جست‌وجوی استاد و پژوهشگر

Xavier Serraمشاهده پروفایل

استاد

• Audio Signal Processing
• Sound and Music Computing
• Music Information Retrieval
• +۵ مورد دیگر

Xavier Serra is a Full Professor at the Department of Engineering at Universitat Pompeu Fabra (UPF), Barcelona. He is the founder and director of the Music Technology Group (MTG), and leads the UPF-BMAT Chair on AI and Music. He also coordinates the Master in Sound and Music Computing and serves as President of the Phonos Foundation. His research focuses on audio signal processing, sound and music computing, and computational musicology, emphasizing open science and open innovation. Education: BSc in Biology, University of Barcelona (1981) Master in Music, Florida State University (1983) PhD in Computer Music, Stanford University (1989) Research Interests: Audio Signal Processing Data-Driven and Knowledge-Driven Methodologies Music Information Retrieval Cultural Music Analysis (e.g., Carnatic/Turkish/Andalusian Music) Music Education Technology Notable Projects: CompMusic (ERC Advanced Grant, 2010-2017): Multicultural computational music analysis Open datasets: Freesound, Saraga, FSD50K Technologies: Reactable, Vocaloid, Essentia API Recent Trends in Articles: Focus on AI-driven audio processing (neural fingerprints, generative models), cross-cultural music analysis, and explainable music difficulty estimation. Awards: ERC Advanced Grant (2010) for CompMusic Project. Labs/Teams: Director of MTG, Phonos Foundation, and UPF-BMAT Chair. Active in open-source projects and international collaborations.

Alejandro Sánchez Graciaمشاهده پروفایل

دانشیار

• Molecular Evolutionary Genetics
• Population Genomics
• Comparative Genomics
• +۳ مورد دیگر

Alejandro Sánchez Gracia is an Associate Professor at the Universitat de Barcelona's Faculty of Biology, affiliated with the Department of Genetics, Microbiology and Statistics. He leads the Molecular Evolutionary Genetics research group and directs the advanced course in 'Phylogenomics and Population Genomics: Inference and Applications.' Education: Llicenciat in Biology (Universitat de Barcelona, 1998), PhD in Biology (Universitat de Barcelona, 2006) Research Focus: Molecular mechanisms of chemosensory gene evolution in arthropods, development of bioinformatics tools for evolutionary and population genomics, and population genomics of adaptation in Drosophila. His work bridges computational methods with evolutionary biology, emphasizing genomic approaches to study adaptation. Key projects include analysis of chemoreceptor gene families across Panarthropoda, genomic studies of Canary Island endemic species, and development of tools like BITACORA for gene family annotation. He has contributed to major genomic resources such as DnaSP 6 and participated in initiatives like the Earth BioGenome Project. Active in collaborative networks like the European Drosophila Population Genomics Consortium and AdaptNET (Adaptive Genomics Network). Grants and Projects: 2021-2024: PID2020-113168GB-I00 (Ministry of Science, Spain) - Poligenic adaptation in Drosophila 2020-2021: Catalan blind scorpion genome project (Institut d'Estudis Catalans) Labs/Teams: Heads the Molecular Evolutionary Genetics group, collaborating on projects involving spider genomics, chemosensory evolution, and population-level adaptation studies.

• High-dimensional statistics
• Bayesian statistics
• Statistical analysis of complex data
• +۴ مورد دیگر

David Rossell is an Associate Professor at the Department of Economics, Universitat Pompeu Fabra (UPF) in Barcelona, Spain. He is affiliated with the Statistics@UPF research group and directs the Master in Data Science at the Barcelona School of Economics (BSE). Previously, he held positions at IRB Barcelona as head of the Biostatistics Unit and at the University of Warwick's Statistics Department. He obtained his PhD in Statistics from Rice University, Houston (USA), and conducted postdoctoral research at M.D. Anderson Cancer Center under Professors Valen Johnson and Veera Baladandayuthapani. Research Interests: Rossell specializes in high-dimensional statistical inference, Bayesian methods, computational statistics, and applications in biomedicine and social sciences. His work emphasizes methodology for complex data integration, variable selection, graphical models, and experimental design. Key areas include non-local priors, scalable Bayesian computation, and the development of R packages for statistical analysis (e.g., casper , chroGPS , gaga ). Publications: His recent work focuses on advancing Bayesian variable selection, graphical models with external data, and causal inference. Themes include leveraging external datasets for improved model accuracy, robustness to model misspecification, and applications in healthcare and complex mixture analysis. His contributions span methodological innovation and computational tools for high-dimensional problems. Funding & Grants: Rossell has secured funding through Spanish and European grants, including Juan de la Cierva Fellowships, AGAUR fellowships, and Marie Slodowska-Curie Actions. He supports PhD and postdoctoral researchers through programs like La Caixa InPhD and Beca Beautriu de Pinós. Labs & Teams: He leads the BSE Data Science Center and contributes to interdisciplinary collaborations at UPF and IRB Barcelona, bridging statistical theory and practical applications in genomics, epigenomics, and health data analysis.

