جست‌وجوی استاد و پژوهشگر

• Criminal Law
• Criminology
• Cybercrime
• +۷ مورد دیگر

Dr. Steven Kemp is a Senior Lecturer in the Department of Public Law at the University of Girona, Spain. His research focuses on the intersection of criminal law, cybercrime, and criminological analysis, with affiliations to institutions like UNICRI, Open University of Catalonia, and the Institute of Public Security of Catalonia. His work spans digital security, fraud victimization, and sentencing disparities. Current roles: Serra Hunter Fellow, University of Girona (2023–present); Collaborating Teacher, UNICRI (2024–present) Previous roles: Associate Professor, University of Girona (2015–2021); Postdoctoral Researcher, Pompeu Fabra University (2021–2023) and University of Manchester (2021) His research interests include: Cybercrime dynamics during global crises (e.g., pandemic-related fraud trends) Victimization patterns in digital societies, particularly among older adults Legal implications of smart technologies and cybersecurity frameworks Comparative criminal justice systems, especially plea bargaining and sentencing disparities Key trends in his recent publications (2025–2019) highlight: Rising cyberfraud incidents and their societal impacts Interdisciplinary approaches to digital security and legal systems Statistical modeling of crime trends post-COVID-19 Behavioral responses to cybercrime risks Scientific recognition includes: Serra Hunter Fellow He actively collaborates with research groups like the Research Group in the Seminar of Criminal and Criminological Sciences and contributes to public policy initiatives in cybersecurity and fraud prevention.

• Public Administration
• Global Governance
• Regulatory Networks
• +۳ مورد دیگر

Angel Saz Carranza is a Professor and Associate Professor at the Department of Strategy and General Management in the Esade Business School, Ramon Llull University. His research focuses on global governance, intergovernmental organizations, regulatory networks, and public-private partnerships. He contributes to the UN Sustainable Development Goals through his work on institutional frameworks and policy design. He leads research projects funded by the EU and Spanish Ministry of Science, including 'EU-VALUES' (2023-2026) and 'LegitGov' (2022-2025). His work explores accountability mechanisms in EU regulatory networks and governance structures of intergovernmental organizations under the UN system. Key research outputs analyze board design in intergovernmental organizations, network tasks in regulatory frameworks, and determinants of public-private partnership policies. His projects often involve semantic big data analysis and configurational approaches. He is part of the Grup de Recerca en Lideratge i Innovación en la Gestión Pública (GLIGP), a research group focusing on public management innovation. Current and past projects address global governance legitimacy, strategic foresight for Spain's foreign policy, and regulatory network governance.

• Bayesian Statistics
• Financial Econometrics
• Markov Chain Monte Carlo
• +۵ مورد دیگر

Nicholas Polson is the Robert Law, Jr. Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His academic career centers on Bayesian statistics with applications in financial econometrics and machine learning. Polson's research interests span Bayesian statistics, financial econometrics, Markov chain Monte Carlo methods, particle learning, and deep learning applications in finance. His work has significantly contributed to understanding stochastic volatility models and developing new algorithms for Bayesian inference. He has pioneered applications of deep learning in asset pricing, portfolio management, and financial prediction, demonstrating how neural networks can detect complex patterns invisible to traditional financial models. His recent publication trends reveal a strong focus on integrating deep learning with financial econometrics, particularly in developing characteristics-sorted factor models, portfolio optimization techniques, and explaining the performance differences between active and passive investment strategies. His work consistently bridges theoretical statistical methods with practical financial applications, with a particular emphasis on nonlinear modeling and high-dimensional data analysis. His article 'Bayesian Analysis of Stochastic Volatility Models' was named one of the most influential articles in the 20th anniversary issue of the Journal of Business and Economic Statistics Polson teaches courses including 'Bayes, AI and Deep Learning' and 'Business Statistics' at Chicago Booth, with scheduled offerings for both 2024-2025 and 2025-2026 academic years. His work has been featured in Chicago Booth Review, where he has contributed insights on statistical analysis in chess, machine learning applications in money management, and the odds of cheating in competitive settings. His research demonstrates the powerful intersection of Bayesian statistics, financial modeling, and modern machine learning techniques.

