جستجوی استاد راهنمای دانشگاهی

• Public Economics
• Industrial Organization
• Government Procurement
• +۳ مورد دیگر

Rodrigo Carril is an Assistant Professor at the Department of Economics and Business at Universitat Pompeu Fabra (UPF) and an Affiliated Professor at the Barcelona School of Economics (BSE). His research focuses on Public Economics and Industrial Organization, particularly examining public procurement policies and their economic impacts. He holds a PhD in Economics from Stanford University (2020) and is a Juan de la Cierva Researcher. Education: PhD in Economics, Stanford University (2020). His work explores topics such as pharmaceutical market dynamics, defense contracting efficiency, and regulatory frameworks for public procurement. He has received prestigious awards including the Claire and Ralph Landau Prize (2020) and the Young Economists' Essay Award (2022). Key research trends include analyzing procurement policies' effects on competition, evaluating preference programs for disadvantaged groups, and methodological contributions to econometric techniques like regression discontinuity designs. Awards: Claire and Ralph Landau Prize 2020 Young Economists' Essay Award 2022 Advising and Grants: While specific grants aren’t listed, his collaborative work involves co-authors like Claudia Allende, Mark Duggan, and Andres Gonzalez-Lira, indicating active academic partnerships. He is affiliated with the BSE and contributes to policy-oriented research initiatives. Labs/Teams: Engaged in interdisciplinary projects at UPF and BSE, focusing on public sector efficiency and regulatory economics.

Bryon Aragamمشاهده پروفایل

دانشیار

• Causality
• Statistical Machine Learning
• Probabilistic Modeling
• +۶ مورد دیگر

Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.

Bernhard Schölkopfمشاهده پروفایل

استاد

• Machine Learning
• Causal Inference
• Artificial Intelligence
• +۴ مورد دیگر

Bernhard Schölkopf is a Director at the Max Planck Institute for Intelligent Systems and holds a Professorship at ETH Zurich. He is one of Europe's leading researchers in Artificial Intelligence and serves as co-founder and president of ELLIS (European Laboratory for Learning and Intelligent Systems). His scientific interests focus on machine learning and causal inference, with applications spanning biomedical problems, computational photography, and astronomy. Schölkopf has conducted research at prestigious institutions including AT&T Bell Labs, GMD FIRST in Berlin, and Microsoft Research Cambridge before joining the Max Planck Society in 2001. Schölkopf's recent work examines the tangible risks of AI systems rather than speculative existential threats, highlighting important challenges including algorithmic bias, lack of transparency, privacy violations, worker exploitation, carbon footprint of AI systems, and job displacement across multiple publications in different languages. His scientific achievements have been recognized with numerous prestigious awards: Academy Prize of the Berlin-Brandenburg Academy of Sciences and Humanities Royal Society Milner Award Leibniz Award Koerber European Science Prize BBVA Foundation Frontiers of Knowledge Award Allen Newell Award Fellow of the ACM Fellow of the CIFAR Program "Learning in Machines and Brains" Schölkopf is a member of the German Academy of Sciences (Leopoldina) and co-founded the series of Machine Learning Summer Schools. His work bridges theoretical advances in machine learning with practical applications across diverse domains, while advocating for responsible AI development that addresses real-world challenges rather than speculative existential threats.

• Labor Economics
• Public Economics
• Health Economics
• +۴ مورد دیگر

Libertad González is an Associate Professor of Economics at Universitat Pompeu Fabra and a researcher at the Barcelona School of Economics (Barcelona GSE). She is affiliated with the Department of Economics and Business, located at the Ciutadella Campus in Barcelona. She holds prestigious research grants, including an ICREA Academia Award and an ERC Consolidator Grant, underscoring her leadership in economic research. Research Interests: Her work spans Labor Economics, Public Economics, and Health Economics, with a strong focus on policy-relevant issues such as reproductive rights, parental leave, gender equality, and the socioeconomic impacts of health policies and pandemics. She uses rigorous empirical methods to evaluate long-term outcomes of social and health interventions. Her recent publications analyze the effects of abortion legalization, paternity leave reforms, and the impact of the Covid-19 pandemic on reproductive health. These studies reflect a consistent theme of evaluating how institutional and policy changes affect individual behavior and long-term socioeconomic and health outcomes, particularly for women and families. Scientific Awards: ICREA Academia Award ERC Consolidator Grant Advising and Grants: While specific students are not listed, she leads major funded research projects, including an ERC Consolidator Grant, which supports independent, high-impact research. Her ICREA Academia award recognizes excellence in both research and teaching, suggesting active mentorship and academic leadership. Labs and Research Teams: She collaborates with leading institutions and researchers across Europe, including the Centre for Economic Performance (LSE) and Nada Es Gratis. She is actively engaged in policy communication, presenting her findings through videos, interviews, and public blogs.