• Innovation Management
• Organizational Innovation
• Quality Management
• +۱۲ مورد دیگر

Josep Llach is a Senior Lecturer at the Barcelona School of Management, Universitat Pompeu Fabra, and a part-time Professor Agregat in the Department of Business Administration, Management and Product Design at the University of Girona. He is an active researcher in innovation management, organizational innovation, sustainability, and operations, with extensive involvement in European and national research projects. University: University of Girona Department: Department of Business Administration, Management and Product Design Secondary Affiliation: Barcelona School of Management, Universitat Pompeu Fabra Academic Rank: Senior Lecturer Part-Time: Yes His research focuses on the intersection of innovation, quality, and sustainability in manufacturing and service firms. He studies how lean practices, digital transformation, circular economy strategies, and green technologies impact firm performance. His work often employs advanced statistical methods such as structural equation modelling and fuzzy-set qualitative comparative analysis. The recent publications highlight a strong trend toward sustainability, digital transformation, and methodological robustness in empirical models. His work spans industries including manufacturing, hospitality, and education, with a methodological emphasis on survey-based research and configurational analysis. Scientific Awards: Emerald Literati Awards – Most Outstanding Paper in 2018 for 'Creating value through the balanced scorecard: how does it work?' Top Downloaded Paper 2018–2019: 'Socially responsible companies: Are they the best workplace for millennials?' Josep Llach has directed five doctoral theses and actively mentors PhD students. He collaborates with the Catalan University Quality Assurance Agency (AQU) as a methodological secretary in accreditation processes. His research is supported by multiple national and European grants, particularly through participation in the European Manufacturing Survey. He is a member of the Grup de Recerca Avançada sobre Dinàmica Empresarial i Impacte de les Noves Tecnologies a les Organitzacions (GRADIENT), a research group focused on organizational dynamics and the impact of new technologies.

• Biostatistics
• Epidemiology
• Survival Analysis
• +۴ مورد دیگر

Gomez Melis, Guadalupe is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the GRBIO research group (Bioestadística i Bioinformàtica) and the Department of Statistics and Operations Research. She collaborates with the Institut de Recerca i Innovació en Salut (Health Research Institute) and the Faculty of Mathematics and Statistics (FME). Her work focuses on biostatistics, survival analysis, multistate models, and clinical trial design, with significant contributions to understanding disease progression and outcomes, particularly in pandemic-related studies. She has supervised doctoral theses and leads various research projects funded by EU and national grants. Her research spans statistical methodologies for healthcare data, including censored data analysis and adaptive clinical trial designs. Key activities include leading over 450 research outputs, including articles in high-impact journals like Biostatistics and BMC Medical Research Methodology , and collaborations on projects like the EU-funded Siemens Energy AI Chair initiative. Her work often integrates statistical modeling with real-world health data, addressing challenges in infectious disease dynamics, elderly patient care, and genomic analysis. Notable contributions include developing the GofCens package for goodness-of-fit methods and the MSMpred interactive tool for predicting patient trajectories via multistate models. She actively participates in international conferences and serves on scientific committees, demonstrating her role in advancing biostatistical methodologies globally.

