جستجوی استاد راهنمای دانشگاهی

• Food Science
• Enology
• Biochemistry
• +۳ مورد دیگر

Andrea Curioni is a Full Professor at the University of Padova , affiliated with the Department of Agronomy, Food and Animal Sciences (DAFNAE). His research focuses on enology, food chemistry, and sustainable processing of wine by-products, particularly wine lees and yeast-derived compounds. Academic Field: AGR/15 - Food Science Key research areas include: Antioxidant properties and bioactive peptides from yeast Mannoprotein extraction and wine stabilization Colloid formation and protein-phenolic interactions in red wines Valorization of winery waste through green chemistry Recent publications highlight his work on sustainable extraction methods, sensory interactions in wine, and molecular characterization of grape and wine compounds. His research employs advanced analytical techniques like asymmetrical flow field-flow fractionation and FTIR spectroscopy for wine composition analysis. While no specific awards are documented in this dataset, his extensive publication record demonstrates leadership in food and wine chemistry. He investigates multisensory interactions, allergenicity of grape products, and innovative applications of plant proteins in food systems.

Claudio SILVESTRIمشاهده پروفایل

دانشیار

• Data Mining
• Privacy in Location-Based Services
• Spatio-Temporal Data Analysis
• +۳ مورد دیگر

Claudio SILVESTRI is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He specializes in Computer Science (INFO-01/A), with a focus on data mining, privacy in location-based services, and spatio-temporal data analysis. His research integrates computer science with environmental and biomedical applications. Teaching Responsibilities include courses on Advanced Data Management (Computer Science) and Geographic Information Systems (Environmental Sciences) at the Master's level across multiple academic years. Research Interests span: Algorithms for privacy protection in location-based services Spatio-Temporal Data Warehouses and trajectory analysis Parallel computing on GPU and cloud platforms Applications in fisheries monitoring and diabetic kidney disease modeling Funding Projects include EU initiatives like H2020 (e.g., DC-ren for kidney disease research) and regional grants (e.g., ADMIN4D on Industry 4.0). Key collaborations involve researchers like Salvatore ORLANDO and Debora SLANZI. He is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Social Innovation. Office hours are held Wednesdays 2-4 PM by email appointment.

Francesca PARPINELمشاهده پروفایل

دانشیار

• Statistics
• Machine Learning
• Econometrics
• +۳ مورد دیگر

Francesca PARPINEL serves as an Associate Professor in the Department of Economics at Ca' Foscari University of Venice, holding additional responsibilities as Department Delegate for Language Training. Her academic work spans statistical methodology development and practical applications in economics and finance. Her educational background includes a Degree in Statistics Applied to Economics (1990) and PhD in Statistics (1994), both from the University of Padua. She progressed from Assistant Professor (1996-2002) to her current Associate Professor position (2002-present), while coordinating the Bachelor's Degree Program in International Trade and Tourism from 2011-2018. Research interests focus on advanced statistical methodologies including estimation methods for regressions on complex spaces , evolutionary algorithms for regime-changing models , and statistical measures of systemic risk . Her work bridges theoretical statistics with practical financial applications, particularly in trading systems and risk assessment. Recent publications demonstrate strong interdisciplinary connections between statistics, finance, and computational methods, with increasing emphasis on machine learning applications in financial distress prediction and climate derivatives pricing. She actively supervises undergraduate and graduate theses requiring data analysis, emphasizing proficiency in R programming. Her teaching portfolio includes Statistics, Multivariate Statistics, and specialized laboratories across multiple degree programs including International Trade and Tourism, Economics and Commerce, and Global Development. PARPINEL has organized significant academic events including SIS 2015 (Statistics and Demography: the Legacy of Corrado Gini) and multiple MAF conferences, while maintaining membership in the Italian Statistical Society (SIS).

Mattia Stivalمشاهده پروفایل

پژوهشگر

• Health Inequalities
• Spatio-Temporal Modeling
• Sports Performance Analysis
• +۷ مورد دیگر

Mattia Stival is a Researcher at the Department of Economics , Ca' Foscari University of Venice , with a focus on social statistics (SSD: STAT-03/B). His work bridges Bayesian and computational statistics with applications in public health and sports science. Current statistician for the Planet4Health project Previously postdoctoral researcher for the Age-it project on multi-morbidity modeling PhD in Statistical Sciences (University of Padua, 2022) with thesis on Sports Performance Analysis with State Space Models Research Interests combine methodological innovation with real-world impact: Applied : Health inequalities, aging population dynamics, sport-for-health promotion, competitive sports analytics (talent identification, performance monitoring), diffusion models Methodological : Bayesian inference, computational statistics, spatio-temporal modeling, machine learning, Monte Carlo methods Publications demonstrate interdisciplinary trends across: Sports statistics (decathlon/heptathlon scoring, youth-to-elite transition) Bayesian spatio-temporal health modeling Missing data patterns in longitudinal athlete datasets Scientific Recognition : 2023 Honorable Mention for Best PhD Thesis in Applied Statistics by the Italian Statistical Society (SIS) Teaching includes statistics exercises for economics degrees and R coding in finance analytics. Office hours: Wednesday 10-12 by appointment.

