جست‌وجوی استاد و پژوهشگر

• Analytical Chemistry
• Electrochemical Sensors
• Biosensors
• +۳ مورد دیگر

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
• +۴ مورد دیگر

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

Salvatore Ingrassiaمشاهده پروفایل

استاد

• Model-based clustering
• Mixture models
• Computational statistics
• +۴ مورد دیگر

Salvatore Ingrassia is a Professor of Statistics at the Department of Economics and Business, University of Catania, Italy. His research focuses on model-based clustering, mixture models, computational statistics, neural networks, and stochastic algorithms. He has held significant editorial roles, including Associate Editor for Statistical Methods and Applications , Advances in Data Analysis and Classification , and Computational Statistics and Data Analysis . He has also served in institutional leadership roles, such as Quality Assurance Chief Officer at the University of Catania and President of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society. Education includes a Ph.D. in Applied Mathematics and Computer Science from the University of Naples (1991), a Research Fellowship at Ecole Normale Supérieure de Cachan (1993-1994), and a Degree in Electrical Engineering from the University of Catania (1986). His work spans editorial contributions, guest editorships, and institutional responsibilities, reflecting his leadership in statistical methodology and education. His research emphasizes robust statistical modeling, with applications in healthcare, finance, and astrophysics. Notable contributions include advancements in cluster-weighted models, mixture models, and computational algorithms for high-dimensional data. He has collaborated internationally, including visiting positions and editorial roles in leading journals.

Mattia Zorziمشاهده پروفایل

دانشیار

• Learning Dynamic Networks from data
• Robust and distributed filtering
• Dynamic Brain Networks
• +۸ مورد دیگر

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
• +۳ مورد دیگر

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 BALDOمشاهده پروفایل

دانشیار

• Analytical Chemistry
• Environmental Analytical Chemistry
• Archaeometry
• +۵ مورد دیگر

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.

Andreas Heinrich Hamelمشاهده پروفایل

استاد

• Convex and variational analysis
• Optimization theory with set-valued objectives
• Mathematical finance (market models with transaction costs)
• +۲ مورد دیگر

Andreas Heinrich Hamel is a Tenured Full Professor at the Faculty of Economics and Management , Free University of Bozen-Bolzano, Italy. His research focuses on advanced mathematical fields including convex and variational analysis, set-valued optimization, mathematical finance (market models with transaction costs), mathematical economics (incomplete preferences and game theory), and multivariate statistics (quantiles). Academic Rank: Professor Institution: Free University of Bozen-Bolzano School: Faculty of Economics and Management Professor Hamel co-developed the groundbreaking area of Set Optimization , with applications in mathematical finance, economics, statistics, game theory, and multi-criteria decision making. His work includes inventing set optimization approaches to risk measures for multivariate positions and developing optimization methods for economics and business applications. Recent publications highlight his expertise in set-valued risk measures, variational principles, and duality theories. His research spans topics such as cone distribution functions, multivariate shortfall risk measures, and utility maximization under transaction costs, reflecting interdisciplinary contributions to financial mathematics and optimization.

• Multivariate Geostatistics
• Environmental Data Analysis
• Space-Time Covariance Modeling
• +۷ مورد دیگر

Monica Palma is an Associate Professor in Statistics at the University of Salento's Department of Economics. She holds a PhD in Statistics from the University of Chieti (2003) and a Degree in Economics from the University of Lecce (1996). Her research focuses on multivariate geostatistics for environmental data, space-time covariance modeling, stochastic simulation, and GIS/WebGIS applications for big data analysis. She is affiliated with the Centro Ecotekne laboratory and serves as a referee for journals like Stochastic Environmental Research & Risk Assessment and Environmental Science & Technology. Education: PhD in Statistics, University of Chieti, 2003 Master's in Economics, University of Lecce, 1996 Her work bridges statistical methodologies with environmental and socio-economic applications. She has authored 18 journal articles, 16 books, and numerous book chapters. Her research emphasizes interdisciplinary approaches to spatial-temporal data analysis and geostatistical modeling.

Francesca Beccaceceمشاهده پروفایل

دانشیار

• Quantitative Finance
• Decision Theory
• Risk Theory
• +۷ مورد دیگر

Francesca Beccacece is an Associate Professor of Financial Mathematics at Bocconi University in Milan. She has held leadership roles as Director of the Bachelor of Science in Economics and Management for Arts, Culture, and Communication (2016–2019) and Director of the Master in Quantitative Finance and Risk Management (2008–2010; 2012–2014). Her educational background includes a Degree in Economics from Università di Parma. Her research focuses on Quantitative Finance (financial markets models, asset pricing, term structure models), Decision Theory (benchmarking models in finance), and Risk Theory (default risk modeling). Recent work explores multivariate risk attitudes in sustainability policies and regulatory principles for financial amortization. Earlier studies include applications of functional ANOVA in utility theory and stochastic frameworks for project evaluation. Teaching responsibilities span undergraduate and graduate courses, including Financial Models for Valuation , Mathematics , and Quantitative Methods for Social Sciences . Past courses include Mathematics, Advanced Financial Mathematics, Quantitative Methods for Management, and Fixed Income/Asset Pricing in master programs. Her contributions to academia include curriculum development and editorial work in finance-related journals. She advises on financial modeling and risk strategies, though specific advisees are not listed. No scientific awards were explicitly mentioned in the provided text.

Laura Magazziniمشاهده پروفایل

دانشیار

• industrial organization
• economics of innovation
• microeconometrics
• +۲ مورد دیگر

Laura Magazzini is an Associate Professor of Econometrics at the Institute of Economics, Sant'Anna School of Advanced Studies, specializing in microeconomic data analysis with emphasis on innovation dynamics and competition in the Life Science industry. Her methodological expertise spans linear and nonlinear panel data models, limited dependent variable frameworks, and simulation-based estimation techniques. Her academic credentials include: PhD from Sant'Anna School of Advanced Studies (2004) Graduate degree in Statistics for Economics from the University of Florence Research visits at Carnegie Mellon University (Pittsburgh) and University of Sydney during academic training Magazzini's research integrates industrial organization, innovation economics, and advanced econometrics to examine real-world economic phenomena. She develops and applies sophisticated quantitative methods to analyze micro-level data, particularly focusing on pharmaceutical innovation, migration economics, and household labor dynamics. Her interdisciplinary approach bridges theoretical econometrics with empirical industrial organization. Recent publications reveal a consistent focus on methodological innovation applied to substantive economic questions, particularly in health economics and industrial dynamics. Her work frequently employs endogenous-switching models and dynamic panel frameworks to address identification challenges in microeconomic datasets, with strong representation in top journals like The Economic Journal and Management Science . No scientific awards, student advising records, grant details, or laboratory affiliations were documented in the provided materials.

• 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