• 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.

Guenter J. Hitschمشاهده پروفایل

استاد

• Quantitative Marketing
• Industrial Organization
• Consumer Choice Modeling
• +۷ مورد دیگر

Günter J. Hitsch is the Kilts Family Professor of Marketing at the University of Chicago Booth School of Business, where he has been a faculty member since 2001. His academic leadership extends to editorial roles as Co-Editor of the Journal of Quantitative Marketing and Economics and Associate Editor at Marketing Science and Management Science. Hitsch's educational journey includes an undergraduate degree from the University of Vienna (1995), followed by master's degrees in economics (1997, 1998), and a PhD in economics from Yale University (2001). This strong foundation in economics informs his approach to marketing research. His research program focuses on quantitative marketing and industrial organization, with particular emphasis on dynamic models of firm and consumer decision-making. Key areas include advertising effectiveness, pricing strategies, sequential learning and experimentation, and intertemporal consumer choice. Hitsch is pioneering in applying causal inference and machine learning to solve practical marketing problems such as optimal customer targeting. His work on dating and marriage markets demonstrates innovative application of economic theory to social phenomena. Hitsch's publication trajectory shows evolution from foundational work on consumer choice and switching costs to more recent applications of machine learning in marketing contexts. His research spans theoretical development and practical application, examining everything from private label demand during economic recessions to television advertising effectiveness across hundreds of brands. Co-Editor, Journal of Quantitative Marketing and Economics Associate Editor, Marketing Science Associate Editor, Management Science Hitsch's editorial leadership has significantly shaped the direction of quantitative marketing research. His commitment to methodological rigor and generalizable results ensures his work provides reliable inputs for both marketing practitioners and academic researchers. As an educator, Hitsch teaches advanced courses in quantitative marketing and business analytics, with scheduled courses for 2024-2026. He emphasizes that 'good marketing isn't fluffy,' challenging students to develop analytical approaches to marketing problems. His research philosophy prioritizes providing generalizable results that apply beyond specific case studies, serving as inputs for both practitioner decision-making and academic advancement.

• 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.

Christian B Hansenمشاهده پروفایل

استاد

• applied and theoretical econometrics
• high-dimensional data analysis
• causal inference using machine learning
• +۴ مورد دیگر

Christian B. Hansen is the Wallace W. Booth Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. He serves as the academic coordinator for Booth's Sokolov Executive MBA Program and is co-editor of the Journal of Political Economy - Microeconomics. Hansen joined the Chicago Booth faculty in 2004 after completing his PhD at MIT. Education: PhD in Economics, Massachusetts Institute of Technology (2004) Bachelor's degree in Economics, Brigham Young University (2000) Professor Hansen specializes in applied and theoretical econometrics, with research focusing on high-dimensional statistical methods in economic applications, panel data models, clustered standard errors, quantile regression, and weak instruments. His most recent work explores the application of machine learning and artificial intelligence techniques to estimate causal and policy effects. Hansen teaches courses including Applied Econometrics, Machine Learning, and Statistics at Chicago Booth. Scientific Awards and Honors: Neubauer Family Faculty Fellow at Booth NSF research grant recipient National Science Foundation graduate research fellow during PhD studies Hansen has published in leading journals including the American Economic Review, Annals of Statistics, Econometrica, Journal of Business and Economic Statistics, Journal of Econometrics, Review of Economics and Statistics, and Review of Economic Studies. He is currently working on a book titled "Applied Causal Inference Powered by ML and AI" with Victor Chernozhukov, Nathan Kallus, Martin Spindler, and Vasilis Syrgkanis.

• Computational Neuroscience
• Spacetime Connectomics
• Neurotwin Models
• +۵ مورد دیگر

Jakub Vohryzek is a postdoctoral researcher at the Computational Neuroscience (CNS) Group at University Pompeu Fabra in Barcelona, supervised by Prof. Gustavo Deco. His work focuses on spacetime connectomics and whole-brain modeling, particularly in neurodegenerative disorders and psychedelic neuroscience. He holds a DPhil from the University of Oxford, where he studied under Prof. Morten Kringelbach. Research Interests: Spacetime connectomics Psychedelic-induced brain state transitions Neurotwin models for personalized medicine Cognitive and clinical applications of whole-brain dynamics Current projects include developing neurotwin models under a European grant for neurodegenerative treatments, investigating brain state dynamics in mindfulness therapy, and modeling psychedelic effects on Alzheimer’s disease. His recent work emphasizes low-dimensional brain network interactions and functional hierarchy perturbations. His research has explored connectivity profiles, oscillatory restoration in dementia, and algorithmic agent approaches to neuropsychiatric disorders. He collaborates on open-science initiatives like Brainhack and advocates for inclusive conference design.