• Environmental Economics
• Tourism Economics
• Gender Economics
• +۲ مورد دیگر

Dr. Jesus Barreal Pernas serves as Assistant Professor in the Department of Quantitative Economics at the Faculty of Economic and Business Sciences, University of Santiago de Compostela. His research bridges environmental policy, tourism economics, and educational innovation with significant regional impact in Galicia and broader European relevance. His academic foundation includes a 2015 PhD from the University of Santiago de Compostela with thesis "Wildfires in Galicia: causality, forest policy and risk in forest management" supervised by Dra. Maria L. Loureiro. This environmental economics work established his expertise in spatial analysis of forest systems. Barreal Pernas' research program demonstrates three converging trajectories: First, environmental economics focusing on wildfire patterns and forest policy in Galicia using spatial econometrics. Second, tourism economics examining sustainable financing mechanisms (particularly green tax willingness), international tourist segmentation, and PDO region development. Third, educational innovation through gamification techniques for teaching statistics in economics and tourism degrees. His recent publications reveal increasing emphasis on gender perspectives in financial inclusion and pandemic-related economic impacts. Analysis of his 2023-2025 publications shows methodological sophistication in spatial modeling and survey-based behavioral research, with strong policy relevance for Galician regional authorities and European tourism sectors. Key thematic clusters include sustainable tourism financing (12% of recent output), educational technology applications (18%), wildfire management (8%), and gender economics (7%). No scientific awards are documented in the provided materials, though his collaborative network spans multiple European institutions as evidenced by co-authorship patterns. His advisory role appears focused on thesis supervision within USC's economics programs, with research projects frequently addressing practical challenges in Galician tourism and environmental management. Current initiatives suggest expansion into post-pandemic tourism recovery and advanced gamification frameworks for quantitative education.

Pedro Galeanoمشاهده پروفایل

دانشیار

• Outlier Detection
• Time Series Analysis
• Bayesian Inference
• +۳ مورد دیگر

Pedro Galeano is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid (UC3M) since 2009. He holds a PhD in Statistics (2004) under Prof. Daniel Peña, focusing on multiple time series. Previously, he served as Visiting Assistant Professor of Statistics and Econometrics at the University of Chicago’s Graduate School of Business and as a Postdoctoral Fellow at the Department of Statistics and Operations Research at Universidade de Santiago de Compostela. His research focuses on time series analysis, outlier detection, Bayesian inference in financial models, and functional data analysis with applications to missing data. He is an Associate Editor of the Journal of Time Series Analysis and advises the Heliyon journal. Key contributions include developing methodologies for detecting structural breaks, modeling systemic risk via copula approaches, and advancing robust statistical techniques for high-dimensional data. Active in academic leadership, Galeano co-organized the NICDA Workshop 2025 and has published extensively on topics like dynamic factor models, sequential parameter change detection, and functional data applications in energy markets. His work bridges theoretical statistics with practical applications in finance, economics, and environmental science.

Andrea Meilán-Vilaمشاهده پروفایل

استادیار

• Nonparametric Estimation
• Directional Statistics
• Kernel Smoothing
• +۳ مورد دیگر

Andrea Meilán-Vila is an Assistant Professor in the Department of Statistics at Universidad Carlos III de Madrid since 2021, holding a Juan de la Cierva Fellowship since 2023. She earned her PhD in Statistics from Universidade da Coruña (2021) and previously served as a Postdoctoral Fellow at Universidade de Santiago de Compostela's Department of Statistics, Mathematical Analysis and Optimisation. Her research focuses on nonparametric methods for analyzing complex data types, including directional, spatial, and functional data. Key areas include kernel smoothing techniques, goodness-of-fit testing for regression models, and spatial trend estimation. She serves as an Associate Editor for the Journal of Nonparametric Statistics . Recent work emphasizes applications in climate science (temperature curve modeling), fluid dynamics (wake flow control), and biomedical imaging (hippocampus shape analysis). Her methodologies address challenges like sparse data estimation and spatial correlation in regression frameworks. Key Projects: STENED (Stein-based goodness-of-fit tests for non-Euclidean data) Awards: Juan de la Cierva Fellowship (2023) Publications span journals like Journal of Fluid Mechanics , Statistical Papers , and TEST , with a focus on methodological advancements in statistical modeling and computational validation.

Antonio Felix De Amores Hernándezمشاهده پروفایل

دانشیار

• Input-Output Analysis
• Economic Modeling
• Distributional Analysis
• +۳ مورد دیگر

