laura Astolfi is an Associate Professor at the Department of Computer, Control, and Management Engineering , Sapienza University of Rome, and a Researcher at Fondazione Santa Lucia Hospital, Italy. She leads the Bioengineering and Bioinformatics Laboratory and is a Junior Fellow at the Sapienza School for Advanced Studies. Ph.D. in Biomedical Engineering, University of Bologna Master's in Electronic Engineering, University of Rome Sapienza Her research spans brain connectivity , high-resolution EEG source reconstruction , neurorehabilitation , hyperscanning , and social neuroscience . Key applications include disorders of consciousness and motor recovery post-stroke. Recent publications focus on deep learning for EEG localization , functional ultrasound imaging , and multi-subject brain network analysis . Awards include World's Top 2% Scientists (2021–2024) and the Best Under-40 Researcher Award at Sapienza (2010). Associate Editor, Brain Topography , Medical & Biological Engineering & Computing , and IEEE Open Journal of Engineering in Medicine and Biology 261 peer-reviewed papers, 8933 citations, H-index 45
Antonio Cosma is a faculty member at the Department of Business Sciences, University of Bergamo. He holds a Doctorate in Economics and a Master’s in Financial Economics from Université catholique de Louvain. His research focuses on microeconometrics, financial econometrics, and semi/non-parametric statistical methods. Doctorate: Economics, Université catholique de Louvain Master’s: Financial Economics, Université catholique de Louvain His work analyzes conditional moment restrictions, tail dependence in global markets, and wavelet-based estimation techniques. Publications appear in journals like Journal of Financial and Quantitative Analysis and Bernoulli , with a focus on computational finance and statistical modeling for economic data. Recent articles investigate stochastic volatility in American options, stratification effects in econometric inference, and diversification risks in hedge fund markets. He teaches Elementi di Matematica and Strumenti per la Misurazione del Rischio at the University of Bergamo.