• Applied Economics
• Economic Integration
• Macroeconomics
• +۴ مورد دیگر

Cecilio Tamarit is a Professor of Applied Economics at the University of Valencia, where he holds a Jean Monnet Chair and coordinates the Research Group on Economic Integration (INTECO). He is also Vice President of the Free Association of Economics (ALDE) and President of the Economics Committee of the National Commission for the Evaluation of Research Activity (CNEAI). Master's in Economics, College of Europe (Bruges) Extraordinary Doctorate Award, University of Valencia (1992) Schuman Scholar, European Parliament (1988) Visiting Scholar, University of Nottingham (1992) Senior Fellow, Wharton School, University of Pennsylvania (1996) His research focuses on applied economics, macroeconomics, and European economic integration, with strong emphasis on modeling and policy analysis. He has contributed extensively to understanding economic convergence, fiscal policy, and international trade dynamics within the EU framework. The 15 most recent publications reflect a consistent focus on empirical and policy-oriented economics, spanning macroeconomic modeling, international trade, public policy, and financial economics. His work frequently appears in high-impact journals, demonstrating sustained scholarly engagement in applied economic research. Scientific Awards: Extraordinary Doctorate Award in 1992 from the University of Valencia He has advised numerous research projects and led major evaluation initiatives in economic research. While specific grants are not listed, his leadership roles in national evaluation bodies and research groups suggest significant involvement in funded research and policy advising. He has directed the European Documentation Center at the University of Valencia and served as an advisor to the Spanish government. He leads the INTECO research group, focusing on economic integration and policy modeling, contributing to both academic and policy debates in European economics.

Vall Castelló, Juditمشاهده پروفایل

استاد

• Health Economics
• Labour Economics
• Public Policy Evaluation
• +۳ مورد دیگر

Judit Vall Castelló is a Full Professor in the Department of Economics at the Universitat de Barcelona and a key researcher at the Institut d’Economia de Barcelona (IEB-UB), where she serves as Director of the Public Policies Research Program. She is also an external affiliated researcher at CRES-UPF and a Research Fellow at IZA. Her academic affiliations reflect a strong commitment to interdisciplinary research in public policy and applied economics. Her research focuses on the evaluation of public policies, particularly in Health Economics and Labour Economics . She employs advanced econometric methods to assess the causal impact of policy interventions on health outcomes, labor market dynamics, and social inequalities. Her work often uses quasi-experimental designs and natural experiments to draw robust conclusions. The trends in her recent publications reveal a consistent engagement with pressing societal issues such as healthcare access, aging populations, unemployment, mental health, and policy reforms. Her studies span multiple countries and leverage large administrative datasets, contributing significantly to both academic literature and evidence-based policymaking. Scientific Awards: ICREA Academia (2022) Fulbright-Schuman Grant Robert Solow Postdoctoral Fellowship Pre-doctoral Marie Curie Research Fellow Judit Vall Castelló has advised numerous PhD and Master’s students in economics and public policy, though specific names are not listed. She has secured competitive research funding through national and international programs, including collaborations with NBER, UNICEF, and Cambridge University. Her research has informed policy debates in Europe and beyond. She is actively involved in research teams at IEB and CRES-UPF, contributing to collaborative projects on health systems, labor markets, and fiscal federalism. Her leadership in the Public Policies Research Program fosters interdisciplinary dialogue and innovation in policy evaluation.

Carlos Castilloمشاهده پروفایل

استاد پژوهش

• Algorithmic Fairness
• Social Computing
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Carlos Castillo is an ICREA Research Professor at Universitat Pompeu Fabra, leading the Social and Responsible Computing Research Group. Their work focuses on algorithmic fairness, social computing, and mitigating bias in AI systems across criminal justice, education, healthcare, and hiring. Key projects include the Horizon Europe FINDHR initiative to detect discrimination in algorithmic hiring, causal inference studies on recidivism risk prediction, and analyzing gender biases in student evaluations. Research Interests: Algorithmic fairness, bias mitigation in AI systems, social data ethics, criminal justice analytics, education technology, and health informatics. Notable contributions include the FA*IR fair ranking algorithm and foundational work on auditing algorithms in digital health. Recent Trends in Articles: Recent work emphasizes interdisciplinary applications of algorithmic fairness—e.g., improving representativeness in hiring datasets, analyzing disparities in medical AI models, and addressing bias in student satisfaction surveys. Publications also explore radicalization pathways via recommendation systems and the societal impact of algorithmic decision-making. Awards: Best Paper Awards in CIKM 2022 (Francesco Fabbri), ICAIL 2019 (Marius Miron), and ISCRAM 2013 (Muhammad Imran). Grants: Leads the Horizon Europe FINDHR project and collaborates with the European Commission on algorithmic discrimination research. Labs/Teams: Directs the Social and Responsible Computing Group, focusing on interdisciplinary projects with PhD students and industry partnerships.

