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Pietro BelloniView profile

Researcher

• Epidemiology
• Medical Statistics
• Social Statistics
• +7 more

Pietro Belloni is a Researcher (RTDa) at the Department of Statistical Sciences, University of Padua, Italy. His primary role involves advancing statistical methodologies for drug safety and public health research through interdisciplinary projects like the Age-IT initiative. He holds a PhD in Statistics from the University of Padua, completed under Professors Giovanna Boccuzzo and Nicholas P. Tatonetti, with visiting research at Columbia University's Department of Biomedical Informatics. His academic journey includes a Master’s and Bachelor’s in Statistical Sciences from the University of Padua, complemented by an Erasmus exchange in Mathematics and Statistics at Århus University. Belloni’s research focuses on epidemiology, medical statistics, and social statistics, with particular emphasis on text mining, spatial epidemiology, and composite indicators for public health assessment. He actively contributes to research teams such as GLASS (a young Italian social statistics laboratory) and the Age-IT project addressing aging society challenges. Teaching responsibilities span epidemiology, medical statistics, and data analysis methods at both University of Padua and H-Farm College. His software contributions include R libraries like perla for mortality cluster analysis and MARMoT for statistical balancing techniques. Belloni’s work bridges theoretical statistics with practical applications in healthcare and social sciences, with publications in journals like Statistical Methods & Applications and Acta Otorhinolaryngol Italica , and book chapters on pharmacovigilance and text mining. His research has addressed topics ranging from cancer staging through NLP to pandemic sentiment analysis during the first wave of the COVID-19 crisis.

• Analytical Chemistry
• Instrumental Analysis
• Chromatography
• +5 more

Caterina Durante is an Associate Professor in the Department of Chemical and Geological Sciences at the University of Modena and Reggio Emilia. She specializes in Analytical Chemistry (Chimica analitica) and teaches instrumental analytical chemistry courses for both undergraduate Chemistry programs and Master's Degree Courses in Chemical Sciences. Her research interests span multiple areas of analytical chemistry with a strong focus on method development and optimization. She has made significant contributions to food analysis and authentication, particularly for traditional Italian products like Aceto Balsamico Tradizionale di Modena and Parmigiano Reggiano cheese. Her work integrates advanced analytical techniques including chromatography, mass spectrometry, and various spectroscopic methods with sophisticated chemometric approaches for data analysis. Her recent publications (2023-2025) demonstrate a clear research trajectory focused on developing robust analytical methods for complex matrices, with applications in food traceability, environmental analysis, and pharmaceutical quality control. The publications reveal a strong emphasis on chemometrics, particularly multivariate data analysis techniques like PCA, PLS, and PARAFAC, which she applies to interpret complex analytical data from various spectroscopic and chromatographic techniques. She actively collaborates with researchers across multiple institutions, evidenced by her numerous co-authored publications spanning food science, environmental chemistry, pharmaceutical analysis, and green chemistry applications. Her work often addresses practical analytical challenges in industrial and food production settings, with several studies focusing on real-time process monitoring and quality assessment.

Augusto FerranteView profile

Professor

• Control Theory
• Quantum Computing
• Linear Algebra
• +5 more

Augusto Ferrante is a Full Professor at the Department of Information Engineering, University of Padova. His research spans control theory, quantum computing, and linear algebra, with a focus on optimal control, spectral estimation, and matrix analysis. University: University of Padova Department: Information Engineering Research Interests: Ferrante's work addresses theoretical and applied problems in control systems, including quantum control, Riccati equations, and covariance matrix estimation. His contributions bridge mathematical rigor with engineering applications, particularly in spectral analysis and optimization. Publications Trends: His recent work (2014-2012) emphasizes quantum channel estimation, entropy-based spectral methods, and generalized Riccati equations, reflecting a synthesis of control theory and quantum information science. Book Chapters: He has co-authored works on modeling, estimation, and control, including a 2007 Modeling, Estimation and Control volume dedicated to Giorgio Picci.

