جست‌وجوی استاد و پژوهشگر

• Economic Growth
• Health Economics
• Macroeconomics
• +۳ مورد دیگر

Giovanni Trovato is a Professor of Economic Statistics at the University of Rome Tor Vergata. His research focuses on economic growth, health economics, macroeconomics, and semiparametric models. He has published extensively on topics such as the impact of organized crime on economic development, macroprudential policies, and healthcare system efficiency. Trovato’s work often combines theoretical frameworks with empirical analyses, addressing issues like fiscal consolidation effects, human capital accumulation, and institutional quality measurement. His recent studies include investigations into the relationship between taxation and growth, life expectancy disparities in Europe, and the role of health amenable deaths in social value assessments. He has contributed to understanding corruption’s economic consequences and the dynamics of credit volatility. His research has been disseminated through leading journals and conferences, reflecting his interdisciplinary approach to economics and statistics. Education details are not explicitly listed, but his academic career suggests advanced training in econometrics and economic theory. His articles span from 2001 to 2025, demonstrating sustained contributions to multiple subfields. Notable works include Organized Crime, Corruption, and Economic Growth (2025) and Human capital-based growth with depopulation and class-size effects (2024). Trovato’s work emphasizes empirical rigor and policy relevance, often employing innovative statistical methodologies like finite mixture models and frontier analysis.

Paul Rilstoneمشاهده پروفایل

استاد

• Econometrics
• Finite Sample Econometrics
• Duration Analysis
• +۳ مورد دیگر

Paul Rilstone is a Professor in the Department of Economics at York University's Faculty of Liberal Arts & Professional Studies. He has been teaching at York since 1995, with prior positions at Western University (BA 1987) and Laval University in Quebec. His research focuses on finite sample econometrics, duration analysis, nonparametric estimation techniques, and Russian literature. He has held visiting roles at Wisconsin, Virginia, Michigan, Toronto, Rochester, and Statistics Canada. His academic career includes over three decades of contributions to econometric theory and applications. Key research areas involve improving estimation methods for nonlinear models, analyzing duration processes in labor markets and public health contexts, and advancing nonparametric statistical techniques. Recent work addresses pandemic modeling and policy impacts through econometric frameworks. Rilstone's publications emphasize higher-order asymptotic expansions, semiparametric efficiency, and innovative estimation strategies. His work bridges theoretical econometrics with applied policy analysis, particularly in labor markets and healthcare systems. No specific awards are listed in available records, though his extensive publication history indicates sustained scholarly impact.

Volodymyr Mininمشاهده پروفایل

استاد

• Biostatistics
• Infectious Disease Modeling
• Phylogenetics
• +۴ مورد دیگر

Volodymyr Minin is a Professor in the Department of Statistics at the University of California, Irvine, where he also serves as Associate Director of the Infectious Disease Initiative and Honors Program Director for the School of Information & Computer Sciences. Additionally, he is Co-Director of the Irvine Summer Institute in Biostatistics and Undergraduate Data Science (ISI-BUDS), which recently welcomed its fourth cohort of 16 undergraduate students from across the country. Professor Minin leads an active research group focused on developing and applying statistical methods for infectious disease modeling, phylogenetics, and population dynamics. His group holds weekly journal club meetings on Fridays where members present and discuss recent research papers related to stochastic and statistical modeling approaches in epidemiology and evolutionary biology. His research interests span Biostatistics , Infectious Disease Modeling , Phylogenetics , Bayesian Statistics , Population Dynamics , Epidemiological Modeling , and Stochastic Processes . Minin's recent publications demonstrate a strong methodological focus with practical public health applications, particularly in infectious disease dynamics. His work integrates multiple data sources including genetic sequences, case reports, and wastewater surveillance to improve epidemiological inference. Key themes include addressing reporting delays in real-time analyses, developing more accurate methods for estimating the effective reproduction number, and investigating transmission dynamics of pathogens like SARS-CoV-2 and tuberculosis. Professor Minin has mentored numerous students through their academic careers, including Catalina Medina who recently defended her dissertation and is starting as an Assistant Professor at CSU Channel Islands, and students like Jessalyn Sebastian and Christian Bernal Zelaya who have received recognition at conferences like WNAR 2025 where Christian won the best student oral presentation award. His former students include Andy Magee, Jon Fintzi, Michael Karcher, Jason Xu, Jane Lange, Peter Chi, Julia Palacios, and Soyoung Ryu. His research group actively collaborates with public health organizations and participates in initiatives like the Infectious Disease Initiative at UCI. The group maintains an active GitHub presence with repositories documenting their journal club activities and sharing resources for stochastic and statistical modeling. The group's work has important implications for understanding and controlling infectious disease outbreaks through advanced statistical modeling approaches.

