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Laura AstolfiView profile

Associate Professor

• Biomedical Engineering
• Neuroscience
• Brain Connectivity
• +4 more

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

• Microeconometrics
• Financial Econometrics
• Semi- and Non-parametric Statistics
• +3 more

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.

• Bayesian Statistics
• Statistical Modeling
• Functional Data Analysis
• +4 more

Raffaele Argiento is a Full Professor of Statistics at the Department of Economics, University of Bergamo since September 2021. His academic career focuses on advanced statistical methodologies with applications across various domains including environmental science, public health, and data analysis. His research is prominently featured in high-impact statistical journals and conference proceedings. Argiento's research interests center around Bayesian statistical methods, particularly in functional data analysis, nonparametric Bayesian modeling, and clustering techniques. His work demonstrates expertise in developing innovative statistical approaches for complex data structures, including spatio-temporal data, categorical variables, and high-dimensional datasets. His research has significant applications in environmental monitoring (particularly air pollution analysis), public health (obesity rate modeling), and seismic monitoring through crowdsourced data. His methodological contributions include advancements in mixture models, partition models, and computational algorithms for statistical inference. His recent publication record shows a strong trend toward developing computationally efficient Bayesian methods for real-world applications. The research spans from theoretical developments in nonparametric Bayesian statistics to practical implementations for environmental monitoring, health data analysis, and functional data processing. His work demonstrates a consistent focus on bridging theoretical statistical advancements with practical applications across multiple scientific domains. Professor Argiento teaches several advanced statistical courses at the University of Bergamo, including Applied Statistical Modelling , Probability and Statistics , and Statistical Models for both undergraduate and graduate programs in Economics and Data Analysis. His teaching reflects his research expertise, emphasizing modern statistical methodologies and computational approaches.

• Analytical Chemistry
• Electrochemical Sensors
• Biosensors
• +3 more

Laura PIGANI is an Associate Professor at the Department of Chemical and Geological Sciences , University of Modena and Reggio Emilia. With expertise in analytical chemistry, she specializes in electrochemical sensor development for applications in clinical, environmental, and food analysis. Research Interests : Electrochemical sensors, biosensors, chemometrics, and optoelectronic materials. Teaching : Courses in Analytical Chemistry and Chemical Sensors at both undergraduate and postgraduate levels. Her work focuses on portable systems for Cannabis sativa analysis, metal bioaccumulation studies in plants, and multisensor data fusion for agricultural monitoring. Recent publications highlight innovations in THC/CBD discrimination , caffeic acid detection , and deep eutectic solvent applications . Collaborations with forensic and environmental institutions underscore her translational research impact. Techniques : Cyclic voltammetry, screen-printed electrodes, sonogel-carbon devices, and multivariate statistical analysis. Applications : Drug testing, grape ripening monitoring, battery recycling, and sustainable pigment extraction. Dr. PIGANI's laboratory employs advanced materials like carbon black , PEDOT , and metal nanoparticles to develop cost-effective, reusable sensors. Her interdisciplinary approach bridges material science, electrochemistry, and analytical methodology.

• Bayesian Statistics
• Statistical Modeling
• Data Science
• +4 more

Gianluca Mastrantonio is an Associate Professor at the Department of Mathematical Sciences (DISMA) of the Polytechnic University of Turin , Italy. He is a member of the Interdepartmental Center SmartData@PoliTO and actively contributes to the Statistics and Data Science research group. His academic roles include teaching in PhD programs (Mathematical Sciences, 2023-2025) and master's courses such as Statistical Methods in Data Science and Statistical Models/Statistical Learning . His research focuses on Bayesian Statistics and Hierarchical Models , with applications spanning Biostatistics , Environmental Monitoring , Machine Learning , and Computational Statistics . Key keywords include RNA Velocity , Sea Climate Analysis , Animal Movement Modeling , and Bayesian Software Development . Selected Scientific Awards Steering Committee Member, Royal Statistical Society (Emerging Applications, 2021-) Effective Member, International Statistical Institute (ISI, 2019-) Effective Member, Graspa (Italy, 2017-) Associate Editor, Journal of Statistical Computation and Simulation (2020-) Key Research Themes Bayesian Modeling of RNA Dynamics Environmental and Wildlife Behavior Analysis Statistical Software Development (Julia/R packages) Climatic Change-Point Detection Integration of Linear/Circular Data in Ecology Applications in Prostate Cancer Diagnostics

