جستجوی استاد راهنمای دانشگاهی

Abolfazl Safikhaniمشاهده پروفایل

استادیار

• Network Modeling
• High-Dimensional Statistics
• Spatiotemporal Models
• +۵ مورد دیگر

Abolfazl Safikhani is an Assistant Professor in the Department of Statistics at George Mason University. He holds a PhD in Statistics and Probability from Michigan State University and has held prior positions at Columbia University and the University of Florida. His research focuses on network modeling, high-dimensional statistics, spatiotemporal models, and applications in urban planning, neuroscience, and smart cities. He is an Associate Editor for Technometrics , Statistica Sinica , and Data Science in Science . He has contributed to advancements in statistical methodologies for time series analysis, including change point detection, transfer learning, and spatiotemporal modeling. His work bridges theoretical statistics with practical applications in urban growth prediction, healthcare (e.g., cancer drug response modeling), and transportation systems. Recent research trends include leveraging explainable AI for land use modeling, longitudinal omics data analysis, and structural break detection in high-dimensional systems. His publications span theoretical developments and real-world case studies, such as subway ridership during the pandemic and New York City’s taxi demand dynamics. Despite no listed awards, his editorial roles highlight his influence in statistical science. He actively mentors students and collaborates on interdisciplinary projects, emphasizing data-driven solutions for complex societal challenges.

• Macroeconomics
• Financial Regulation
• Economic Growth
• +۳ مورد دیگر

Professor Stephen Wright is a faculty member in the Department of Economics at Birkbeck Business School, part of Birkbeck, University of London. His academic role includes teaching modules such as Macroeconomics (EMEC011S6) and Introduction to Economics (EMEC013S4). His research focuses on macroeconomics, financial regulation, economic growth, and econometric methods. He has contributed to understanding stock market predictability, the Indian economy's growth dynamics, and pension scheme sustainability. His work spans theoretical and applied economics, including studies on monetary policy, corporate finance, and economic indicators. His publications address topics like predictive models, state-level economic disparities in India, and the implications of financial regulation. Collaborations include analyses of GDP estimation and pension funding challenges. He has authored monographs on topics ranging from the UK's cost of capital to actuarial pension schemes. His research often bridges empirical analysis with policy relevance, particularly in macroeconomic stabilization and financial systems. Notable projects include reports on pension contribution rates and cost-of-capital methodologies for UK regulators. His work frequently appears in journals such as the Journal of Business and Economic Statistics and Economic and Political Weekly .

• Economics
• Quantitative Analysis
• Econometrics
• +۱ مورد دیگر

Yiyi Zhou is an Associate Professor in the Department of Economics at Stony Brook University. He holds a tenure-track position and is affiliated with the Social and Behavioral Sciences Building (Office N-625). His contact information includes a publicly listed email address and an academic webpage. While his formal academic affiliation is in Economics, his published research demonstrates expertise in high-energy physics and particle detection technologies, particularly through contributions to the ATLAS experiment at CERN. His work focuses on analyzing multiparticle correlations, collision dynamics, and detector performance in heavy-ion and proton-proton collisions. Zhou's research outputs from 2016-2019 highlight advancements in understanding collective phenomena in small collision systems, centrality fluctuations, and the performance of trigger systems in high-energy environments. His studies often employ advanced statistical methods like subevent cumulant analysis to probe fundamental aspects of quantum chromodynamics.

• Longitudinal Data Analysis
• Social Policy Evaluation
• Wellbeing Across Lifecourse
• +۳ مورد دیگر