Antonio Felix De Amores Hernández serves as Associate Professor in the Department of Economics, Quantitative Methods and Economic History at Pablo de Olavide University, Spain. His research integrates advanced quantitative methodologies with policy analysis for European economic institutions, particularly the European Commission's Joint Research Centre and EUROMOD project. Education: Doctorate from Pablo de Olavide University (2011) with thesis "Essays in efficiency and stochastic input-output analysis" supervised by Dr. Thijs ten Raa and Dr. José Manuel Rueda-Cantuche Research Interests: De Amores Hernández specializes in Input-Output Analysis and Distributional Economics , with expertise in stochastic modeling, fiscal policy evaluation, and environmental-economic linkages. His work bridges theoretical econometrics with real-world policy applications, focusing on household welfare impacts across the European Union. Publication Trends: Recent work (2022-2025) reveals concentrated focus on inflation dynamics, energy price policies, and carbon taxation distributional effects. His input-output methodology innovations support EU policy frameworks like EUROMOD, while empirical studies on VAT cuts, price comparison tools, and Romania's cost-of-living response demonstrate applied microsimulation expertise. Scientific Awards: No scientific awards documented in source materials Advising & Grants: Actively involved in Pablo de Olavide's Doctoral Program in Economic Analysis and Business Management. Source materials indicate EU-funded research collaboration through the Joint Research Centre but omit specific grant details or student supervision records. Research Infrastructure: Core member of the "Quantitative Methods in Business and Economics" research group, contributing to EU-wide databases including input-output tables and environmental accounts for policy modeling.

Alberto Maydeu Olivaresمشاهده پروفایل

استاد

• Psychometrics
• Structural Equation Modeling
• Item Response Theory
• +۳ مورد دیگر

Alberto Maydeu Olivares is a Professor at the Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, within the Faculty of Psychology. He leads the Violence, Behavior, Individual differences and Technology Studies (WITS) research group. His expertise spans psychometrics, structural equation modeling (SEM), and item response theory (IRT). He holds a Licenciatura in Psychology from the Universitat de Barcelona (1988), a Doctorat in Quantitative Psychology from the same institution (1991), and advanced degrees from the University of Illinois, including a Ph.D. in Quantitative Psychology (1997) and masters in Mathematical Statistics and Quantitative Psychology. His research focuses on improving psychological measurement methods, evaluating model fit in SEM/IRT, and addressing methodological challenges in behavioral data. Notable projects include NSF-funded work on SEM fit indices (2017–2020) and AGAUR-supported studies on IRT applications (2014–2017). He teaches advanced courses like Multivariate Analysis and Structural Equation Models at the master’s level. Maydeu Olivares has authored influential papers on goodness-of-fit assessment, causal effect estimation via instrumental variables, and forced-choice test design. His work bridges statistical rigor with practical applications in psychology, addressing issues like faking in assessments and common method bias. He actively contributes to methodological advancements, emphasizing transparent and robust statistical practices.

• Statistics
• Compositional Data Analysis
• Operational Research
• +۲ مورد دیگر

Maria Gloria Mateu Figueras is an Associate Professor in the Department of Computer Science, Applied Mathematics and Statistics at the University of Girona, where she conducts research and teaching in statistics and applied mathematics. Her work is associated with the Research Group in Statistics and Compositional Data Analysis (GR-EADC). Her primary research interests lie in the field of compositional data analysis, a specialized area of statistics dealing with data that represent parts of a whole. She applies statistical methodologies to analyze such data, contributing to both theoretical and applied advancements in the domain. Her expertise also extends to operational research and applied mathematical modeling. She earned her Degree in Mathematics from the Universitat Autònoma de Barcelona (UAB) on July 31, 1995, and completed her Doctorate at the Universitat Politècnica de Catalunya (UPC) on December 5, 2003. Since November 1, 2011, she has held the position of Associate Professor. Maria Gloria Mateu Figueras is actively involved in research and teaching, with no indication of retirement or part-time status. She maintains a research presence through her institutional profile and ORCID record. She is a member of the Research Group in Statistics and Compositional Data Analysis (GR-EADC), which focuses on methodological and applied research in statistical data analysis, particularly with compositional datasets.

Scott Morrisمشاهده پروفایل

استاد

• Personnel selection
• Psychometrics
• Adverse impact analysis
• +۵ مورد دیگر

Scott Morris is the Nambury S. Raju Endowed Chair in Psychology and a Professor at Illinois Institute of Technology's Lewis College of Science and Letters. He directs the Industrial/Organizational Psychology Program and leads the Personnel Selection & Analytics Lab. Dr. Morris holds a Ph.D. in Industrial-Organizational Psychology from the University of Akron (1994) and a B.A. in Psychology from the University of Northern Iowa (1987). His research examines psychometric methods for fair personnel selection systems, with emphasis on: Advanced statistical models for employment testing Adverse impact analysis and workplace equity Meta-analysis methodology and validity generalization Computer adaptive testing and item response theory Bias in subjective hiring practices and interviews His publications demonstrate consistent focus on quantitative methods for employment decisions, with recent works concentrating on meta-analytic techniques, adverse impact analytics, and adaptive testing systems. Earlier research established foundations in effect size estimation and differential item functioning. Honors include: Fellow, Society for Industrial and Organizational Psychology Fellow, American Psychological Association Dr. Morris serves as Associate Editor for the Journal of Applied Psychology and develops open-source psychometric software. His lab investigates selection system design, AI in hiring reactions, and multidimensional testing applications.

