جست‌وجوی استاد و پژوهشگر

Roberto Pascual Gascóمشاهده پروفایل

استاد

• Financial Market Microstructure
• High Frequency Trading
• Financial Econometrics
• +۳ مورد دیگر

Dr. Roberto Pascual Gascó is a Full Professor of Financial Economics and Financial Markets at the Department of Business Economics, University of the Balearic Islands (UIB), since April 2019. He has been affiliated with UIB since September 1999 and holds a Ph.D. in Economics from Universidad Carlos III de Madrid (2001). Specialization: Financial Market Microstructure, High Frequency Trading, Financial Econometrics Key research themes: Liquidity, Price Discovery, Market Transparency, Algorithmic Trading Current teaching: Financial Economics (UIB), Financial Stock Markets (Double Degrees), Big Data Econometrics (Master's) His research has appeared in top journals like Journal of Finance , Journal of Financial Markets , and Journal of Banking and Finance , focusing on market structure, liquidity dynamics, and high-frequency trading. Recent articles examine algorithmic trading during crises, non-standard statistical errors, and cross-listing impacts. Notable awards include the Plato Market Innovator Prize (2020), Northern Finance Association Best Paper (2018), and multiple Spanish Stock Exchange recognitions. Scientific Awards Asociación Española de Finanzas (2001, 2006) Fundación de Estudios Financieros (2007) Spanish Stock Exchange (2007, 2009, 2012, 2019) CNMV (2006) Josseph de la Vega Prize (2004) Plato Market Innovator (MI3) Prize (2020) He held visiting fellow positions at NYU (2003), Yale (2012), Université Libre de Bruxelles (2008), Auckland University of Technology (2017), and University of Cambridge (2023). His work involves 18 competitive research projects and multiple grants from institutions including Fulbright and Fundación BBVA.

• Bayesian Statistics
• Biostatistics
• Epidemiology
• +۵ مورد دیگر

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.

• Functional Data Analysis
• Statistical Modeling
• Longitudinal Data Analysis
• +۴ مورد دیگر

Ana Arribas Gil is a Professor at Carlos III University of Madrid , specializing in Functional Data Analysis , Longitudinal Data Analysis , and Statistical Modeling . Her work bridges theoretical statistics with applications in healthcare, demography, and computational biology. Research Focus : Functional data methods, Bayesian and penalized regression models, robust statistical techniques, and alignment algorithms. Methodology : Develops tools for time warping, outlier detection, and lasso-type regularization in mixed-effects models. Applications : Health expectancy estimation, children's well-being metrics, and pregnancy outcome prediction. Her recent publications emphasize penalized splines , dynamic time warping , and robust high-dimensional analysis . She has contributed open-source tools like the roahd R package for functional data.

Antonio Cuevas Gonzálezمشاهده پروفایل

استاد

• Set estimation
• Statistics with functional data
• Classification
• +۱ مورد دیگر

Antonio Cuevas González is a Professor of Statistics and Probability at the Department of Mathematics, Faculty of Sciences, Autonomous University of Madrid. His office is located in Building 17, Room 503 at the university campus in Madrid (28049). He maintains an active research program in statistical methodology and has supervised numerous PhD students throughout his career. Professor Cuevas González specializes in several advanced areas of statistical theory, with primary research interests in set estimation, statistics with functional data, classification methods, and geometric approaches to statistical problems. His work bridges theoretical statistics with practical applications, particularly in high-dimensional and functional data settings. Over his career, he has developed novel methodologies for shape analysis, boundary estimation, and nonparametric classification that have become influential in the statistical community. An analysis of his recent publications reveals a strong focus on functional data analysis, with particular emphasis on regression models, classification techniques, and geometric approaches to statistical problems. His research increasingly integrates machine learning concepts with traditional statistical methodology, particularly through the use of reproducing kernel Hilbert spaces and other advanced mathematical frameworks. The trend shows growing interest in high-dimensional problems, dimensionality reduction techniques, and the development of computationally efficient statistical methods for complex data structures. SEIO-BBVA Foundation Award 2022 to the Best Methodological Contribution in the Statistics Field Medalla de oro 2025 de la Sociedad de Estadística e Investigación Operativa (SEIO) Professor Cuevas González has supervised numerous PhD students including Paloma Sanz (1988), Amparo Baíllo (2000), Alberto Rodríguez-Casal (2003), Alejandro Cholaquidis (2014), José L. Torrecilla (2015), Beatriz Bueno (2018), Luis A. Rodríguez (2024), and Antonio Coín (current). He is currently principal investigator for the research project 'Statistical techniques in high-dimensional spaces' (grant code PID2023-148081NB-I00) funded by the Spanish Ministry of Science, Innovation and Universities from September 2024 until September 2027, with Amparo Baíllo and Javier Cárcamo as main collaborators. As an active member of the statistical research community, Professor Cuevas González serves as Associate Editor for the journal ALEA and contributes to various research collaborations centered around functional data analysis, set estimation, and geometric statistics. His work often involves interdisciplinary collaborations, particularly with researchers in biomedical fields as evidenced by his publication on metabolic changes in mouse hearts.