Dr Lee Bentley is a Researcher at Manchester Metropolitan University, based in the Policy Evaluation and Research Unit (PERU). He leads on the COORDINATE project within the Growing Up in Digital Europe (GUIDE) initiative, focusing on establishing a pan-European birth cohort study to assess child wellbeing. His research expertise spans quantitative social science methods, longitudinal data analysis, and the sociocontextual determinants of wellbeing across lifecourses. He holds a PhD and MSc in Social Statistics from the Cathie Marsh Institute, University of Manchester. Education PhD in Social Statistics (Manchester Metropolitan University) MSc in Social Research Methods and Statistics (Manchester Metropolitan University) Research Interests Dr Bentley's work centers on: Longitudinal data analysis methodologies Impact of social contexts on pro-social behavior and trust Disability welfare systems and policy evaluation Health inequalities and multimorbidity trends Ethnic diversity's role in social cohesion and political behavior Publications Trends His recent work emphasizes comparative policy analysis across nations, focusing on disability welfare reforms, aging populations' labor participation, and the societal impacts of immigration. Key themes include: Cross-national policy comparisons (UK/Canada/Denmark/Sweden) Longitudinal evaluation of welfare reforms Quantitative analysis of health-employment relationships Grants & Projects Central to his role is the COORDINATE project coordinating European birth cohort research networks. While specific grant details aren't listed, his work implies involvement in large-scale collaborative initiatives. Labs/Teams He contributes to the Policy Evaluation and Research Unit (PERU) at Manchester Metropolitan University, collaborating with international teams on cohort studies and policy evaluations.

Zhenyu Cuiمشاهده پروفایل

دانشیار

• Financial Engineering
• Insurance Analytics
• Operations Research
• +۵ مورد دیگر

Zhenyu Cui is an Associate Professor of Financial Engineering at the School of Business, Stevens Institute of Technology. He holds a PhD in Statistics from the University of Waterloo and a BS in Actuarial Science from the University of Hong Kong. His research focuses on financial engineering, insurance analytics, and operations research, with notable contributions to stochastic volatility models, Monte Carlo simulation, and financial systemic risk. He has published in top journals such as Mathematical Finance, SIAM Journal on Financial Mathematics, and European Journal of Operational Research. Education: PhD (2013, Statistics, University of Waterloo); MS (2010, Quantitative Finance, University of Waterloo); BS (2008, Actuarial Science, University of Hong Kong). Research Interests: Financial Systemic Risk, Monte Carlo Methods, Stochastic Volatility, Option Pricing, and Risk Management. His work bridges theoretical finance and practical applications, emphasizing robust pricing techniques and computational methods. Grants include leadership roles in NSF-funded projects on quantum algorithms for financial risk management and collaborations with institutions like Accenture and the Society of Actuaries. Awards include recognition for top-cited articles and editorial excellence.

• Saddlepoint-Based Bootstrap
• Time Series Modeling
• Longitudinal Modeling
• +۳ مورد دیگر

Dr. A. Alexandre Trindade is a Professor in the Department of Mathematics & Statistics at Texas Tech University. His research focuses on developing novel statistical methodologies for complex data structures, with applications spanning finance, physics, and environmental science. He teaches graduate courses in Time Series Analysis and Nonparametric Statistics, and serves as advisor for the undergraduate Actuarial Science Minor program. His primary research areas include: Saddlepoint-Based Bootstrap (SPBB) : Methods for approximate inference in complex models with intractable distributions Time Series & Volatility Modeling : Multivariate autoregressive models, GARCH variants, and asymmetric distributions Spatial & Longitudinal Analysis : State-space models for missing data and spatial regression techniques Tail Risk Quantification : Nonparametric estimation of systemic risk measures like CoVaR Nonparametric Inference : Density estimation and signal detection for high-energy physics His publications demonstrate consistent innovation in statistical theory, particularly in developing resampling-based inference and extending time series methodologies. Collaborative projects include interdisciplinary work with petroleum engineering, nuclear science, and finance. Dr. Trindade maintains active research partnerships with national laboratories and industry, including reliability studies for Boeing and medical device research. He has developed specialized software for multivariate time series analysis and maintains public repositories for statistical computing resources.