Yonghong Anمشاهده پروفایل

استاد

• Microeconometrics
• Industrial Organization
• Applied Microeconomics
• +۴ مورد دیگر

Yonghong An is a Professor of Economics at Texas A&M University, specializing in microeconometrics and its applications in industrial organization and labor economics. His research emphasizes robust econometric methodologies for analyzing strategic interactions and agent behavior in economic models. Education: Ph.D. in Economics from Johns Hopkins University (2011) Research interests include structural econometric modeling, public goods provision, auction theory, and policy evaluation. His work often integrates theoretical frameworks with empirical analysis to address questions in industrial organization and labor markets. Key publications focus on topics such as intergenerational mobility, merger efficiencies, and public procurement dynamics. Recent work explores algorithmic collusion detection and cost-based contracting. Notable Awards: Best Poster Award at 2016 EAERE Annual Conference He has advised on numerous research projects and contributes to academic discussions on journal pricing and research dissemination. His collaborative efforts include studies on healthcare markets and public policy implications of economic models.

Harini Hapuarachchiمشاهده پروفایل

پژوهشگر ارشد

• Quantum Technology
• Plasmonics
• Quantum Optics
• +۳ مورد دیگر

Dr. Harini Hapuarachchi is a Vice Chancellor’s Postdoctoral Research Fellow at the School of Science, RMIT University, within the STEM College. Previously, she served as a Research Fellow at the ARC Centre of Excellence in Exciton Science. Her research focuses on quantum systems such as nitrogen-vacancy centers in diamond, color centers in 2D materials, and semiconductor quantum dots, leveraging plasmonic interactions to advance quantum technologies. Her work spans theoretical and experimental studies in nanophotonics, quantum optics, and nanomaterials engineering. Research interests include plasmon-quantum emitter interactions, quantum control mechanisms, and the development of hybrid nanostructures for optoelectronic applications. Her contributions address challenges in quantum sensing, quantum computing, and biomedical plasmonic systems. Her publications explore topics such as nitrogen-doped diamond color centers, orientation-generalized plasmonic models, and quantum master equations. These studies highlight advancements in quantum emitter manipulation and plasmonic field engineering. She is open to supervising PhD and Master’s students in these areas. Dr. Hapuarachchi’s research has been applied to fields like temperature sensing via plasmonic nanoparticles and long-term water pipe condition assessment using semiparametric models. Collaborations include projects on nanohybrids for tumor imaging and IVF incubator design.

Gaurab Aryalمشاهده پروفایل

دانشیار

• Empirical Industrial Organization
• Econometrics
• Market Design
• +۱ مورد دیگر

Gaurab Aryal is an Associate Professor of Economics at Boston University's Department of Economics, with previous positions at Washington University in St. Louis and the University of Virginia. He holds a Ph.D. in Economics from The Pennsylvania State University and specializes in empirical industrial organization. His research focuses on market design, pricing strategies, and competitive dynamics in industries such as airlines, insurance, and procurement. Key interests include econometric modeling of auctions, analysis of collusion mechanisms, and the impact of information asymmetries on market outcomes. Professor Aryal's work has appeared in leading journals including the Review of Economic Studies and American Economic Review, with recent studies examining airline subcontracting patterns, multidimensional insurance markets, and Cournot oligopoly frameworks. His research integrates theoretical modeling with innovative empirical approaches to address real-world competition policy questions. He has received multiple research grants including the Bankard Fund for Political Economy grant and Weidenaum Center award, supporting investigations into coordinated market behaviors and institutional design. Professor Aryal actively mentors graduate students and serves on departmental committees, including PhD admissions and executive committees. He teaches courses on market structure, auction theory, and empirical industrial organization.

