جست‌وجوی استاد و پژوهشگر

• Metabolomics
• NMR Spectroscopy
• Multivariate Statistics
• +۳ مورد دیگر

Alessia Vignoli is a Research Fellow at the Department of Chemistry, University of Florence, affiliated with the Magnetic Resonance Center (CERM). She holds a M.Sc. in Chemical Sciences (cum laude) and a PhD in Structural Biology from the University of Florence. Her research focuses on NMR-based metabolomics for disease diagnosis and prognosis, particularly in cardiovascular, neurological, and oncological contexts. She has been awarded the GIDRM Under 35 award (2022) and the Airalzh Grant for Young Researchers (2022). Education: M.Sc. in Chemical Sciences (cum laude) - University of Florence (2014) PhD in Structural Biology (cum laude) - University of Florence (2017) Research interests emphasize metabolic profiling of biofluids using NMR spectroscopy, with applications in precision medicine. Key areas include biomarker discovery for diseases like Alzheimer’s, cancer, and cardiovascular conditions. She has contributed to projects analyzing metabolomic signatures in breast cancer recurrence, myocardial infarction outcomes, and drug response monitoring. Awards and grants include the AIRC fellowship (2019-2020), CERM/CIRMMP institutional support, and collaborations with clinical teams to develop diagnostic tools. Her work bridges analytical chemistry, computational statistics, and clinical translation, leveraging multivariate data analysis and metabolic network modeling. Her research has been applied to diverse fields, including veterinary medicine (e.g., dairy calf health) and space-related physiology (e.g., skeletal muscle adaptation in microgravity).

• Bioinformatics
• Systems Biology
• Deep Learning
• +۶ مورد دیگر

Gianfranco Michele Maria Politano is an Associate Professor at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin, with affiliations to the College of Computer, Film and Mechatronics Engineering and College of Biomedical Engineering. His research focuses on Bioinformatics, Systems Biology, and Deep Learning applications in health. Research trends span computational modeling of biological systems, protein function prediction using machine learning, and public health analysis of disease burdens (influenza, rectal cancer, and COVID-19). He also investigates gene regulatory networks and microRNA roles in inflammation. His teaching includes Bioinformatics and Internship courses for Computer Engineering and Aerospace Engineering students since 2019. He supervises PhD student Sofia Ostellino on computational solutions for disease monitoring and has secured research grants for biostatistics projects like DIDES (exotic animal diagnostics) and rectal cancer ultrasound staging. Notable projects : DIDES (2020), Feasibility study for rectal cancer diagnostics (2021) Patents : Computerized culture protocols for biomanufacturing, Simulation of biological ontogeny

Massimiliano Bencardinoمشاهده پروفایل

استاد

• Economic Geography
• Political Geography
• Geopolitics
• +۱۲ مورد دیگر

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
• +۳ مورد دیگر

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 Giordanoمشاهده پروفایل

دانشیار

• Categorical Data Analysis
• Longitudinal Data Analysis
• Copula Functions
• +۷ مورد دیگر

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 Francoمشاهده پروفایل

استاد

• Social Research Methodology
• Electoral Sociology
• Attitudes and Values of Young People
• +۳ مورد دیگر

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.

• Financial Risk Management
• Portfolio Optimization
• Mathematical Finance
• +۷ مورد دیگر

Rosella Giacometti is a Full Professor in Mathematical Methods for Economics and Actuarial and Financial Sciences at the Department of Management, University of Bergamo, Italy. Since February 2022, she has served as Dean of the School of Economics and Management at the University of Bergamo. Her academic career spans several decades with extensive teaching experience in financial mathematics, risk measurement, and portfolio theory. Professor Giacometti earned her degree in Computer Science from the University of Milan in 1990, followed by an M.Sc. in Statistics and Operational Research from the University of Essex, UK (1993-94), and a PhD from the University of Brescia (1992-95). Her research focuses on financial risk management, particularly in market risk, credit risk, operational risk, and mortality risk. Her work combines mathematical modeling with practical applications in portfolio optimization and risk measurement. She has led several major research projects including the GACR 19-11965S "A network approach to portfolio optimization and tracking problems" (2018-2021). Professor Giacometti's recent publications demonstrate a strong focus on advanced portfolio optimization techniques, network analysis in banking systems, and the measurement of tail risks in financial markets. Her work increasingly addresses contemporary challenges such as climate risk exposure in banking and ESG-integrated risk measures. 2017 Winner of the national special funding for distinguished researchers (FFABR 2017) 1992 Winner of the scholarship funded by Banca Popolare di Bergamo 1995 Grant from IMI-SIGECO Professor Giacometti has advised numerous students and has been actively involved in professional training courses for banks and government institutions, including the Prime Minister's Office in 2012. She has held visiting positions at prestigious institutions including the University of Washington Bothell, Stony Brook University, and the University of Cyprus. Her research has been supported by multiple grants from MIUR (PRIN projects) and other funding bodies. She leads international collaborations through Erasmus+ agreements with Charles University, Prague, and Texas Tech University, and has served in various leadership roles including as Member of the University Board of Directors (2016-2018) and Director of the Master's Degree in "The Educational operator and Autism" (2015-2016).