• Chemometrics
• Analytical Chemistry
• Spectroscopy
• +4 more

Nicola Cavallini is a Fixed-term Assistant Professor at the Department of Applied Science and Technology (DISAT) , Politecnico di Torino , and a member of the College of Chemical and Materials Engineering . He holds a Scientific Branch CHEM-06/A - Chemical Foundations of Technologies within Area 0003 - Chemical Sciences . Since 2020, he has been teaching Principles of Chemometrics and Practical Design of Experiments to PhD and undergraduate students in Chemical Engineering. 2025/26 : Course Lecturer for Principles of Chemometrics 2024/25 : Course Lecturer for Principles of Chemometrics 2023/24 : Course Lecturer for Principles of Chemometrics 2022/23 : Course Collaborator for Principles of Chemometrics 2021/22 : Course Collaborator for Principles of Chemometrics 2020/21 : Course Collaborator for Principles of Chemometrics His research focuses on Chemometrics , Analytical Chemistry , and Applied Spectroscopy , particularly in food authentication and materials characterization. He has developed methods for ethanol quantification in wine using NMR, rice variety classification via hyperspectral imaging, and fermentation monitoring with portable NIR sensors. Collaborative projects include polymer electrolyte optimization and textile waste valorization in biotechnological processes. Recent publications highlight his work on: Food Fraud Detection (Mechanically Separated Meat in processed products) Advanced Spectroscopic Techniques (NMR and NIR applications) Algorithm Development for FESEM image analysis Sustainable Material Processing (Polymer blends, textile waste) Plant-Microbe Interactions (β-ionone's role in mycorrhization)

Mattia ZorziView profile

Associate Professor

• Learning Dynamic Networks from data
• Robust and distributed filtering
• Dynamic Brain Networks
• +8 more

Mattia Zorzi is an Associate Professor in the Department of Information Engineering at the University of Padova, Italy. He has held academic positions since 2014, transitioning from Assistant Professor to Associate Professor in 2020. His research focuses on system identification, machine learning, and robust control, with applications in dynamic brain networks, robotic systems, and quantum information processing. Education: Ph.D. and M.S. in Information Engineering from University of Padova International Experience: Visiting Scientist at University of Cambridge (2013-2014), Research Associate at University of Liege (2013-2014) Zorzi's research integrates robust and distributed filtering, inverse dynamics learning, and nonparametric identification of Kronecker networks. His work bridges theoretical advancements in spectral estimation with practical applications in neuroscience (e.g., effective connectivity analysis) and control systems (e.g., robust Kalman filtering under uncertainty). Recent publications (2024-2023) demonstrate expertise in ARMA graphical models, kernel-based estimation, and optimal transport for Gaussian processes. He has contributed to the IEEE and IFAC communities as Associate Editor and actively participates in editorial roles for leading journals. Scientific Awards: IEEE Senior Member (2021) Member of IFAC Technical Committee TC 1.1 (2018) Associate Editor roles in Automatica, IEEE Control Systems Letters, and major conferences Grants & Collaborations: Collaborated on projects involving quantum channel estimation, free-space quantum communication, and biomedical signal processing.

• Econometrics
• Economic Statistics
• Policy Impact Evaluation
• +3 more

Riccardo D'Alberto is a Senior Fixed-Term Researcher (RTD-B) and Temporary Assistant Professor at the Department of Economics , University of Verona. He specializes in quantitative methods for policy evaluation and data integration in socioeconomic/environmental contexts. Research Focus: Causal effect analysis (Propensity Score Matching, Diff-In-Diff), statistical matching for data integration, environmental valuation (CVM/CE methods), and quantitative policy assessment at regional scales. His work bridges econometrics, data science, and sustainability science. Notable Collaborations: Participated in Horizon 2020 projects (PROVIDE, LIFT, CONSOLE), FP7 IMPRESA, and European Commission tenders. Affiliated with Verona Experimental Lab in Economics (VELE) and Visual Research Lab . Teaching: Delivers Business Statistics and Financial Statistics courses for Master’s programs in Marketing & Corporate Communication and Banking & Finance.

Maria Antonietta BALDOView profile

Associate Professor

• Analytical Chemistry
• Environmental Analytical Chemistry
• Archaeometry
• +5 more