Giorgio PicciView profile

Professor

• Stochastic Systems
• System Identification
• Control Theory
• +2 more

Giorgio Picci is a Full Professor in the Department of Information Engineering at the University of Padova, Italy, holding this position since 1980. His academic career includes prior roles as Lecturer (1970-1975) in Statistics, Researcher (1973-1980) at LADSEB-CNR, and Associate Professor (1975-1980) in Electrical Engineering at the same institution. International appointments include Brown University, MIT, University of Kentucky, Arizona State University, Kyoto University, and Washington University. He received his Dr. Engineering degree (cum laude) in Electronic Engineering from the University of Padova in 1967. Professor Picci's research pioneered a geometric framework for stochastic systems centered on Markovian Splitting Subspaces , providing probabilistic analogs of state-space concepts. This work revolutionized understanding of minimality in stochastic models and solved noncausal estimation problems. Current research focuses on: Subspace Identification : Addressing closed-loop systems and statistical properties of multivariable system identification Reciprocal Processes : Modeling finite-support signals (e.g., images) to eliminate border effects of traditional methods Mechanical Systems Identification : Using variational integrators for well-conditioned recovery of continuous-time parameters His publication record (2002-2014) demonstrates deep integration of control theory, linear algebra, and statistical estimation. Key trends include unifying subspace identification algorithms, advancing covariance extension for reciprocal processes, and developing robust methods for ill-conditioned identification problems in mechanical systems. Professor Picci leads the Padova research unit that developed breakthrough closed-loop subspace identification algorithms. His collaborations span global institutions including the Royal Institute of Technology (Stockholm) and MIT, with ongoing work on recursive identification and statistical properties of subspace estimates.

FRANCESCO FERRACUTIView profile

Researcher

• Control Systems
• Robotics
• Brain-Computer Interfaces
• +6 more

Prof. Francesco Ferracuti is a Researcher at the Department of Information Engineering (Università Politecnica delle Marche, Ancona, Italy). His work focuses on advanced control systems, robotics, brain-computer interfaces, and energy management. Key research themes include fault-tolerant control, autonomous navigation, and human-machine interaction through wearable sensors. Research interests span across: Control Engineering (MIMO systems, PID control, Model Predictive Control) Robotics (mobile robotics, UAVs, smart wheelchairs) Neuroengineering (EEG-based BCI, cognitive workload assessment) Energy Systems (renewable integration, home energy management) Data-Driven Methods (machine learning, system identification) Publications emphasize innovative solutions like EEG-driven obstacle avoidance and thermal stress monitoring for smart wheelchairs, demonstrating interdisciplinary approaches combining robotics with biometrics. His work on fault detection in multirotors and energy optimization algorithms highlights practical applications in both industrial and healthcare domains. Current projects include the E-MOTIVE initiative for mobility solutions via affective computing and BCI. His lab develops cutting-edge algorithms for cyber-physical systems security and predictive maintenance in industrial equipment.

• Financial Mathematics
• High-Frequency Financial Econometrics
• Stochastic Volatility Modeling
• +2 more

Giacomo Toscano is a Tenured Assistant Professor of Financial Mathematics at the University of Florence, Department of Economics and Management. His research focuses on high-frequency financial econometrics, stochastic volatility modeling, and applications of Fourier methods in economics. He holds a Ph.D. in Financial Mathematics from Scuola Normale Superiore. Research interests include climate risk measurement and econometric methodologies for analyzing financial markets. His work bridges statistical theory with practical applications, such as volatility forecasting using graph attention networks and developing the FMVol MATLAB library for volatility estimation. Recent studies address microstructure noise, Hawkes-driven volatility models, and historical financial systems like 15th-century Barcelona's foreign exchange markets. Publications span 2020–2025, emphasizing volatility dynamics, estimation techniques, and algorithmic trading strategies. His research often combines advanced mathematical tools with empirical validation using S&P500 and other financial datasets. No scientific awards are explicitly listed, though his active publication record suggests potential recognition in econometrics or financial mathematics. Advising and grants details are not provided in the source text.

• Machine Learning
• Cyber-Physical Systems
• Intelligent Embedded Systems
• +5 more

Cesare Alippi is a Professor at Politecnico di Milano, Italy, and Università della Svizzera italiana, Switzerland, with visiting appointments at the University of Kobe (Japan) and Guangzhou (China). His research focuses on machine learning in nonstationary environments, intelligent embedded systems, and cyber-physical systems. Alippi holds IEEE Fellow status and has received notable awards, including the 2016 Gabor Award and the 2018 IEEE CIS Outstanding Computational Intelligence Magazine Award. He has authored a monograph, 6 edited books, and over 200 papers. Alippi's academic roles include Vice-President for Education of the IEEE Computational Intelligence Society and Distinguished Lecturer (2014-2016). He has organized major conferences like IJCNN and IEEE SSCI and contributed to initiatives promoting education in computational intelligence. His research addresses challenges in adaptive systems, embedded intelligence, and fault diagnosis. Key projects include deploying wireless sensor networks for environmental monitoring and developing machine learning algorithms for real-world applications like landslide prediction and network security. Alippi's awards reflect his contributions to neural networks and adaptive learning, including the IBM Faculty Award (2013) and IEEE Young Engineer Award (2004).