Anindya Royمشاهده پروفایل

استاد

• Time Series Analysis
• Nonparametric Bayesian Analysis
• High-dimensional Estimation and Inference
• +۳ مورد دیگر

Anindya Roy is a Professor of Statistics in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC). His research focuses on time series analysis, Bayesian methods, high-dimensional statistics, and applications in biomedical and engineering domains. He serves as an Area Editor for Statistical Analysis and Data Mining , and on editorial boards for Sankhya, Ser. A and Statistics in Medicine . His research interests include nonparametric Bayesian approaches, geometric constraints in statistical models, and sequential experimental design. He has received research funding from the National Science Foundation (NSF DMS–2210282). Recent work addresses privacy-preserving data synthesis, causal inference in time series networks, and fetal growth modeling. Key contributions include methodologies for high-dimensional time series with directed acyclic graphs, Bayesian approaches for relational graph estimation, and statistical techniques for medical applications such as cyclotron ion source development and cervical cancer screening risk prediction. Notable collaborative efforts involve proteomic analysis of chemical mixtures, oncology trial design, and biomarker studies. His work bridges theoretical statistics with applied problems in health sciences and engineering, emphasizing interdisciplinary impact.

Hailong Qianمشاهده پروفایل

دانشیار

• Econometric Theory
• Applied Econometrics

Hailong Qian is an Associate Professor and Chair of the Department of Economics at Saint Louis University's Richard A. Chaifetz School of Business. He also serves as Program Director for the M.S. in Applied Financial Economics. His academic career spans roles at the Federal Reserve Bank of St. Louis and consultancy positions in economics and finance. Ph.D. in Economics, Michigan State University M.A. in Economics, Fudan University, China B.S. in Mathematics, Fudan University, China His research focuses on econometric theory and applied econometrics, with emphasis on moment conditions, generalized method of moments (GMM) estimation, and efficiency analysis in statistical models. His work explores redundancies in econometric frameworks and improves estimator performance. Recent publications highlight his contributions to GMM efficiency, moment condition redundancy, and SUR model optimization. His work bridges theoretical econometric advancements with practical applications in economic modeling and policy analysis. Graduate Teacher of the Year, Chaifetz School of Business (2019 - 2020) Contact: hailong.qian@slu.edu | Office: Davis-Shaughnessy Hall, 3674 Lindell Blvd, 308, St. Louis, MO 63108 | Phone: (314)977-3866

Dennie Van Dolderمشاهده پروفایل

مدرس ارشد

• Behavioral Economics
• Experimental Economics
• Decision Theory
• +۳ مورد دیگر

Dr. Dennie Van Dolder is a Senior Lecturer in Economics at the University of Essex and Director of the Essex Centre for Behavioural Science, home to the ESSEXLab. He serves as an Associate Editor at the Journal of Economic Behavior & Organization . His research bridges behavioral economics, experimental methods, and empirical analysis of human decision-making. Education: PhD in Economics from Erasmus University Rotterdam and Tinbergen Institute (2014), supervised by Peter Wakker and Han Bleichrodt. Past Appointments: Research Fellow at University of Nottingham (2014-2017), Assistant Professor at VU Amsterdam (2017-2021), visiting positions at University of Chicago, Carnegie Mellon, and Max Planck Institute. Van Dolder’s research focuses on behavioral economics , particularly judgment and decision-making under uncertainty. He combines experimental methods with natural experiments in high-stakes environments (e.g., game shows, financial markets) to study risk preferences, cooperation, and strategic behavior. His work employs advanced microeconometric techniques and behavioral game theory. Recent publications analyze conditional cooperation in uncertain social dilemmas, loss aversion in financial decisions, and choking under pressure in competitive settings. He has contributed to journals like Games and Economic Behavior , Management Science , and Nature Human Behaviour . Van Dolder supervises PhD students, including Richie Dilip Kurian, and collaborates with institutions such as the University of Chicago and Carnegie Mellon. His work often leverages rich datasets from real-world contexts to validate theoretical models of human behavior.