Enrique Acebo Moralمشاهده پروفایل

استادیار

• Eco-innovation
• Twin Transition (Green and Digital)
• New Space Economy
• +۴ مورد دیگر

Dr. Enrique Acebo Moral is an Assistant Professor in Management at the University of León's Department of Management and Business Economics, affiliated with the Faculty of Economics and Business. His work bridges eco-innovation , green-digital twin transition , and the new space economy , utilizing causal inference and econometric methods to study sustainable development and technological adaptation in firms. Education: PhD in Business Economics (Summa Cum Laude, International Mention) from the University of León (2022) His research explores how business ecosystems and sustainable innovation are shaped by policy tools like R&D grants, with a focus on multi-level innovation policy frameworks and financial constraints in technology adoption. Publications in Industry and Innovation , Science and Public Policy , and related journals demonstrate his expertise in econometric modeling of innovation dynamics. Recent articles analyze topics such as the heterogeneous impact of government support , complementary/substitutive stakeholder effects , and university-industry knowledge flows , reflecting his interdisciplinary approach to innovation management. His work has been cited over 90 times across Dimensions metrics. Awards: Best Reviewer Award (Industry and Innovation, 2022) PhD FPU Fellowship (2019-2022) Extraordinary Master's Prize (2019) He teaches operations management , innovation management , and conducts workshops on causal inference methodologies like Directed Acyclic Graphs (DAGs). Active in academic service as ACEDE Operations and Technology Division Coordinator and Social Media Editor for Industry and Innovation .

• Computational Neuroscience
• Neuroscience
• Biophysics
• +۳ مورد دیگر

Gustavo Deco is a Research Professor at the Institució Catalana de Recerca i Estudis Avançats (ICREA) and holds a Professorship (Catedrático) at Pompeu Fabra University (UPF). He leads the Computational Neuroscience Group and directs the Center of Brain and Cognition at UPF. His research focuses on computational models of brain dynamics, integrating biophysics, neuroimaging, and complex systems principles. Deco’s academic journey includes a PhD in Physics (1987, thesis on Relativistic Atomic Collisions), postdoctoral work at the University of Bordeaux (France) and University of Giessen (Germany), and a Habilitation in Computer Science (1997, Technical University of Munich). He has led computational neuroscience research at Siemens Corporate Research Center (1990–2003) and pioneered whole-brain modeling frameworks like The Virtual Brain (TVB). His research interests span critical brain dynamics, non-equilibrium thermodynamics in neural systems, psychedelics’ effects on brain hierarchy, and clinical applications of computational models in disorders such as Alzheimer’s and depression. Recent work emphasizes turbulence-like dynamics in healthy and diseased brains, and biomarker discovery using AI-driven simulations. Deco’s articles (2024–2025) explore topics like entropy production in brain networks, psychedelics-induced flattening of functional hierarchies, sleep-like dynamics post-stroke, and the role of long-range connections in global brain communication. His work bridges theoretical models with clinical insights, aiming to advance personalized neurology and digital brain research.

Ricard Gavaldàمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Healthcare Analytics
• +۳ مورد دیگر

Ricard Gavaldà is a Professor in the Department of Computer Science at Universitat Politècnica de Catalunya (UPC), affiliated with the LARCA research group. Since February 2020, he has been on academic leave to work full-time at Amalfi Analytics, focusing on healthcare data analytics. His research interests include Machine Learning, Data Mining, and their applications to healthcare and social good. He has supervised numerous PhD students and contributed to impactful projects in clinical decision support, traffic prediction, and energy-efficient systems. Education details are not explicitly mentioned in the provided texts. His work spans data stream mining, algorithmic frameworks (e.g., MOA), and healthcare informatics. He has co-founded Amalfi Analytics to develop AI-driven solutions for healthcare management. Notable recent activities include co-chairing the Nectar Track at ECML PKDD 2025 and organizing workshops on Data Science for Social Good. Key technical contributions include methods for adaptive learning, probabilistic modeling, and interpretable AI systems. His research bridges theoretical foundations and real-world applications, with a focus on improving healthcare outcomes and sustainable practices.