• Autonomous Vehicles
• Intelligent Transportation Systems
• Robotics
• +۷ مورد دیگر

Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework

Scott Nelsonمشاهده پروفایل

دانشیار

• Consumer Credit Markets
• Financial Regulation
• Information Asymmetry
• +۷ مورد دیگر

Scott Nelson is an Associate Professor of Finance at the University of Chicago Booth School of Business. His research bridges consumer credit markets, regulatory frameworks, and behavioral economics, with a focus on how information asymmetries and algorithmic decision-making shape market outcomes. He has contributed to understanding the impacts of the 2009 CARD Act, eviction protections in housing markets, and fairness in credit scoring systems. PhD in Economics, Massachusetts Institute of Technology BA (summa cum laude) in Economics and Mathematics, Yale College Nelson's work employs diverse data sources, including credit reports, court filings, and tax records, combined with structural models to analyze consumer and firm behavior. Key themes include regulatory efficiency, validity disparities in predictive models, and the welfare implications of policy interventions. His articles reveal trends in algorithmic regulation (2025), eviction dynamics (2025), credit scoring disparities (2024), and public finance impacts on Chinese real estate (2023). These publications highlight interdisciplinary methodologies integrating economics, law, and data science. Scientific awards include the AQR Top Finance Graduate Award (2018) and National Science Foundation Graduate Research Fellowship. He has held postdoctoral roles at the Consumer Financial Protection Bureau/Princeton University and visiting research positions at the Federal Reserve Bank of Boston.

Alexander P. Frankelمشاهده پروفایل

استاد

• Mechanism Design
• Game Theory
• Contract Theory
• +۲ مورد دیگر

Alexander P. Frankel is the Isidore Brown and Gladys J. Brown Professor of Economics at the University of Chicago Booth School of Business. His research focuses on mechanism design, game theory, and contracting, with applications across various economic domains. Previously, he worked at Yahoo! Research and has published in top economics journals including the American Economic Review and Journal of Political Economy. Education: BS in Mathematics from the University of Chicago BA in Economics from the University of Chicago PhD in Economic Analysis and Policy from Stanford Graduate School of Business Frankel specializes in information economics, mechanism design, and contract theory. His work explores how information structures affect economic outcomes, with applications to delegation, signaling, and strategic communication. He has made significant contributions to understanding how information is designed and used in strategic settings, particularly in areas such as R&D investment, admissions policy, and central banking. Frankel's publication record demonstrates a consistent focus on information design and its applications across diverse contexts. His work spans theoretical developments in signal structures and information hierarchies to practical applications in education policy, corporate decision-making, and monetary policy. The research shows increasing sophistication in modeling information environments and their economic consequences, with recent work addressing contemporary issues like test-optional admissions while maintaining strong theoretical foundations. As a faculty member at Chicago Booth, Frankel teaches Microeconomics (33001) and The Economics of Contracts (33931). His research has received attention in major media outlets including the New York Times, Chicago Tribune, and Freakonomics blog, indicating the broader relevance of his theoretical work to practical economic issues.

• 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.