• Bayesian Inference
• Spatial Statistics
• Biostatistics
• +5 more

Maura Mezzetti is a Full Professor of Statistics at the Department of Economics and Finance, Università degli Studi di Roma II (Tor Vergata), Rome, Italy. Her career spans institutions such as Harvard School of Public Health, Università Bocconi, and European Institute of Oncology. She holds a PhD in Methodological Statistics from Università di Trento (1997) and a Laurea in Mathematics from Università di Milano (1992). Current Position: Full Professor (2021–Present) Former Roles: Associate Professor (2010–2021), Assistant Professor (2004–2010, Tor Vergata; 2000–2005, Bocconi) Research Interests: She specializes in Bayesian statistical methods for spatially correlated data, hierarchical modeling, survival analysis, and biostatistics. Her work addresses public health challenges like cancer incidence modeling, socioeconomic disparities in disease burden, and psychometric/motor behavior analysis. She has developed Bayesian compartmental models for chemical exposure studies and contributed to epidemiological research on breast and colorectal cancer risk factors. Scientific Awards: Yamagiwa-Yoshida Fellowship (2014) ICRETT Fellowships (2012) Excellence in Research (2005) from Bocconi AIRC Fellowships (1998, 1993) Teaching Contributions: She has taught Statistics at undergraduate and graduate levels across Tor Vergata and Bocconi, including specialized courses in medicine, European economy, and data analysis. Her pedagogical efforts include authoring educational materials like "Statistica Descrittiva: Esercizi risolti e guida alla soluzione usando Excel" (2002).

Andrea CerioliView profile

Professor

• Robust Statistical Methodologies
• Multivariate Data Analysis
• Outlier Detection
• +3 more

Andrea Cerioli is a full Professor of Statistics at the Department of Economics and Management, University of Parma, Italy, since 2002. He specializes in robust statistical methodologies, including the Forward Search approach, multivariate outlier detection, Benford’s Law, and tempered stable distributions, with applications to economic data and international trade fraud detection. Ph.D. in Statistics, University of Padua (1992) Editor-in-Chief of Statistical Methods and Applications (2011-2015) Current Editor of Advances in Data Analysis and Classification President of CLADAG (2009-2011) His research spans robust classification, clustering, and spatial data analysis. He has co-authored over 100 peer-reviewed works, including two Springer books, and has served on numerous conference committees. Recent work focuses on Benford’s Law for fraud detection and tempered stable distributions for modeling heavy-tailed data. He teaches courses like Data Science for Marketing and Statistics for Management at the University of Parma, contributing to graduate programs in trade and consumer marketing. His editorial and academic leadership roles highlight his influence in statistical methodology development.

Fabio VivianoView profile

Research Fellow

• Financial Mathematics
• Actuarial Science
• Risk Management
• +3 more

Dr. Fabio Viviano is a Research Fellow in Mathematical Methods for Economics, Actuarial and Financial Sciences at the Department of Economics, Statistics and Finance 'Giovanni Anania' (DESF) within the University of Calabria . He serves as Professor of Pension Funds and Social Security in the Master's degree course in Finance and Insurance. PhD in Managerial and Actuarial Sciences (University of Udine/University of Trieste, 2022) Research periods at Université Catholique de Louvain (Belgium) and Bayes Business School (UK) Research Focus : The primary research areas of Dr. Viviano revolve around advanced numerical methods for complex derivative securities valuation, longevity forecasting for dependent lives, and morbidity/disability risk management . His work emphasizes computational finance techniques and stochastic modeling for insurance applications. Publication Trends : His peer-reviewed articles focus on Monte Carlo simulation techniques, biometric risk modeling, stochastic valuation of insurance portfolios, and multi-state analysis of health-related risks. Recent works (2024-2025) address semi-Markov modeling of disability, subordinated hypercube mortality models, and iterative simulation approaches for biometric indices.

• Multivariate Statistics
• Data Analysis
• Clustering Algorithms
• +4 more

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.

• General and Inorganic Chemistry
• Analytical Chemistry
• Nuclear Magnetic Resonance (NMR) Spectroscopy
• +9 more