Bartolomeo Montrucchioمشاهده پروفایل

استاد

• Computer Vision
• Quantum Computing
• Image Processing
• +۵ مورد دیگر

Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.

• Bayesian inference
• Biostatistics
• Clinical trials
• +۷ مورد دیگر

Mauro Gasparini is a Full Professor at the Department of Mathematical Sciences (DISMA) of Polytechnic University of Turin. He serves as Director of DISMA since 2019, Member of Academic Senate, and co-leader in the SmartData@PoliTO Big Data Laboratory. His career spans academia and industry, including roles at Purdue University (Assistant Professor 1992-1996) and Novartis (Senior Statistician 1996-1998). He has been Editor of Biometrical Journal (2012-2015) and maintains referee activities across international journals. PhD from University of Michigan (1992, Dirichlet process applications) Academic leadership: Department Director, Editorial boards, ISTAT Advisor Research spans Bayesian methodology with biomedical applications Maintains collaborations with Novartis, Chiesi, and research centers His research interests focus on Bayesian inference , Biostatistics , and Clinical trials methodology, particularly addressing issues in pharmaceutical development, genomic data analysis, and medical decision-making. Recent work includes vaccine efficacy modeling, optimal imaging timing for cancer diagnostics, and adaptive trial designs. Key publication trends show interdisciplinary applications in Statistics in Medicine , Biometrics , and Statistical Methods in Medical Research , with emphasis on biomedical data science, Bayesian adaptive methods, and clinical decision support systems. Scientific contributions include: Editor, Biometrical Journal (2012-2015) Advisor, Italian National Institute of Statistics (2020-2024) Leadership in multiple research projects (NODES, SORGENTE, IDEAS) As PhD advisor, he supervises students in: Shaoshi Tang (Clinical trial modeling) Saeed Sani (Biomedical data analysis) Marco Ratta (Genomic statistics) Luca Rondano (Bayesian methods) Vittorio Zampinetti (Tumor DNA sequencing) Fulvio Di Stefano (Evidence-based decision statistical methods) He leads research projects in pharmaceutical statistics, genomic surveillance, and spatial risk assessment frameworks, with recent emphasis on SARS-CoV-2 analysis and cancer progression modeling.

Ilaria Lucrezia Ameriseمشاهده پروفایل

دانشیار

• Multivariate Analysis
• Time Series
• Nonparametric Statistics
• +۳ مورد دیگر

Ilaria Lucrezia Amerise is an Associate Professor in the Department of Economics, Statistics and Finance 'Giovanni Anania' (DESF) at the University of Calabria (UNICAL). Her research focuses on multivariate analysis, time series, nonparametric statistics, and statistical methods for complex/high-dimensional data including functional and spatial data. Editor-in-Chief of JP Journal of Biostatistics (ANVUR Area 13) Editorial Board Member of International Journal of Statistics and Systems (ANVUR Area 13) Recent research involves: Statistical preprocessing of crowdsourced data for Nigerian food prices Quantile regression with heteroskedasticity and non-crossing constraints Electricity demand forecasting via Reg-SARMA models Exchange rate prediction using simultaneous prediction intervals Time series outlier detection and smoothing techniques She contributes to academic governance through the Laboratorio Statistico Informatico (Statistical Informatics Lab) within DESF. Teaching includes undergraduate and graduate courses in Statistics, with materials available in both Italian and English.