• Statistics
• Probability
• Markov Chain Monte Carlo
• +۶ مورد دیگر

Professor Yves Atchade is a faculty member at the Department of Mathematics and Statistics at Boston University, holding the Duan Family Faculty Fellow of Data Science position. He leads the FORMES research group focused on statistical methods for environmental sciences. His work bridges probability, high-dimensional computation, and applied environmental modeling. Current projects include large-scale Bayesian inference , deep learning for rainfall prediction in West Africa , and inverse problems in remote sensing . Collaborations with institutions like ENSEA, Abidjan and the TAHMO Foundation drive environmental sensor network deployments in Côte d'Ivoire. His research emphasizes MCMC algorithm design and unbiased Monte Carlo methods , with applications spanning environmental science, machine learning, and high-dimensional statistics. Recent publications explore unbiased MCMC , cyclical sampling , and Bayesian PINNs . Scientific contributions include: Unbiased MCMC with Couplings (2020) High-dimensional Bayesian Computation (2018) Efficiency bounds in semiparametric models (2020) Adaptive MCMC Confidence Intervals (2016) He actively mentors students and postdocs, with methodological developments in Markov chain theory , stochastic optimization , and Monte Carlo variance reduction . The FORMES group welcomes inquiries from prospective researchers via email at atchade@bu.edu .

Alan Duncanمشاهده پروفایل

استاد

• Economic Policy
• Public Finance
• Labour Market Dynamics
• +۷ مورد دیگر

Professor Alan Duncan is the Director of the Bankwest Curtin Economics Centre and Bankwest Professor of Economic Policy at Curtin University's Curtin Business School. He holds a DPhil in Economics from the University of York and a BA (Honours) in Economics from the University of Manchester. His research focuses on economic and social policy evaluation, taxation, public finance, labour markets, poverty, inequality, and econometric modelling. He has advised governments and international organizations on tax policy, pensions, and welfare, and has received the Frisch Medal from the Econometric Society in 2000. Key contributions include studies on migration impacts, housing affordability, gender equity, and policy analysis. His work spans academic journals like Econometrica and European Economic Review , as well as influential policy reports through BCEC. Education: DPhil (Economics, York), BA Econ (Hons, Manchester) Roles: BCEC Director (2013–present), Former NATSEM Director, Head of Nottingham School of Economics Awards: Frisch Medal (2000), R I Downing Fellowship (2002) Research interests emphasize applied economics with a focus on policy relevance. Notable publications analyze migration policy effects, gender pay gaps, and housing reforms. His BCEC-led reports address WA-China trade dynamics, WA economic diversification, and social issues like poverty and wellbeing.

Yue Zhaoمشاهده پروفایل

مدرس

• Nonparametric Statistics
• Semiparametric Multivariate Dependence Modeling
• Copula Methods
• +۵ مورد دیگر

Dr. Yue Zhao is a Lecturer in Statistics at the Department of Mathematics, University of York (equivalent to Assistant Professor in North America). She holds a PhD in experimental cosmology from Princeton University (2010) and a second PhD in statistics from Cornell University (2015). Her postdoctoral research included positions at McGill University (2015-16) and KU Leuven (2016-19). She serves as Director of the MSc in Statistics and Computational Finance program. Her research focuses on nonparametric/semiparametric multivariate dependence modeling (copulas), high-dimensional statistics, survival analysis, and statistical inference for neural networks. She actively supervises PhD students and welcomes applications in copula methods, estimating equations, and high-dimensional statistical problems. Dr. Zhao has published extensively in top journals like Annals of Statistics and Scandinavian Journal of Statistics , with work spanning theoretical advancements and applied statistical methodologies. Her research activities include peer-review for journals like Statistics and Computing and invited talks at international conferences. Professional affiliations include roles in the York University Statistics group, and she maintains an active research network through collaborations across Europe and North America.