Jonas Westinمشاهده پروفایل

دانشیار

• Mathematical Modeling
• Transportation Economics
• Regional Science
• +۳ مورد دیگر

Jonas Westin is an Associate Professor at the Department of Mathematics and Mathematical Statistics and a Research Fellow at the Centre for Regional Science (CERUM) at Umeå University. His research focuses on applying mathematical methods and models to address social science challenges, particularly in transportation, regional development, and environmental policy. He teaches courses in mathematical modeling and project courses for civil engineering students, and is recognized as a university teacher. His research interests include transportation economics, input-output analysis, and operations research, with a focus on optimizing freight networks, evaluating infrastructure policies, and modeling regional accessibility. He has contributed to projects analyzing sustainable aviation, maritime safety, and cross-border infrastructure planning in Northern Europe. Westin collaborates with institutions like Trafikverket (Swedish Transport Administration) and the Nordic countries’ transport networks. His work bridges theoretical mathematical modeling with practical policy analysis, emphasizing the implications of transport policies on regional competitiveness and environmental sustainability. Notable projects include the Botnia-Atlantica corridor analysis and studies on fossil-free regional aviation. Affiliations: Associate Professor, Department of Mathematics and Mathematical Statistics Research Fellow, CERUM (Centre for Regional Science) Key Research Themes: Transportation Network Optimization Regional Economic Impact Analysis Environmental Policy Modeling His recent publications highlight innovative approaches to freight modeling, maritime safety metrics, and cross-border infrastructure coordination. Westin’s interdisciplinary work reflects a commitment to addressing complex societal challenges through rigorous quantitative methods.

Arash Alooshمشاهده پروفایل

استادیار

• International Finance
• Forensic Finance
• FinTech
• +۳ مورد دیگر

Dr. Arash Aloosh is an Assistant Professor of Finance at the Dublin City University (DCU) Business School. He holds a PhD in Finance from BI Norwegian Business School (2016) and was a visiting scholar at Columbia Business School in New York. His research focuses on FinTech, sustainability, and interdisciplinary topics such as forensic finance, social media's impact on financial markets, and international finance dynamics. Education: PhD in Finance, BI Norwegian Business School, 2016 Visiting Scholar, Columbia Business School, 2014–2016 Research Interests: International Finance Forensic Finance FinTech Innovations Social Media & Finance Interactions His recent work explores cryptocurrency trading anomalies, meme stock behavior, and the unintended consequences of economic sanctions on public health. Key themes include market efficiency, regulatory challenges in digital assets, and cross-border financial dynamics. Despite extensive publication activity, no scientific awards are explicitly mentioned in the provided texts. No grants, advising roles, or laboratory affiliations are detailed.

Ted Juhlمشاهده پروفایل

استاد

• Econometrics
• Time Series Analysis
• Nonparametric Models
• +۳ مورد دیگر

Ted Juhl is the O. Maurice Joy Professor and Area Director of Finance at the University of Kansas School of Business. His research focuses on econometric methodologies, particularly in time series analysis, nonparametric models, panel data, and quantile regression. He has contributed to understanding slope heterogeneity in panel data models and testing for structural stability in econometric frameworks. His work bridges theoretical econometrics with practical applications in finance and policy analysis. His research interests emphasize advancing methodologies for analyzing complex economic and financial datasets, including cointegration analysis, predictive regression, and model diagnostics. Notable contributions include addressing issues of heteroskedasticity in fixed effects models and evaluating the impact of R&D funding on scientific productivity in academic chemistry. Recent publications explore topics like rolling regression estimator distributions, policy heterogeneity in corporate finance, and the implications of cross-sectional correlation in panel data. While no specific awards are listed, his extensive publication record reflects sustained scholarly impact in econometric theory and applications. Teaching focuses on econometrics at the graduate level, aligning with his research expertise. His professional address is Capitol Federal Hall, Room 4113, Lawrence, KS. No advising or grant details are explicitly stated in the provided materials.