• Cognitive Neuroscience
• Bilingualism
• Infant Cognition
• +۳ مورد دیگر

Nuria Sebastian Galles is a Full Professor at the Universitat Pompeu Fabra (UPF), affiliated with the Department of Engineering and the UPF Center of Studies in Natural and Artificial Intelligence. Her career includes roles as Associate Professor (University of Barcelona, 1988-2002) and Full Professor (since 2002). She leads the Speech Acquisition and Perception (SAP) Research Group and coordinates major projects such as the BRAINGLOT consortium on bilingualism and cognitive neuroscience. Dr. Galles has received notable awards including the James S. McDonnell Foundation Award and ICREA Academia Prize, and served on the European Research Council Scientific Council. Her research focuses on cognitive neuroscience, bilingualism, and infant language development, leveraging EEG, brain imaging, and behavioral studies. Education: PhD in Experimental Psychology (University of Barcelona, 1986), postdoctoral training at Max Planck Institute and LSCP-CNRS (Paris). Visiting scholarships include University of Pennsylvania, University College London, and University of Chicago. Research Interests: Bilingualism's impact on cognition, neurobiological foundations of language acquisition, infant speech perception, and social cognition. Current projects include ERC-funded studies on attention-language links and cognitive effects of walnut consumption in adolescents. Publications: Over 100 peer-reviewed articles in journals like Science , PNAS , and Developmental Science , with a focus on bilingualism, phonetic categorization, and social hierarchy processing in infants. Editor of Developmental Science and Language Learning and Development . Grants & Teams: ERC Advanced Grant (Under Control), Consolider-Ingenio 2010 (BRAINGLOT). Lab collaborations include multi-country studies on traffic pollution’s cognitive impact and walnut-based dietary interventions.

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.

Sanjay K Dharمشاهده پروفایل

استاد

• Strategic Marketing Management
• Brand Management
• New Product Development
• +۱۲ مورد دیگر

Sanjay K. Dhar, the James M. Kilts, Jr. Professor of Marketing at the University of Chicago Booth School of Business, is a leading scholar in strategic marketing management and retail dynamics. His work bridges empirical economic modeling with actionable business insights. Education: B.Tech (IIT), MBA (IIM), PhD (UCLA Anderson School) Affiliation: Faculty member at Chicago Booth since 1992 Research interests span brand management , consumer behavior , and retail strategy , with a focus on how economic factors and marketing mix variables influence household budget allocations and brand performance . His empirical work leverages massive datasets like Nielsen Homescan to uncover geographic patterns and long-term consumer trends . Recent publications examine on-screen cigarette product placement effects, WIC program impacts on cereal consumption, and retail format competition . His 2025 under-review paper extends these insights to multi-category budget reallocation during macroeconomic shifts. Scientific Recognition includes: William O’Dell Award Finalist (2012) Paul Green Award (2008) John D. C. Little Award (1995) McKinsey Teaching Excellence Award (2000) Hillel Einhorn Teaching Awards (2008, 2012) Dhar’s teaching philosophy emphasizes mastering fundamentals to solve complex marketing problems. He advises firms on strategic marketing and new product development while maintaining active research in consumer packaged goods (CPG) industries.

Puig Oriol, Xavierمشاهده پروفایل

استادیار

• Bayesian data analysis
• Model Based clustering
• Multinomial model
• +۷ مورد دیگر

Xavier Puig is an Assistant Professor at the Universitat Politècnica de Catalunya (UPC) , affiliated with the Department of Statistics and Operations Research and the School of Mathematics and Statistics (FME). He is a member of the ADBD - Analysis of Complex Data for Business Decisions and GRBIO - Biostatistics and Bioinformatics Research Group . His research focuses on Bayesian data analysis , with applications in Epidemiology Ecology Public health Political science Industrial quality control Marketing analytics Recent publications reveal a strong trend in Bayesian spatiotemporal modeling for health data, alcohol-migraine interaction studies, and industrial error rate monitoring . His work combines methodological innovation with real-world applications across diverse sectors. Collaborations include researchers from biostatistics, clinical epidemiology, and industrial engineering. He has contributed to 44 indexed journal articles and participated in 49 congress presentations , with recent projects focusing on competitive research and non-competitive industrial collaborations in statistical modeling.