Maria Antonietta BALDO is an Associate Professor at the Department of Molecular Sciences and Nanosystems (DSMN) at Ca' Foscari University of Venice. She holds roles as Rector's Delegate for Sports Activities and President of the University Sports Committee. Her primary research focuses on Analytical Chemistry with specializations in Environmental Analytical Chemistry, Archaeometry, and Electrochemical Sensor Development. She is involved in the Research Institute for Green and Blue Growth, leading laboratory activities (RDRL) and supervising research facilities in the Epsilon building. Research Interests: Her work spans environmental monitoring (e.g., emerging contaminants in water), cultural heritage preservation (e.g., pigment analysis in artworks), and biomedical diagnostics. She develops electrochemical sensors for real-world applications in food, environmental, and biomedical matrices. Key techniques include voltammetry, microelectrode analysis, and ion-selective sensors. Grants & Collaborations: She leads projects like the 2023 EU-funded 'ProCleanLakes' (environmental lake protection) and a Ministry of Research initiative on biosensors for pyroptosis studies. Her team includes researchers like Angela Maria Stortini and Lorena Gobbo. Past funding includes PRIN grants (2014, 2008) for sensor development and food safety. Teaching: She instructs courses in Analytical Chemistry and Cultural Heritage Analysis for the Chemistry and Sustainable Technologies program. Recent courses include Instrumental Analytical Chemistry Laboratory and Analytical Chemistry for Cultural Heritage. Labs & Facilities: Oversees research laboratories 204-205-206 in the Epsilon building, focusing on electrochemical methods and sensor fabrication. Collaborates with the DSMN library council and contributes to the University Sports Committee.

Massimiliano BencardinoView profile

Professor

• Economic Geography
• Political Geography
• Geopolitics
• +12 more

Massimiliano Bencardino is a Full Professor at the University of Salerno, affiliated with the Department of Political, Social and Communication Sciences. He is based at the Fisciano Campus and holds a PhD and an engineering qualification. His primary academic focus lies in Economic-political Geography, where he contributes significantly through teaching and research. His research interests are broad and interdisciplinary, centering on Economic and Political Geography , Geopolitics (particularly concerning the Mediterranean and water resources), Environmental Sustainability , Remote Sensing , and Spatial Analysis using Geographic Information Systems (GIS). His work critically examines territorial cohesion, land use dynamics, urban-rural linkages, and the Blue Economy, often with a strong policy orientation for regional and European development. The trends in his recent publications reveal a consistent application of quantitative and spatial methodologies to address complex socio-territorial issues. His work spans from analyzing land value dynamics in Campania to investigating Special Economic Zones in Morocco and the geopolitics of water in the Middle East. A recurring theme is the integration of socioeconomic data with spatial analysis to understand urban growth, re-urbanization, and sustainable development in both Italian and European contexts. He is an active researcher with numerous publications, including books such as L’altra sponda. Prospettive di Crescita Blu nel Mediterraneo centro–occidentale and Dinamiche demografiche e consumo di suolo negli ambienti insediativi della Regione Campania , and articles in journals like Sustainability , European Journal of Population , and Environmental Management . His research is supported by his expertise in GIS and statistical modeling. Professor Bencardino teaches key courses for undergraduate and graduate programs, including Geopolitics for the Bachelor's in Political Science and International Relations, Territorial organisation and spatial planning for the Master's in Territorial Policies and International Cooperation, and Tourism geography for the Master's in Management.

• Econometrics
• Time Series Analysis
• Bootstrap Inference
• +3 more

Iliyan Georgiev is an Associate Professor of Econometrics at the Faculty of Economics, University of Bologna, since 2018. Previously, he held roles at Nova School of Business and Economics (2011–2015) and the Agency for Economic Analysis and Forecasting in Sofia (1995–1998). He obtained a PhD in Economics from the European University Institute (2004), and degrees in Mathematics and International Economic Relations from Sofia University and Karl Marx Institute of Economics. His research focuses on econometric theory, time series analysis, bootstrap inference, and spurious correlations. He teaches Econometrics and Mathematics, including differential calculus and stochastic calculus. Georgiev’s work emphasizes robust statistical methods for non-stationary processes and rare events, with applications in financial and economic forecasting. His recent publications explore predictive regression, canonical correlation analysis, and unit root testing under heavy-tailed distributions. He has contributed to methodologies addressing parameter instability and spurious correlations in time series data. No explicit scientific awards are listed, but he achieved National Scientific Qualification for Full Professor in Econometrics (MIUR, 2018). No grants or lab affiliations are mentioned in the provided texts.

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

Giovanni Di FrancoView profile

Professor

• Social Research Methodology
• Electoral Sociology
• Attitudes and Values of Young People
• +3 more

Giovanni Di Franco serves as Full Professor in the Department of Social and Economic Sciences at Sapienza University of Rome's Faculty of Political Science, Sociology and Communication. He directs the book series "La cassetta degli attrezzi" (Franco Angeli Milano) and holds affiliations with CIRES at Roma Tre University and Bonanno publishing house's scientific committee. His research centers on Social Research Methodology , emphasizing data collection/analysis techniques, historical evolution of methods, qualitative-quantitative integration, and micro-macro data synthesis. Specialized in Electoral Sociology , he examines polling methodologies in digital contexts, while his work on Youth Attitudes explores values during economic crises. Additional expertise spans Europeanization Processes , Social Representations of eating disorders, and Social Cohesion frameworks. Recent publications reveal methodological innovation through machine learning applications and critical analysis of intergenerational inequality, reflecting his commitment to advancing sociological research in contemporary digital landscapes. Professor Di Franco has led significant projects including immigrant family-school interactions (2009-10), food education integration (2009), Campanian legality culture (2008), and European identity formation (2007-09), alongside European Commission-funded e-inclusion research. He supervises doctoral candidates through Sapienza's PhD program in Sociology and Applied Social Sciences. He contributes to interdisciplinary research through LARFAD laboratory and CIRES center, developing methodological tools for social analysis while directing academic publications that shape methodological discourse in Italian sociology.