Chiara Roberta Girelli is a fixed-term University Researcher (RTD-B) in the scientific disciplinary sector CHIM/03 (General and Inorganic Chemistry) at the University of Salento, within the Department of Biological and Environmental Sciences and Technologies. She is based at the Ecotekne Center in Lecce and has been actively involved in research and teaching since completing her PhD in 2014. Current Position: Fixed-term University Researcher (RTD-B), University of Salento Department: Biological and Environmental Sciences and Technologies Scientific Sector: CHIM/03 – General and Inorganic Chemistry Teaching Role: Tenured professor of Chemistry in the Optics and Optometry degree program Contact: One of the official contact persons for the Optics and Optometry program since 2020/21 Dr. Girelli's research focuses on analytical and inorganic chemistry with applications in food science and biomedicine. Her early work involved the synthesis and study of platinum-based compounds for potential therapeutic use. Subsequently, her research expanded into the application of NMR spectroscopy combined with multivariate statistical methods to characterize and classify extra virgin olive oils — a significant agricultural product in the Salento region. This interdisciplinary approach bridges chemistry, environmental science, and food technology. She earned her PhD in 2014 from the University of Bari "Aldo Moro" with a dissertation titled: "Synthesis of new platinum complexes potentially active as antitumor and/or antiviral drugs. Uptake and processing of platinum bonded nucleobases." Prior to her current faculty position, she held a research grant from 2014 to 2019 at the University of Salento focused on NMR and olive oil analysis. From 2019 to 2022, she served as a fixed-term University Researcher (RTD-A) under the PON Research and Innovation 2014–2020 AIM program, before transitioning to her current RTD-B role. Although no recent publications are listed in the provided text, her research trajectory demonstrates a strong foundation in chemical synthesis, spectroscopic analysis, and real-world applications in both health and agriculture. Her ongoing role in teaching and research confirms her active status in the academic community. Dr. Girelli has not received any scientific awards listed in the source material. There is no mention of graduate students she may have supervised. She is not part-time, not retired, and not former staff; she is a current, full-time researcher and educator. She is affiliated with the Ecotekne Center at the University of Salento, a hub for interdisciplinary research in environmental and biological technologies, indicating integration into a broader scientific network focused on sustainable innovation.

• Materials Science
• Analytical Chemistry
• Surface Science
• +3 more

Alberto Torrisi is a Full Professor of Analytical Chemistry at the Department of Chemical Sciences of the University of Catania . His career spans over four decades, including roles as Assistant Professor of Physical Chemistry (1984-1992), Associate Professor of Analytical Chemistry (1992-2006), and Full Professor since 2006. He has held visiting positions at Philips Research Laboratories and contributed to institutional committees for academic evaluations. Education: PhD in Chemistry from University of Catania (1980, magna cum laude ) His research focuses on surface and interface phenomena in materials like polymers, metals, and composites, with applications in microelectronics, cultural heritage conservation, and biomedical fields. He pioneered advancements in Secondary Ion Mass Spectrometry (SIMS) , X-ray Photoelectron Spectroscopy (XPS) , and Angle-Resolved XPS for depth profiling and artifact mitigation. His work also includes synthesizing ion-selective macrocyclics and developing big data statistical methods for ToF-SIMS. Recent publications highlight innovations in cluster ion beam depth profiling and multivariate data analysis for improved mass resolution. His scientific output comprises 63 international journal publications and 69 conference presentations, with interdisciplinary applications in cultural heritage and biomedicine. Scientific Awards NATO Scholarship (1988-1989) As an educator, he teaches Analytical Chemistry I and laboratory courses, with active involvement in PhD admissions committees. His institutional roles include membership in evaluation commissions for academic grants and professorships.

• Robust Statistics
• Data Analysis
• Regression Analysis
• +3 more

Prof. Aldo Corbellini is an Associate Professor at the Department of Economic and Business Sciences , University of Parma, Italy. He specializes in robust statistical methods, data analysis, and their applications in economics, business, and health research. Teaching: Courses in Statistics and Statistical Methods for Decision Making (2014–2025) for Economics and Management programs, and Food System Management. Research: Focus on robust regression, outlier detection, data transformations, and ESG modeling for SMEs. Collaborations: Long-term partnership with researchers like Marco Riani and Anthony C. Atkinson. Key Contributions: Development of tools for robust regression monitoring, the fsdaSAS and FSDA4R libraries, and applications in credit risk, fraud detection, and labor market analysis. Publications: Over 15 recent articles spanning robust regression, correspondence analysis, data science, and methodological extensions of the Box-Cox transformation. Historical Work: Contributed to studies on elderly frailty and health status prediction (SMILES Study, 2000–2002).

Fulvio CorsiView profile

Professor

• Financial Economics
• Financial Econometrics
• Empirical Finance
• +4 more

Fulvio Corsi is a Full Professor of Econometrics at the Department of Economics and Management, University of Pisa. He holds a PhD in Finance (2005) from the University of Lugano and earlier degrees from the University of Pisa and Venice International University. His research focuses on financial econometrics, volatility modeling, and systemic risk analysis. Education: Ph.D. in Finance (Hons), University of Lugano, 2005 MSc in Economics and Finance (Hons), Venice International University, 1999 Diploma in Economics and Business (Hons), University of Pisa, 1998 Research Interests: Volatility dynamics modeling (HAR-RV model) High-frequency financial data analysis Financial bubbles and systemic risk Score-driven models for time-varying parameters Covariance and correlation measurement Derivative pricing and risk management His work has been recognized with the 2010 Engle Prize for the influential HAR-RV model. Recent research emphasizes structural VAR identification, nonlinear dynamics, and macroeconomic nowcasting applications. Over 20 years of academic contributions include 40+ peer-reviewed articles in top journals like Journal of Financial Economics and Journal of Econometrics.