• Macroeconomics
• Applied Macroeconomics
• Theoretical Macroeconomics
• +۱۰ مورد دیگر

Francesco Turino is a Professor in the Department of Fundamentals of Economic Analysis at the University of Alicante, affiliated with the Faculty of Economic and Business Sciences. He is an active researcher and educator, with a strong presence in macroeconomic research and public policy analysis. Academic Background: PhD in Economics, Pompeu Fabra University (2009) MSc in Economics, Pompeu Fabra University (2002) Laurea in Economics, University of Bologna (2000) His research focuses on theoretical and applied macroeconomics, particularly tax evasion, the shadow economy, fiscal policy, and business cycle dynamics. He employs quantitative models such as DSGE frameworks and general equilibrium analysis to study issues like financial frictions, firm informality, and public debt sustainability. His work often draws empirical evidence from Spain and broader European contexts. His recent publications (2022–2023) emphasize the interplay between tax evasion, fiscal policy, and macroeconomic stability. Trends in his research show a consistent focus on informal economic activity, its measurement, and policy implications, supported by rigorous econometric and modeling techniques. Scientific Contributions: Published in top journals including Economic Journal , Review of Economic Dynamics , and European Economic Review Active participant in competitive public research projects funded by national and regional agencies Contributor to teaching innovation, especially in English-medium instruction in economics Francesco Turino has directed or co-directed three doctoral theses and has been involved in over 10 public research projects in the last five years. He teaches advanced and undergraduate courses in macroeconomics, international macroeconomics, and econometrics. He has also contributed to teaching innovation projects related to bilingual education. He is part of the Macroeconomics and Financial Econometrics (MacroMetrics) research group at the University of Alicante.

• Behavioral Science
• Management
• Judgement and Decision Making
• +۳ مورد دیگر

Gaël Le Mens is a Full Professor at Universitat Pompeu Fabra, specializing in Behavioral Science, Management, and Judgment and Decision Making. His research focuses on organizational theory, social influence, and the psychological mechanisms underlying decision-making processes. He holds a PhD from Stanford University and has published extensively in top journals such as Psychological Review and Journal of Personality and Social Psychology . His work explores topics like information sampling, categorization heuristics, and the dynamics of collective beliefs. Key research themes include the 'simple averaging heuristic' in category evaluation, the impact of social influence on decision-making, and the application of machine learning to analyze political texts and concepts. His recent work extends to studying politician-citizen interactions via social media and the semantic analysis of cultural concepts using AI tools like GPT-4.

• Quantum Machine Learning
• Reinforcement Learning
• Medical Informatics
• +۱۲ مورد دیگر

Jose David Martin Guerrero is a Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is conducted within the Intelligent Data Analysis Laboratory (IDAL), focusing on the intersection of quantum computing, machine learning, and biomedical applications. His research interests span Quantum Machine Learning , Reinforcement Learning for Quantum Control , Deep Learning for Medical Image Analysis , and Long-COVID Symptom Trajectory Modeling . He applies advanced AI techniques to solve complex problems in physics, healthcare, and engineering, particularly in modeling prostate cancer, hemodialysis, and post-COVID neurological and functional impairments. The recent publications highlight a strong trend toward integrating quantum computing with classical machine learning, especially in developing quantum neural networks, quantum autoencoders, and reinforcement learning for quantum gate optimization. Simultaneously, a significant body of work uses clustering, deep learning, and Bayesian modeling to analyze longitudinal clinical data from multicenter studies like LONG-COVID-EXP, aiming to understand symptom persistence and recovery patterns in post-COVID patients. Dr. Martin Guerrero earned his PhD from the Universitat de València in 2004 with a thesis on unsupervised techniques for web trend detection and collaborative filtering-based recommendation systems, supervised by Dr. Emilio Soria Olivas and Dr. Paulo Jorge Gomes Lisboa. His work demonstrates active collaboration across disciplines, particularly in clinical research involving multicenter studies, and in quantum computing applications in physics and finance. While no specific grants are mentioned, his involvement in large-scale clinical studies and quantum computing research suggests significant project leadership and funding acquisition. He leads research within the Intelligent Data Analysis Laboratory (IDAL) , which focuses on self-organizing maps, clustering, learning vector quantization, and their applications in security, healthcare, and quantum systems.