• Dynamic Classification
• Copula Functions
• Probability Distributions
• +۴ مورد دیگر

Francesca Condino serves as Associate Professor of Statistics (SECS-S/01) at the University of Calabria's Department of Economics, Statistics and Finance since 2020, following her tenure as Researcher from 2012. She teaches graduate courses including Multivariate Data Analysis and Statistical Methods for Business Strategies within the Statistics for Data Science and Data Science for Business Analytics programs. Her academic qualifications include: Bachelor's degree with honors in Statistical and Actuarial Sciences from University of Calabria (2002) Master's in Economy and Statistics of Territory from G. Tagliacarne Institute, Rome (2003) Ph.D. in Statistics from University 'Federico II' of Naples (2010) Condino's research centers on dynamic classification algorithms, copula-based dependence modeling, and novel probability distributions. She develops statistical frameworks for analyzing income/consumption data, hydrological phenomena, and medical diagnostics, with particular expertise in density-valued symbolic data classification and spectral biomarker analysis. Her methodological innovations bridge theoretical statistics with applications in economic policy and clinical neuroscience. Analysis of her recent publications reveals three dominant research streams: economic inequality studies using Lorenz curves and share-density clustering; medical diagnostics through FTIR spectroscopy and multivariate analysis for multiple sclerosis/epilepsy; and theoretical contributions to unit interval distributions and copula-based modeling. Her work demonstrates consistent interdisciplinary collaboration between statisticians, economists, and medical researchers. No scientific awards were documented in the provided materials. Her research has been supported by CNR research grants (2004-2010), Calabria Region funding (2008), and University of Calabria research assignments (2012). Teaching experience spans 23 years across multiple institutions, complemented by national scientific qualification for Associate Professorship (2017). She contributes to the 'Statistica & Demografia' research group and utilizes the departmental Statistical Informatics Laboratory for computational work.

Ksenia Morozovaمشاهده پروفایل

پژوهشگر

• Food Chemistry
• Antioxidants
• Milk Processing
• +۳ مورد دیگر

Ksenia Morozova is a researcher at the Free University of Bozen-Bolzano's Faculty of Agricultural, Environmental and Food Sciences. Her work focuses on food chemistry and preservation, particularly antioxidant mechanisms in plant and dairy systems. Research Areas: Food chemistry, antioxidant analysis, lipid oxidation, and waste valorization Techniques: HPLC, NMR, calorimetry, and mass spectrometry Current Projects: Antioxidant extraction from agricultural by-products, oil stabilization, and food authentication Recent research demonstrates her expertise in advanced analytical methods for food quality assessment, with publications in 2025 covering HPLC analysis of Salvia extracts, NMR-based spice authentication, and isothermal calorimetry for oxidation kinetics. She has also explored supercritical CO2 extraction applications and Maillard reaction products as preservatives. Her 2024-2025 publications reveal a strong focus on food authenticity verification (saffron, hay milk), oxidation inhibition mechanisms, and innovative oil structuring techniques for food applications. Current collaborations include VOG Products and University of Zurich researchers.

• Econophysics
• Complex Networks
• Statistical Physics
• +۷ مورد دیگر

Prof. Rosario Nunzio Mantegna is a Full Professor in the Department of Physics and Chemistry - Emilio Segrè at the University of Palermo (Unipa), Italy. He has held office hours in Building 18, Viale delle Scienze, focusing on appointments via email at rosario.mantegna@unipa.it. Research Interests: Econophysics, Complex Networks, Financial Market Dynamics, Air Traffic Systems, and Statistical Physics Applications. Methodological Expertise: Network Validation, Correlation Filtering, Hierarchical Clustering, and Stochastic Modeling. His work bridges physics, finance, and data science through network-based approaches to complex systems. Key contributions include analyzing financial indices, market lead-lag relationships, and air traffic networks. Publications span interdisciplinary topics from autism spectrum disorders to volcanic impact on ATM systems.

• Applied Mathematics
• Probability Theory
• Operational Research
• +۵ مورد دیگر

Sergio Ortobelli Lozza is a full professor in Applied Mathematics at the Department of Management , University of Bergamo (Italy), where he coordinates the Master in Economics and Finance and PhD program in Management Accounting and Finance . With a Ph.D. in Computational Methods for Financial and Economic Forecasting and a Master's in Mathematics, his research focuses on applying probability theory and operational research to economics and finance. His scholarly work includes over 180 refereed publications in prestigious journals such as: European Journal of Operational Research Journal of Banking and Finance Insurance: Mathematics and Economics Mathematical Problems in Engineering His research emphasizes: Portfolio optimization with applications to crisis scenarios Stochastic dominance for sector-based investments De Novo programming in renewable energy location systems Network reputation analysis in financial contexts Scientific achievements include: Best paper award at EBES Athens (2010) Principal Investigator for GACR research projects Editorial board member of Mathematical Problems in Engineering Contributor to PRIN research teams He actively participates in academic conferences and has served on organization committees for events like Managing and Modelling of Financial Risks (2013-2019) and ICSP XIII (2013). Current contact: sergio.ortobelli@unibg.it | ORCID: 0000-0003-4983-8165