• Statistics
• Environmetrics
• Air Quality
• +5 more

Alessandro Fasso is a full professor of Statistics at the School of Engineering, University of Bergamo, Italy, where he has been teaching since 2000. He serves as Editor in Chief of Environmetrics (2019-) and has held various editorial positions for prestigious journals including Stochastic Environmental Research and Risk Analysis and Advances in Statistical Analysis. His international recognition includes serving as President of The International Environmetrics Society (TIES) from 2017-2019 and as a member of the Council of the International Statistical Institute (ISI) from 2013-2017. Professor Fasso's research focuses on statistical methods and applications to environmetrics, air quality, climate variables, and spatio-temporal data analysis. His work spans functional data analysis for atmospheric profiles, multivariate spatio-temporal modeling of air pollution, and statistical approaches for environmental monitoring networks. He has made significant contributions to understanding collocation uncertainty using heteroskedastic functional regression models and studying vertical smoothing mismatch uncertainty when comparing satellite and radiosonde data. His recent publications (2023-2025) demonstrate a strong focus on PM2.5 pollution modeling, particularly examining livestock-related emissions in the Lombardy region using advanced spatio-temporal techniques. His work increasingly integrates functional data analysis, regularization methods, and uncertainty quantification in environmental applications. The articles show a progression from theoretical statistical developments to practical environmental problem-solving with policy implications. President of The International Environmetrics Society (TIES) (2017-2019) Member of the Council of the International Statistical Institute (ISI) (2013-2017) Elected member of the International Statistical Institute (ISI) Founder and previous Coordinator of GRASPA (2013-2015) Member of WG-GRUAN, Working Group on Atmospheric Reference Observations (2013-) Professor Fasso has successfully supervised numerous PhD students including Emilio Porcu, Michela Cameletti, and Francesco Finazzi. His research has been supported by significant grants including EU Horizon 2020: GAIA-CLIM (budget €500,000), Project AQ2009-EN17 (budget €850,000), and PRIN-2006 (budget €260,000). He has served on evaluation committees for the Italian Research Quality Exercise (VQR 2015-2019) and as a referee for international research councils. His international lecturing activities include PhD courses at Peking University and the University of Bolzano-Bozen.

Marco RianiView profile

Professor

• Robust Statistics
• Regression Analysis
• Time Series Analysis
• +5 more

Marco Riani is Full Professor of Statistics at the Department of Economic and Business Sciences, Faculty of Economics, University of Parma since 2006. He directs the Interdepartmental Center Ro.S.A. (Robust Statistics Academy) and has held academic positions including Post Doctoral Fellow (1996-1998), Lecturer (1998-1999), and Associate Professor (1999-2006) at the same institution. Education: Bachelor of Science in Economics (cum laude), University of Parma (1986-1990) PhD in Statistics, University of Florence (1992-1995) His research centers on robust statistics with methodological focus on robust regression , time series , and multivariate analysis . Applied work spans risk management , quality evaluation , international trade monitoring , and medical statistics (neonatal health parameters). He pioneers outlier detection without arbitrary thresholds and robust machine learning. Recent publications highlight robust transformations for regression, explainable AI, and applications in environmental/medical fields. Key trends include automated fraud detection in trade data, soil moisture estimation through time series, and biomarker analysis for birth anomalies. Scientific awards: Best Italian PhD thesis in Statistics (1997) Best contribution at MATLAB expo 2016 (Milan) As advisor, he has supervised five PhD theses and over 100 degree theses. His grant leadership includes Horizon 2020 PrimeFish (2014-2019) and multiple Italian Ministry projects on robust methods. External expertise spans EU Automated Monitoring Tool projects (AMT3-AMT5) for trade fraud detection. Principal Investigator: 11 national/EU projects (2000-2019) Steering roles: ICORS, SIS CLADAG, Ro.S.A. center He co-developed the FSDA toolbox (MATLAB/R) with the European Commission, enabling robust multivariate analysis for institutions like the Joint Research Centre. The Ro.S.A. center drives his collaborative work on outlier detection and data mining.