Marinho Bertanhaمشاهده پروفایل

دانشیار

• Econometrics
• Causal Inference
• Applied Microeconomics
• +۵ مورد دیگر

Marinho Bertanha is a tenured Associate Professor of Economics at the University of Notre Dame, serving as concurrent faculty in Statistics and a faculty fellow at the Kellogg Institute. His academic work bridges econometrics and applied microeconomics with significant contributions to causal inference methodologies. His educational background includes a Ph.D. in Economics from Stanford University (2015), an M.A. from Fundação Getúlio Vargas in Rio de Janeiro (2009), and a B.A. from Universidade de São Paulo (2006). Prior to his current position, he completed postdoctoral work at the University of Louvain and served as a visiting professor at the University of Chicago. Bertanha's research focuses on causal inference , resampling methods , and policy evaluation , with particular expertise in regression discontinuity designs, bunching estimation, and permutation testing. His methodological innovations address critical challenges in econometric identification and statistical inference, especially in contexts with strategic reporting and imperfect compliance. His publication record shows consistent high-impact output in top journals including the Journal of the American Statistical Association , Journal of Econometrics , and Review of Economics and Statistics . Recent work demonstrates increasing focus on practical implementation through software development (Stata and MATLAB packages) that has become standard in empirical economics research. Through his concurrent appointment in Statistics and faculty fellowship at the Kellogg Institute, Bertanha contributes to interdisciplinary research initiatives focusing on economic policy evaluation and statistical methodology development. His current work-in-progress examines causal effects in matching mechanisms, returns to education with strategic reporting, and tax elasticity estimation across multiple countries.

Sara Pudasمشاهده پروفایل

دانشیار

• cognitive aging
• long-term memory
• brain structure
• +۳ مورد دیگر

Sara Pudas is an Associate Professor at Umeå University's Department of Psychology, specializing in cognitive aging and long-term memory mechanisms. Her research investigates brain structure and function relationships, biological markers of aging, and lifestyle influences on cognitive health. Research focuses on longitudinal predictors of dementia, neuropsychiatric symptom trajectories, and heterogeneity in brain aging patterns. Work integrates neuroimaging, epigenetic biomarkers, and advanced statistical modeling to understand cognitive resilience and decline across the lifespan. Recent publications examine telomere dynamics, DNA methylation biomarkers for Alzheimer's prediction, and educational impacts on cognitive differences across European and US cohorts. Methodological contributions include Bayesian approaches for longitudinal data with dropout and explainable AI for clinical neuroimaging applications.

Maria Josefssonمشاهده پروفایل

دانشیار

• Statistics
• Gerontology
• Cognitive Aging
• +۶ مورد دیگر

Maria Josefsson is an Associate Professor (Senior Lecturer) and Docent in Statistics at Umeå School of Business, Economics and Statistics (USBE), Umeå University. She holds an affiliation as Research Fellow at the Centre for Demographic and Aging Research (CEDAR), also at Umeå University. Her research focuses on statistical methods for studying age-related cognitive change, including dementia risk prediction, longitudinal data analysis, and causal inference in aging cohorts. She leads the Stat4Reg research group and has contributed to projects such as RECO (rehabilitation for cognitive decline in stress-related disorders) and iPARK (Parkinson’s disease interventions). Her work integrates epidemiological approaches with statistical modeling to address cognitive aging mechanisms, including the role of herpesviruses, telomere dynamics, and epigenetic markers. Key areas include causal mediation analysis, sensitivity to non-ignorable dropout, and multivariate outcomes in longitudinal studies. She has also explored sociodemographic factors affecting mental health during pandemics and disparities in violence against indigenous populations. Josefsson has authored/co-authored over 50 peer-reviewed articles spanning statistical methodology, cognitive neuroscience, and public health. Her methodological contributions include Bayesian semiparametric approaches and pattern mixture models. She collaborates with multidisciplinary teams on projects such as the Betula longitudinal cohort study and blood-based biomarker evaluations for Alzheimer’s disease prediction.

