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Salvador Naya FernándezView profile

Professor

• Statistics
• Operational Research
• Thermal Analysis
• +4 more

Salvador Naya Fernández is a Full Professor in the Department of Statistics and Operational Research at the Higher Polytechnic School of the University of A Coruña (Spain). He leads statistical research projects in materials science, thermal analysis, and industrial quality control, with a focus on functional data analysis and reliability engineering. Affiliations: MODES research group, CITIC research center Education: Not explicitly stated in provided texts Research Interests span Statistics , Operational Research , and Materials Science , with specific applications to: Thermal degradation modeling of polymers and composites Functional data analysis for interlaboratory studies Statistical quality control in industrial processes Reliability engineering for mechanical systems Image analysis for defect detection in manufacturing Publication Trends show expertise in applying statistical learning to materials engineering , particularly through thermal analysis (TGA, DSC, DMA) and functional data methods . Collaborative work extends to biomedical scaffolds , energy efficiency , and maritime engineering . Teaching Contributions include advising 25+ graduate theses (2010-2024) in statistical applications to: Biopolymer degradation Credit risk modeling Industrial anomaly detection Maritime traffic analysis Energy efficiency Scientific Awards : No specific awards mentioned in provided texts. Labs & Collaborations : Works with the MODES research group and CITIC at University of A Coruña. Collaborates with universities in Ecuador, France, and Portugal, and participates in international conferences like ISI World Statistics Congress and NATAS .

• Computational Statistics
• Nonparametric Regression
• Survival Analysis
• +4 more

Nora M. Villanueva is an Assistant Professor at the Department of Statistics and Operations Research, University of Vigo. She works at the intersection of computational statistics, nonparametric regression, and survival analysis, with applications to cybersecurity and industry 4.0. Her academic journey includes a PhD in Statistics and Operations Research from the University of Vigo (2021) and prior roles as a Data Scientist at Optare Solutions and Ecomanagement Technology. Education: PhD in Statistics and Operations Research (2021), University of Vigo Her research focuses on predictive modeling, nonparametric curve estimation, and software development for statistical analysis. She has contributed to the creation of four R packages and participated in 17 research projects and 39 conferences. Her most recent publications explore group determination in survival curves, explainable AI methods, and genomic sequence analysis. Her work combines theoretical statistics with practical applications in telecommunications, energy, and biomedical domains. Scientific Awards: Research Award (Science and Technology), Pontevedra Provincial Council (Spain) Premio a la mejor solución del reto IN1: 'Clasificación de ataques a honeypots SSH' Villanueva has extensive teaching experience at the University of Vigo, covering courses in statistics, regression models, and data analytics. She also contributed to industry workshops on predictive modeling and R package development.

• Bayesian Statistics
• Biostatistics
• Epidemiology
• +5 more

Stefano Cabras is a Full Professor in the Department of Statistics at University Carlos III de Madrid (UC3M), where he serves as Director of the Flores de Lemus Institute and Deputy Director of the Master's Degree in Statistics for Data Science. His office is located at 10.1.10 - Campomanes (Getafe). Professor Cabras maintains broad interdisciplinary research interests spanning: Bayesian statistics and computational methods Biostatistical applications in nutrition, epidemiology, and medicine Causal inference and policy impact evaluation Machine learning applications in transportation and sports science Statistical modeling of complex biological systems His publication trends show strong emphasis on Bayesian methodologies applied to healthcare, public policy, and urban systems. Recent work demonstrates increasing integration of deep learning with traditional statistical approaches for problems in causal inference, pandemic forecasting, and transportation optimization. Professor Cabras leads several major research initiatives: Principal researcher for 'Statistical modelling for smart cities' (Beijing Metro Group, 2020-2023) Director of 'Contrato marco para servicios de consultoría estadística' (KROLL Advisory, 2022-2024) Co-researcher for 'Predicción de edad biológica mediante IA' (Fundación Mutualidad Abogacía, 2020-2021) He has supervised graduate research including theses on Bayesian metro occupancy modeling and maintains active collaborations through the Flores de Lemus Institute. His research has been applied in policy analysis, healthcare diagnostics, and urban planning internationally.