• Health Economics
• Quantitative Methods in Economics
• Addictive Consumption
• +۳ مورد دیگر

Jaime Pinilla Domínguez is a Full Professor at the University of Las Palmas de Gran Canaria , affiliated with the Department of Quantitative Methods in Economics and Management. His research spans Health Economics and Quantitative Methods , focusing on addictive consumption (tobacco), dental services market analysis, equity in healthcare resource allocation, and quantitative modeling of economic data. Research Interests: Tobacco demand, Dental healthcare equity, Public health financing, and Econometric modeling. Projects: Collaborating on EU-funded initiatives like IMAGINE (antibiotic use in long-term care) and Health Economics and Public Policies (health equity analysis). Publications emphasize policy impacts on smoking behavior, pharmaceutical co-payments, and healthcare access disparities. Recent works explore health technology assessment and seasonal surgical waitlists using advanced statistical methods. Grants: Involved in European Commission and regional projects (FEDER, Fundación Mapfre). Collaborations: Works with Carl Llor, Beatriz González López-Valcárcel, and international institutions.

• Operations Research
• Game Theory
• Optimization
• +۳ مورد دیگر

Julio González Díaz holds the position of General Coordinator of Doctorate and USC at the University of Santiago de Compostela , within the Department of Statistics, Mathematical Analysis and Optimization . His work focuses on advancing mathematical methodologies in optimization, game theory, and operations research, with notable contributions to polynomial optimization, energy network modeling, and algorithmic development. He oversees doctoral programs and contributes to academic governance at the university level. His research interests span game theory (especially cooperative and non-cooperative frameworks), optimization techniques (including global and polynomial optimization), and applied modeling in energy systems and supply chain networks. He has developed algorithms like RAPOSa for polynomial optimization and explored applications such as gas transmission networks and portfolio design. Publications emphasize computational efficiency in optimization, fairness in resource allocation , and interdisciplinary applications of game theory. His work bridges theoretical foundations with practical implementations, as seen in his contributions to open-source solvers and algorithmic advancements. He has received institutional recognition, including an Excellence Award in doctoral program administration. His academic leadership includes coordinating master's and PhD programs in statistical techniques and operations research, fostering educational innovation and international collaborations.

• Functional Data Analysis
• Statistical Modeling
• Biostatistics
• +۳ مورد دیگر

Manuel Febrero Bande is a Professor in the Department of Statistics and Operations Research at the University of Santiago de Compostela (USC). He specializes in functional data analysis, statistical modeling, and their applications in diverse fields such as biostatistics, environmental science, and forensic medicine. His research focuses on developing novel statistical methodologies for complex data structures, including functional regression models and goodness-of-fit tests for high-dimensional and time-dependent data. He teaches courses in Probability and Statistics, Machine Learning, and Functional Data Analysis at both undergraduate and graduate levels. Notable contributions include the development of the fda.usc R package for functional data analysis and the IPMICALC software for post-mortem interval estimation. His work bridges theoretical statistics with practical applications, particularly in forensic science and energy production analysis. Febrero Bande's articles span topics like variable selection in high-dimensional data, nonparametric regression testing, and stochastic volatility modeling. His research emphasizes methodological innovation and computational tools, with applications to environmental monitoring, financial time series, and medical diagnostics.