• Statistics
• Environmetrics
• Air Quality
• +۵ مورد دیگر

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.

• Chemistry
• Inorganic Chemistry
• General Chemistry
• +۵ مورد دیگر

Paride Papadia serves as an Associate Professor in the Department of Biological and Environmental Sciences and Technologies at the University of Salento. His academic appointment is in the Competitive Sector 03/B1 - Fundamentals of Chemical Sciences and Inorganic Systems (CHIM/03). Professor Papadia earned his Chemistry degree with highest honors (110/110) from the University of Bari's Faculty of Mathematical, Physical and Natural Sciences, followed by a PhD in Medicinal Chemistry from the University of Bari's Faculty of Pharmacy. He held a Research Grant at the University of Salento from 2004-2007 before becoming a permanent University Researcher in 2007. In 2022, he obtained National Scientific Qualification for Associate Professor, and in 2025 began his current position as Associate Professor. His research focuses on platinum-based anticancer compounds and their drug delivery mechanisms, application of NMR spectroscopy with multivariate statistical analysis for determining metabolic profiles of biomedical and agri-food interest, structural characterization of pharmaceutical metabolites, and studying the impact of metals and metalloids on ecosystems. With 52 international publications in impact factor journals and an h-index of 18, his scholarly contributions span chemical sciences and environmental applications. Professor Papadia teaches General and Inorganic Chemistry for the Bachelor's Degree in Environmental Sciences and Technologies, and serves as Head Lecturer for General and Inorganic Chemistry in the Bachelor's Degree in Chemistry for Sustainability (6 CFU). His office hours are flexible and by appointment via institutional email, available both in-person and remotely. His laboratory work is conducted at the General and Inorganic Chemistry Laboratory in Building A6 at the Ecotekne Center, where he conducts research in the Department of Biological and Environmental Sciences and Technologies at the University of Salento.

Marco Rianiمشاهده پروفایل

استاد

• Robust Statistics
• Regression Analysis
• Time Series Analysis
• +۵ مورد دیگر

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.

Pietro Belloniمشاهده پروفایل

پژوهشگر

• Epidemiology
• Medical Statistics
• Social Statistics
• +۷ مورد دیگر

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
• +۵ مورد دیگر

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.

• Computational Chemistry
• Physical Chemistry
• Materials Science
• +۳ مورد دیگر

Alfonso Pedone is an Associate Professor at the Department of Chemical and Geological Sciences , University of Modena and Reggio Emilia. His research focuses on computational chemistry approaches to understanding oxide glasses, including silicates, borosilicates, and nuclear waste materials, through molecular dynamics simulations and machine learning potentials. Research Interests : Computational materials science, spectroscopy, glass structure-property relationships, quantum chemistry of minerals, and machine learning applications in material modeling. Teaching : Offers advanced courses in Physical Chemistry I , Energetics and Chemical Equilibrium , and Molecular Spectroscopy for chemistry and sustainable chemistry degree programs. Technical Expertise : Specializes in Density Functional Theory (DFT) calculations, metadynamics, and reactive molecular dynamics for surface interactions and crystallization studies. Collaborative Work : Co-author on studies involving ceria polishing mechanisms, iron toxicity modeling, and machine learning potential benchmarking for industrial applications. Publications : Recent work examines pressure-induced glass densification, dispersion interactions in machine learning potentials, and predictive modeling of glass crystallization pathways.

Augusto Ferranteمشاهده پروفایل

استاد

• Control Theory
• Quantum Computing
• Linear Algebra
• +۵ مورد دیگر

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 Picciمشاهده پروفایل

استاد

• Stochastic Systems
• System Identification
• Control Theory
• +۲ مورد دیگر

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.