• Transportation Engineering
• Infrastructure
• Traffic Management
• +6 more

José María del Castillo Granados is a Professor at the University of Seville, working within the Higher Technical School of Engineering. He belongs to the Department of Materials and Transportation Engineering and Science, with a specialization in Transportation Engineering and Infrastructure. His academic career spans multiple decades with significant contributions to transportation research, mechanical engineering, and statistical modeling. Professor Castillo Granados specializes in Transportation Engineering with research interests spanning multiple domains: Traffic flow theory and modeling, including development of flow-density relationships Transportation demand modeling and forecasting Railway engineering and infrastructure Logistics and freight transportation systems Planetary gear train mechanics and applications Application of statistical methods to transportation problems His research output shows a clear progression from fundamental traffic flow theory to more complex transportation systems analysis, with recent work incorporating modern data sources like mobile phone data for traffic estimation. His publications demonstrate expertise in both theoretical statistical modeling and practical transportation engineering applications, particularly in the areas of traffic flow modeling, transportation demand analysis, and mechanical systems design. Professor Castillo Granados has received research funding for numerous projects including: DESARROLLO DE SISTEMAS AUTORRETENIBLES PARA SU UTILIZACIÓN EN TRANSMISIONES CONTINUAS VARIABLES RED ESPAÑOLA DE PLATAFORMAS LOGÍSTICAS INTERMODALES SIMETRIA: MODELOS DE SIMULACIÓN PARA LA EVALUACIÓN DE ESCENARIOS MULTIMODALES DE TRANSPORTE DISEÑO, CONSTRUCCIÓN Y ENSAYO DE UNA TRANSMISIÓN MECÁNICA CONTINUAMENTE VARIABLE DIURMÓVIL. Dinámica de una ciudad. Caracterización de la movilidad Urbana mediante datos de telefonía móvil He has been actively involved in the academic community, presenting his research at numerous conferences including the EURO Working Group on Transportation meetings, World Conference on Transport Research, and Transportation Research Board Annual Meetings.

PABLO GARCIA TAHOCESView profile

Professor

• Medical Imaging
• Computer-Aided Diagnosis (CAD)
• Digital Mammography
• +3 more

PABLO GARCIA TAHOCES is a Professor at the Department of Electronics and Computing, Higher Technical School of Engineering, University of Santiago de Compostela, Spain. His research focuses on medical imaging technologies, particularly computer-aided diagnosis (CAD), digital mammography, computed tomography (CT), and machine learning applications in radiology. He holds a Doctorate from the University of Santiago de Compostela, with a thesis on breast cancer risk assessment through radiographic analysis. Key contributions include the development of automated systems for detecting breast masses and microcalcifications, image compression techniques for mammograms, and algorithms for aortic geometry analysis. He has collaborated on the Galician Telemammography System project, integrating CAD tools into telemedicine platforms. His work spans over 30 years of research in digital radiography and PACS systems, with a focus on enhancing diagnostic accuracy and workflow efficiency. His publications emphasize advanced imaging techniques, including ellipse-based motion estimation, CT visualization tools, and deep learning applications for cardiovascular and dental imaging. His research has been applied in clinical settings, improving the detection of pulmonary nodules, interstitial lung disease, and aortic pathologies. He maintains active collaborations with institutions like AIMEN Technological Center and Siemens Medical Systems.

• Numerical Methods in Engineering
• Railway Systems
• Fire Safety Engineering
• +5 more

Dr. Alberto Carnicero López is a Senior Associate Professor at the School of Engineering (ICAI) of Comillas Pontifical University, affiliated with the Institute for Research in Technology (IIT). He holds a Ph.D. in Engineering from Comillas and has been active in academia since 1999. His research focuses on numerical methods in engineering, railway systems, catenary-pantograph dynamics, fire safety, thermal/fluids engineering, and bioengineering. He has supervised multiple Ph.D. theses and led over 40 research projects funded by entities like the Spanish Ministry of Science and international organizations. His educational background includes degrees in Mechanical Engineering and Industrial Engineering from Comillas. Key research contributions include advancements in catenary-pantograph interaction modeling, structural analysis using FE methods, and bioengineering applications like subperiosteal implant designs. He has authored 42+ journal articles, with recent works addressing e-scooter rider safety, CO2 emissions during the pandemic, and crack propagation analysis. Dr. Carnicero has received awards such as the X Premio Talgo for Innovation and has served on doctoral committees and as a reviewer for journals like Vehicle System Dynamics . His work bridges engineering disciplines, emphasizing practical solutions for railway systems, biomechanics, and sustainable mobility.

Jose Solana IbañezView profile

Associate Professor

• Data Envelopment Analysis
• Tourism Efficiency
• Municipal Services
• +2 more

Jose Solana Ibañez is Associate Professor in Quantitative Methods at the University of Murcia's Faculty of Economics and Business. His research applies data envelopment analysis to efficiency measurement in public services, tourism regions, and foundations. Research focus: Efficiency determinants in Spanish municipalities and regions Performance benchmarking of public service providers Tourism competitiveness modeling Stakeholder perception of organizational efficiency He investigates exogenous factors affecting public sector performance using empirical methods including two-stage DEA and bootstrap analysis. His work has examined cultural facilities provision, waste management services, and defense sector efficiency.