Maria Karlssonمشاهده پروفایل

دانشیار

• Statistics
• Econometrics
• Education Technology
• +۳ مورد دیگر

Maria Karlsson is an Associate Professor at the Department of Statistics, Umeå School of Business, Economics and Statistics (USBE), Umeå University. She also serves as a Student Counsellor. Her research focuses on statistical methodology, particularly in truncated and censored regression models, as well as pedagogical innovations in statistics education. She has contributed to projects like Stat4Reg and led initiatives such as Analysis of demand equations using mixtures of Tobit models (2013–2015) and Estimation of labor market policy program effects in the presence of interference between individuals (2013–2014). Educational Background: Holds the title of Distinguished university teacher , reflecting her expertise in pedagogy. Her academic qualifications emphasize both statistical rigor and educational effectiveness. Research Interests: Her work bridges statistical theory and practical applications, including labor market policy evaluation, causal inference in observational studies, and integrating flipped classrooms with MOOCs. She also explores ethical frameworks for AI in education and innovative writing practices in statistics curricula. Publications Overview: Karlsson's publications span statistical methodology (e.g., truncSP R package development) and pedagogical advancements. Recent work highlights include addressing ethical AI challenges and advancing active learning strategies in higher education. Awards: Recognized as a Distinguished university teacher , underscoring her contributions to educational excellence. Grants & Projects: Led two major research projects on labor market policies and demand modeling, demonstrating her impact on both theoretical and applied statistics. Labs/Teams: Active member of the Stat4Reg research group, focusing on statistical methods for regression analysis and policy evaluation.

Xavier de Lunaمشاهده پروفایل

استاد

• Causal Inference
• Machine Learning
• Statistics
• +۵ مورد دیگر

Xavier de Luna is a Professor of Statistics at Umeå School of Business, Economics and Statistics (USBE) at Umeå University in Sweden. He leads the Stat4Reg Lab and is part of the Umeå SIMSAM Lab and the SINGS graduate school. His research focuses on causal inference, machine learning, and statistical methodology applied to social and health sciences. He serves as Editor of the Scandinavian Journal of Statistics (2025-2027) and has held roles as Associate Editor for Biometrics, Computational Statistics and Data Analysis, and Observational Studies. Education: PhD in Statistics from Swiss Federal Institute of Technology (1996). Prior roles include Head of the Department of Statistics at Umeå University (2009-2011) and affiliation with institutions like IFAU and the Institute of Labour Market Policy Evaluation. Research interests span causal machine learning, covariate selection, and register-based studies in health and social sciences. Key projects include using generative AI for open science and machine learning for causal discovery. His work addresses challenges like unobserved confounding and high-dimensional data. Notable contributions include methodological advances in causal inference (e.g., covariate balancing, neural networks for causal effects) and applications in health economics, retirement effects, and brain imaging studies. He has advised over 15 PhD students and secured grants from the Swedish Research Council and Wallenberg Foundation. Labs/Teams: Stat4Reg Lab (causal inference), Umeå SIMSAM Lab (register-based research), SINGS (interdisciplinary graduate school).

Chuan-Fa Tangمشاهده پروفایل

استادیار

• Statistics
• Survival Analysis
• Statistical Machine Learning
• +۹ مورد دیگر

Chuan-Fa Tang is an Assistant Professor of Statistics in the Department of Mathematical Sciences at the University of Texas at Dallas, affiliated with the School of Natural Sciences and Mathematics. He joined UTD in 2019 and teaches graduate-level courses including Applied Linear Models, Linear Statistical Models, and Nonparametric Methods. Ph.D. in Statistics from University of South Carolina (2017) M.S. and B.S. in Mathematics from National Taiwan University (2010, 2007) His research focuses on order-restricted inference , shape-constrained inference , survival analysis , and statistical machine learning , with particular interest in: Nonparametric and semiparametric models Empirical processes and likelihood methods Post-selection inference Stochastic ordering and heavy-tailed distributions His work includes developing goodness-of-fit tests for Cox models and stochastic ordering frameworks, with software implementations in R . Key publications examine uniform stochastic ordering comparisons, positive quadrant dependence testing, and Taylor's laws for heavy-tailed data. Scientific awards include: NSF DMS 2311292 grant (2023-2026) for monotonic hazard trend research He has contributed computational tools like TestUSO and LLGOF_UniCoxPH packages for statistical analysis.