• Numerical Analysis
• Computational Mathematics
• Applied Mathematics

Maria Luisa Seoane Martinez is a University Lecturer in the Department of Applied Mathematics at the University of Santiago de Compostela. She teaches courses such as Matrix Numerical Analysis and Numerical Computing in One Variable across multiple academic years, including 2022/2023 to 2026/2027. Her teaching responsibilities span various bachelor programs, including Mathematics, Physics, and Informatics Engineering. Her research interests, inferred from her academic role and teaching focus, center on numerical methods and computational techniques within applied mathematics. No specific research grants, awards, or publications are listed in the provided information. Tutoring hours for the selected academic years are noted as 'No data available,' suggesting active teaching commitments without explicit mentoring details. No lab affiliations or team collaborations are mentioned in the text.

• Applied Mathematics
• Approximation Theory
• Orthogonal Polynomials
• +۵ مورد دیگر

Darío Ramos López is a Professor of Applied Mathematics at the Department of Mathematics, Universidad de Almería (UAL). He coordinates the Double Degree in Economics and Mathematics and teaches subjects such as Mathematics II and Numerical Methods and Optimization . His research focuses on Approximation Theory, Orthogonal Polynomials, Bayesian Networks, and Machine Learning applications in biomedical optics and data streams. He leads the research group on Approximation Theory and Orthogonal Polynomials (FQM229). His work integrates mathematical modeling with real-world applications, including corneal data analysis (via the rPACI R package) and environmental conservation projects. He developed the AMIDST toolbox , a Java library for scalable probabilistic machine learning, supporting analysis of massive data streams in finance and other domains. He has authored over 30 publications since 2010, with recent contributions to nonstationary data stream inference and keratoconus detection using Bayesian methods. Tutoring sessions are held in-person or online at CITE III INFORMATICA-MATEMAT (Office 1-400), with flexible scheduling via email appointment.

• Anthropology
• Cultural Evolution
• Bayesian Statistics
• +۴ مورد دیگر

Richard McElreath is a Full Professor and Director of the Department of Human Behavior, Ecology, and Culture at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. He holds an honorary professorship in Human Evolutionary Ecology at Leipzig University. His research focuses on how culture shapes human evolution and adaptation, alongside Bayesian statistical methods. He authored the influential textbook Statistical Rethinking . McElreath earned his Ph.D. in Anthropology (2001) from UCLA and B.S. from Emory University (1995). He held academic positions at UC Davis from 2002–2018, progressing from Assistant to Full Professor. His work integrates theory with empirical studies on cultural dynamics, including fieldwork in diverse populations like the Peruvian Amazon and Faroe Islands. Research Interests: McElreath investigates cultural evolution, social learning strategies, and human behavioral ecology. He develops computational models to bridge theory and data, emphasizing interdisciplinary methods. His Bayesian statistics work provides tools for analyzing complex cultural processes. Grants & Awards: NSF grants (2015, 2014, 2012, 2010) UC Davis Chancellor’s Fellow ($25k, 2007) Max Planck postdoctoral fellowship (2001–2002) MacArthur Foundation grants (2000, 1998) Advising & Mentorship: Supervised PhD students including Tim Waring (now at University of Maine) and Bret Beheim (University of New Mexico). Supported postdocs like Kari Schroeder (Boston University) and John Bunce (Indiana University). Labs & Collaborations: Leads the Max Planck Department, collaborating on projects like cultural transmission in primates and urban settlement evolution in Ulaanbaatar. Develops software like R packages rethinking and glmer2stan .

Eduardo Acosta Gonzálezمشاهده پروفایل

دانشیار

• Applied Econometrics
• Financial Econometrics
• Computational Econometrics
• +۴ مورد دیگر

Eduardo Acosta González is an Associate Professor at the University of Las Palmas de Gran Canaria, affiliated with the Department of Quantitative Methods in Economics and Management. He specializes in Applied Econometrics, Financial Econometrics, and Computational Methods. Current teaching responsibilities include courses like 'Estadística II' (Economics Degree), 'Trabajo Fin de Grado' (Business Administration), and 'Estadística Básica Aplicada al Sector Turístico' (Tourism Degree). His research focuses on econometric modeling with applications to tourism, financial markets, and crisis analysis, often employing genetic algorithms and cointegration techniques. Recent publications analyze hotel industry efficiency in the Canary Islands, the dynamics of the 2008 financial crisis, and epidemiological modeling during the pandemic. He has contributed to numerous projects funded by institutions like Spain's Ministry of Science and Innovation, exploring topics such as stock-bond decoupling, shadow economy determinants, and financial failure prediction. Acosta has presented at international conferences including the 'International Conference on Advances in Tourism Economics' and the 'Workshop on International Economics'. His work bridges quantitative methodologies with real-world economic challenges, emphasizing computational approaches to policy-relevant questions.