Jan Olof William NilssonView profile

Professor

• Microeconometrics
• Nonparametric Models
• Labor Economics
• +6 more

Jan Olof William Nilsson is a Full Professor in the Department of Applied Economics at the University of the Balearic Islands (UIB) since 2009. With a PhD in Economics from Umeå University (2005), he specializes in microeconometrics (nonparametric models) and labor economics, focusing on inequality of opportunity, social mobility, and poverty dynamics. He teaches undergraduate and graduate courses including 'Economic Data Analysis,' 'Microeconometrics,' and 'Statistical Learning and Decision-Making.' Research Interests Microeconometrics and nonparametric modeling Labor economics, particularly unemployment and spousal income dynamics Social inequality, mobility, and poverty Water resource economics and sustainability in tourism Educational economics and student expectation analysis Grants & Projects Participated in nationally competitive research projects funded by Spain's Ministry of Science and Innovation Contributed to studies on water tariffs in Mallorcan hotels and peer-to-peer accommodation occupancy rates Involved in teaching innovation projects at UIB Academic Affiliations Member of the Econometrics and Data Science (ECD) Consolidated R&D+I Group at UIB. Previously affiliated with CEMFI (Madrid) and CREB (Barcelona) for research stays.

• Microeconometrics
• Nonparametric Models
• Labor Economics
• +5 more

Jan Olof William Nilsson is a Professor in the Department of Applied Economics at the University of the Balearic Islands (UIB), where he has been teaching since 2009. Born in Umeå, Sweden in 1975, he holds a PhD in Economics from the University of Umeå (2005). His academic career spans institutions in both Sweden and Spain, with significant contributions to microeconometrics and labor economics. His research interests focus on microeconometrics, particularly nonparametric models, labor economics, inequality of opportunity, mobility, and poverty dynamics. More recently, his work has expanded into water resource economics within the hospitality sector, examining water consumption patterns in Mallorcan hotels. His publications appear in high-impact journals including Review of Income and Wealth, Journal of Economic Inequality, Labour Economics, Water Resources Research, and International Journal of Hospitality Management. Analysis of his recent publications reveals a strong methodological focus on nonparametric techniques and twin studies to address selection bias in economic research. His work spans both theoretical econometrics and applied research in labor economics, poverty dynamics, and hospitality economics, demonstrating interdisciplinary breadth while maintaining methodological rigor. Professor Nilsson actively participates in competitive national research projects funded by the Ministry of Science and Innovation, with research spanning topics from educational attainment to water conservation in tourism. He is a member of the Econometrics and Data Science research group at UIB. Teaching responsibilities include undergraduate courses such as Economic Data Analysis and Microeconometrics, as well as Master's level courses including Statistical Learning and Decision-Making and Causal Inference. He supervises bachelor's theses across multiple programs and doctoral students in the Applied Economics doctoral program.

• Time Series Analysis
• Functional Data Analysis
• Bootstrap Methods
• +5 more

Manuel Febrero-Bande is a Professor of Statistics and Operations Research at the University of Santiago de Compostela, affiliated with the Department of Statistics, Mathematical Analysis and Optimization under the Faculty of Mathematics. He earned his PhD in 1995 with a thesis on time series modeling. His research focuses on functional data analysis, time series, bootstrap methods, and computational statistics, with applications in environmental control, finance, and health. He co-developed the R package fda.usc , a key tool in functional data analysis. Febrero-Bande has coordinated academic programs like the Master in Statistical Techniques and the Doctoral Program in Statistics and Operations Research. His work emphasizes statistical methodology and interdisciplinary applications, with over 30 peer-reviewed publications and contributions to software development. Key research trends include functional data classification (e.g., Bitcoin address analysis), variable selection in additive models, and goodness-of-fit testing for functional linear models. He has explored applications in fields like forensic science (post-mortem interval estimation) and malaria transmission dynamics. His collaborative projects span institutions in Spain and internationally, reflecting a commitment to both theoretical and applied statistics. He has advised numerous students, though explicit student names are not listed. Awards are not mentioned, but his contributions to statistical software (e.g., fda.usc) and leadership in academic programs highlight his impact. His research often addresses real-world problems, integrating computational methods with statistical rigor.

• Statistics in Engineering
• Migration Studies
• Big Data
• +6 more

Dr. Raquel Caro Carretero is an Associate Professor at the School of Engineering (ICAI) of Comillas Pontifical University in Madrid. With 26 years of teaching experience , she chairs the Disasters Chair at Comillas and contributes to research in Statistics, Migration, Big Data, Space Sciences , and Sustainable Development Goals (SDGs) . Her work bridges industrial organization with social vulnerability and environmental risk assessment . Education: PhD in Economics and Business Administration (Comillas Pontifical University) Additional Training: Actuarial Sciences Degree (Universidad Complutense de Madrid); Pedagogical Accreditation Certificate Research Highlights: Her publications focus on multivariate statistical analysis for engineering and AI applications in disaster modeling, with recent work on wildfire risk monitoring and microplastics in salt production . She has led strategic partnerships under Erasmus+ and contributed to Martian atmospheric studies via the Meiga-MetNet research group. Scientific Awards: Award for 2006 Best Research in Corporate Social Responsibility Grants & Projects: Collaborated on European Human Rights Agency-funded research, led projects like Martian Data Analysis (ESP2016-79135-R), and participated in climate migration studies. Her work aligns with disaster resilience , climate policy , and smart city initiatives .