Christopher S. Hoagمشاهده پروفایل

استاد

• Financial Economic History
• Banking History
• Financial Markets
• +۴ مورد دیگر

Christopher S. Hoag is the George M. Ferris Professor of Corporation Finance and Investments at Trinity College's Department of Economics. He has been affiliated with Trinity College since 2010. His education includes a Ph.D. from the California Institute of Technology (Caltech) and a B.A. from Amherst College. Hoag's research focuses on financial economic history, particularly banking and financial markets in the U.S. during the 19th and 20th centuries. His work examines pre-Federal Reserve crisis management mechanisms like clearinghouse loan certificates, bank window dressing practices, and technological advancements in capital market information systems. He also contributes to applied microeconomic theory. His recent publications analyze historical financial crises (e.g., 1884, 1893), interbank lending systems, and the role of telegraph technology in market information flows. Collaborative works include methodological econometric studies and analyses of executive decision-making during crises. Hoag's research has been published in journals such as the International Journal of Economics and Finance, North American Journal of Economics and Finance, and the Journal of Economic History. He maintains an active presence in academic discourse through working papers and conference presentations. No scientific awards or grants are explicitly mentioned in the provided materials. He advises no listed students but collaborates with researchers like Mark Stater and Kamal Lamsal. His office is located at Downes Memorial 302, and his email is Christopher.Hoag@trincoll.edu .

Michael Sinkeyمشاهده پروفایل

دانشیار

• Econometrics
• Sports Economics
• Behavioral Finance
• +۳ مورد دیگر

Michael Sinkey is an Associate Professor of Economics at the University of West Georgia's Richards College of Business, Department of Economics. He specializes in econometrics, sports economics, and behavioral finance. He has taught courses such as Statistics for Business II, Economics of Sports, Forecasting, and Business Analytics Capstone since 2020. Education: B.B.A. in Economics from University of Louisville (2005), M.A. and Ph.D. in Economics from The Ohio State University (2006, 2011). Research focuses on topics like socioeconomic impacts on labor contracts in sports, cognitive biases in expert decision-making, and market efficiency in betting markets. His work combines empirical analysis with behavioral theories, particularly in non-traditional economic environments like sports and gambling. Recent publications explore the intersection of sports economics and labor market dynamics, as well as behavioral finance principles applied to betting markets. His 2025 study examines socioeconomic factors in MLB contract timing, while earlier works analyze expert belief revision and hot-hand fallacy in college football betting. No scientific awards explicitly listed, but his research demonstrates significant contributions to behavioral and sports economics. Teaching responsibilities include advanced statistical methods and capstone projects in business analytics.

Gongjun Xuمشاهده پروفایل

دانشیار

• Latent Variable Models
• Psychometrics
• Statistical Learning
• +۶ مورد دیگر

Gongjun Xu is an Associate Professor of Statistics and courtesy Associate Professor of Psychology at the University of Michigan. He leads the Master's Program in Applied Statistics and holds positions in the Department of Statistics within the College of Literature, Science, and the Arts (LSA). His research focuses on latent variable models, psychometrics, statistical learning, and high-dimensional statistics. Xu completed his Ph.D. in Statistics at Columbia University and B.S. at the University of Science and Technology of China (USTC). His research interests include advanced statistical methodologies for educational and psychological measurement, such as cognitive diagnosis models, item response theory, and network data analysis. He has contributed to high-dimensional inference, survival analysis, and machine learning applications in healthcare. Xu serves as Co-Editor-in-Chief of the Journal of Educational and Behavioral Statistics and holds editorial roles in multiple top-tier journals. Xu has been recognized with prestigious awards including the AERA Research Methodology Award (2025), ICSA President’s Citation (2024), and COPSS Emerging Leader Award (2023). His team advises numerous graduate and undergraduate students, many of whom pursue academic and industry roles in statistics, data science, and education. Key collaborations include work on educational testing, health analytics, and AI-driven scientific methods via the Schmidt AI in Science Fellowship. He oversees a vibrant research group with active projects in latent variable modeling, differential item functioning detection, and scalable Bayesian methods for large-scale assessments. His lab emphasizes interdisciplinary applications spanning education, healthcare, and social sciences.