• Algebraic Geometry
• Mathematical Biology
• Phylogenetics
• +۳ مورد دیگر

Jesús Fernández Sánchez is a Researcher at the Department of Mathematics, Polytechnic University of Catalonia (UPC), associated with the GEOMVAP (Geometry of Varieties and Applications) research group. He holds an affiliation with the Faculty of Mathematics and Statistics (FME) and the Institute of Mathematics of UPC-BarcelonaTech (IMTech). His work focuses on algebraic geometry, mathematical phylogenetics, and computational algebra, with applications to evolutionary biology and stochastic processes. Research Interests: Fernández Sánchez's research bridges algebraic geometry with biological applications, particularly in phylogenetics. He explores topics such as Markov matrix embeddability, phylogenetic invariants, equivariant models, and algebraic methods for evolutionary analysis. His work includes developing semi-algebraic methods for quartet reconstruction and analyzing rank conditions in phylogenetic networks. Grants & Projects: He has led or contributed to several competitive research projects, including 'GEOMETRIA DE VARIETATS I APLICACIONS' (GEOMVAP group), the María de Maeztu Excellence Program, and collaborations on phylogenetic model development. His projects emphasize multidisciplinary approaches in geometry, algebra, and topology. Advising: He has supervised doctoral students like Marina Garrote-López and Jordi Roca-Lacostena in topics such as phylogenetic reconstruction methods and Markov matrix analysis. His lab investigates geometric and algebraic tools for evolutionary biology, with a focus on model validation and computational techniques. Affiliations: Besides his primary role at UPC, he collaborates with international research networks in algebraic phylogenetics and stochastic processes. His work integrates pure mathematics with applied problems in biology and statistics.

• Microeconometrics
• Nonparametric Models
• Labor Economics
• +۵ مورد دیگر

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.

• Computer Networking
• Telecommunications
• Internet of Things (IoT)
• +۷ مورد دیگر

Thomas Heide Clausen is a Professor at École Polytechnique (France) and leads its computer networking research group. He holds the Cisco Endowed Chair in 'Internet of Everything' and serves as Academic Director for the interdisciplinary Master's program 'IoT: Innovation and Management'. His work focuses on protocols and architectures for maintaining internet connectivity in dynamic environments, particularly through the development of the OLSR and LOADng routing protocols. Education: M.Sc. and PhD from Aalborg University (Denmark) Research: IoT networking, Smart Grid communication, wireless mesh networks, routing protocol design, network load balancing, and security in MANETs Recent Article Trends: Explored machine learning for load balancing (2022), zero-trust architectures (2023), and wireless optimization for IoT/SmarGrid (2016-2022) Scientific Awards: IEEE Senior Member (2016), IEEE Computer Society Distinguished Contributor (2021) Industrial Collaborations: Hitachi (Japan), Fujitsu (USA), Toyota (Japan), Cisco (USA/France), EDF (France), and others

Malika Korganbekovaمشاهده پروفایل

استادیار

• Marketing
• Technology and Society
• Data Privacy
• +۶ مورد دیگر

Malika Korganbekova is an Assistant Professor of Marketing at the University of Chicago Booth School of Business and a Fishman Faculty Fellow. Her research combines causal inference, empirical industrial organization, and machine learning to analyze how technology affects societal issues like privacy, data regulation, and sustainability. PhD in Quantitative Marketing (Kellogg School of Management, Northwestern University, 2024 expected) Master’s in Economics (Penn State, 2018; Central European University, 2015) Bachelor’s in Economics (Lomonosov Moscow State University, 2013) Her work with major e-commerce platforms explores: Privacy restrictions' impact on personalization algorithms Environmental consequences of fast shipping Regulatory challenges in dual-platform B2B markets Dynamic pricing strategies influenced by ranking systems Key methodologies include structural econometrics, deep learning, and field experimentation. Her research has been presented at leading conferences such as INFORMS, KDD Workshop, and Wharton Innovation Doctoral Symposium. Scientific awards include: MSI Alden G. Clayton Best Dissertation Proposal Award (2023) Shankar-Spiegel Best Dissertation Proposal Award (2023) INFORMS Society for Marketing Science Doctoral Fellowship (2022, 2023) She has collaborated with Wayfair’s Machine Learning Science team and previously worked at Google, Morgan Stanley, and KPMG.