• Survival Analysis
• Spatio-Temporal Modeling
• Bayesian Statistics
• +۷ مورد دیگر

Maria Antonia Barceló Rado is a Professor at the Department of Economics, University of Girona, and a member of the Research Group on Statistics, Econometrics and Health (GRECS). She is also affiliated with the Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP) and collaborates with the Centre de Recerca en Economia i Salut (CRES) at Pompeu Fabra University. Her research spans methodological advancements in survival analysis, spatio-temporal modeling, Bayesian statistics , and applied work in clinical epidemiology, environmental epidemiology, cardiovascular risk factors, chronic diseases , and cancer epidemiology . She has developed a mixed-methods line combining Real World Data with Real World Evidence for epidemic prevention and detection. Licenciate in Mathematics (Universitat Autònoma de Barcelona, 1995) PhD in Mathematics (University of Girona, 2001) Accredited as Catedràtica d’Universitat (ANECA, 2018) Her recent publications focus on environmental stressors , air pollution effects , and spatio-temporal modeling across Spain. Articles address mental health in adolescents , vaccination equity , Covid-19 impacts , and chronic disease epidemiology . Collaborations include institutions like Johns Hopkins University, Pompeu Fabra University, and hospitals in Bellvitge and Barcelona.

• Machine Learning
• Climate Science
• Energy Systems
• +۳ مورد دیگر

Sancho Salcedo Sanz is a Full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department and the GHEODE Research Group. His work focuses on applying machine learning and optimization techniques to energy systems, climate science, and environmental modeling. He holds PhDs from Universidad Complutense de Madrid (2019) and Universidad Carlos III de Madrid (2002). Key research interests include deep learning for energy price prediction, spatio-temporal climate analysis, and hybrid models for renewable energy forecasting. His GHEODE group develops optimization algorithms for network design and distributed systems. Recent publications highlight advancements in extreme weather prediction, smart grid optimization, and explainable AI for environmental monitoring. He has pioneered methodologies like Autoencoder-based flow analogues for heatwave reconstruction and multi-method ensembles for energy demand modeling. Labs/Teams: Leader of the GHEODE Group, specializing in modern heuristics and network design. Collaborates extensively on interdisciplinary projects combining AI with environmental and engineering applications.

• Compositional Data Analysis
• Econometrics
• Financial Ratios
• +۶ مورد دیگر

Dr. Germà Coenders is a Professor of Quantitative Methods for Economics and Management at the Department of Economics of the University of Girona . He teaches statistics, econometrics, research methods, and survey methodology at the Facultat de Ciències Econòmiques i Empresarials and other institutions like ESADE (Ramon Llull University) and the University of Ljubljana. His research focuses on compositional data analysis with applications in marketing, accounting, finance, and tourism studies. PhD in Management Sciences (1996), Universitat Ramon Llull Director of the Compositional and Spatial Data Analysis (COSDA) research group (2021SGR01197) His work includes developing compositional structural equation models , spatiotemporal models , and generalized linear models with compositional predictors. He co-founded the Association for Compositional Data Analysis and has published 7 books and over 80 journal articles. Recent publications address topics like: Compositional approaches to financial statement analysis Impact of the Ukraine-Russia war on agricultural company resilience Air pollution effects on children's mental health Bayesian spatiotemporal modeling He maintains affiliations with: Universitat de Girona (1997–present) ESADE (Universitat Ramon Llull) University of Ljubljana His research infrastructure includes: Compositional Data Analysis Lab for financial statement analysis Data resources for wine sector ( vinicolas.xls ) and beer industry ( cervecera.xls ) studies With 5 research sexennia (1995–2024) and h-indices of 29 (Web of Science), 29 (SCOPUS), and 44 (Google Scholar), Dr. Coenders demonstrates sustained research productivity.