جست‌وجوی استاد و پژوهشگر

Dimitris N. Politisمشاهده پروفایل

استاد

• Time Series Analysis
• Nonparametric Statistics
• Bootstrap Methods
• +۶ مورد دیگر

Dimitris N. Politis is a Distinguished Professor in the Department of Mathematics and the Halicioglu Data Science Institute at the University of California, San Diego. He holds the prestigious Halicioglu Data Science Institute Chancellor's Endowed Chair II position and has been affiliated with UCSD since 1997, progressing from Associate Professor to his current distinguished position. His educational background includes a Ph.D. in Statistics from Stanford University (1990), along with multiple master's degrees in Statistics, Mathematics, and Computer and Systems Engineering from Stanford and Rensselaer Polytechnic Institute. Professor Politis's research focuses on advanced statistical methodologies, with particular expertise in: Time Series and Random Fields analysis Computer-Intensive Methods in Statistics Resampling and Subsampling for Dependent Observations Spatial Statistics and Point Processes Nonparametric Spectral and Probability Density Estimation Model-free Prediction and Regression Information Theory and Signal Processing Econometric Analysis of Financial Time Series His scholarly output includes over 100 journal papers and several influential books, most notably "SUBSAMPLING" (1999), "MODEL-FREE PREDICTION AND REGRESSION" (2015), and "TIME SERIES: A FIRST COURSE WITH BOOTSTRAP STARTER" (2020), which has become a key educational resource in the field. Professor Politis has received numerous prestigious awards and honors: Guggenheim Fellowship (2011) Fellow of the American Statistical Association (2011) Fellow of the Institute of Mathematical Statistics (2004) Distinguished Author Award from the Journal of Time Series Analysis (2020) Econometric Theory Multa Scripsit Award (2013) Tjalling C. Koopmans Econometric Theory Prize (2012) He has been principal investigator on numerous NSF and NIH grants, including current funding for "Computer-intensive methods for dependent and complex data" (NSF DMS 24-13718, 2024). Professor Politis has held significant leadership roles, including serving as Chair of the Faculty Council of the Halicioglu Data Science Institute (2019-2023) and Associate Director (Founding) of the Institute (2018-2024). As a co-founder of the International Society for NonParametric Statistics, Professor Politis has made substantial contributions to the organization of major conferences and workshops in his field, including the First Conference of the International Society for NonParametric Statistics in 2012. His editorial work includes serving as Co-Editor of the Journal of Time Series Analysis since 2013 and Senior Editor for the ACM/IMS Journal of Data Science since 2022.

• Financial Economics
• Portfolio Optimization
• Stochastic Dominance
• +۵ مورد دیگر

Professor Wing-Keung Wong is a distinguished academic at the Department of Finance, Asia University . With over 187 scholarly papers and 638 citations, his work spans critical areas in financial economics and quantitative finance. Current affiliation: Asia University, Department of Finance Past affiliations: National University of Singapore, Chinese University of Hong Kong, Erasmus University Rotterdam Research Themes include: Portfolio optimization and stochastic dominance theory Market efficiency analysis across diverse financial instruments Behavioral finance and investor decision-making models Risk measurement with VAR and CVaR frameworks International financial market integration studies Quantitative trading system development Key Article Trends reveal consistent focus on empirical finance, mathematical modeling, and decision science applications in portfolio management and market anomalies.

• Multivariate Statistics
• Statistical Decision Theory
• Asymptotic Methods
• +۳ مورد دیگر

Martin Bilodeau is a full professor in the Department of Mathematics and Statistics at Université de Montréal. He holds a Ph.D. from the University of Toronto (1986) and is an Associate of the Society of Actuaries (ASA) since 1993. His research focuses on multivariate statistics, statistical decision theory, asymptotic methods, and robust statistics. Bilodeau has authored a notable textbook, *Theory of Multivariate Statistics* (Springer, 1999), co-authored with David Brenner, which provides a rigorous treatment of modern multivariate statistical theory. His work emphasizes foundational topics such as multivariate regression, principal components analysis, and robust statistical methods. Bilodeau has also contributed to computational statistics through R packages like *groc* and *IndependenceTests*, which implement advanced statistical techniques for regression analysis and independence testing. Recent publications include methodological advancements in variance component models (2021), independence testing across scales (2017), and applications of meta-elliptical distributions (2014). Bilodeau's research integrates theoretical developments with practical applications, spanning fields from ecology to actuarial science. His work on nonparametric independence tests (2007) and robust SUR models (2000) demonstrates his commitment to both statistical methodology and real-world problem-solving. He maintains an active academic profile with contributions to statistical education and ongoing collaborations in multivariate analysis.

James G. MacKinnonمشاهده پروفایل

استاد

• Bootstrap Methods
• Cluster-Robust Inference
• Econometric Theory
• +۳ مورد دیگر

James G. MacKinnon is the Sir Edward Peacock Professor of Econometrics at Queen’s University, Department of Economics. He holds a B.A. (York University), M.A., and Ph.D. (Princeton University). His research focuses on bootstrap methods, cluster-robust inference, and econometric theory. He has authored influential textbooks like *Estimation and Inference in Econometrics* and *Econometric Theory and Methods*. MacKinnon has served as Head of the Department of Economics (2003–2013) and President of the Canadian Economics Association (2001–2002). His honors include Fellowships from the Econometric Society, Royal Society of Canada, and International Association for Applied Econometrics. His work spans over 150 publications, emphasizing robust statistical methods and empirical practice. Notable contributions include numerical distribution functions for cointegration tests and cluster-robust inference guidelines. He has advised numerous graduate students and collaborates on software tools for econometric analysis, such as Stata modules for bootstrap inference.

Yining Chenمشاهده پروفایل

دانشیار

• Statistical Methodology
• Change-Point Detection
• Nonparametric Estimation
• +۴ مورد دیگر

Yining Chen is an Associate Professor in the Department of Statistics at the London School of Economics and Political Science (LSE). He holds a PhD in Statistics from the University of Cambridge (2014). His research focuses on statistical methodology, particularly in change-point detection, nonparametric estimation, and computational aspects of statistical methods. He also explores shape-constrained estimation and time series analysis. Dr. Chen has taught courses such as ST444 Computational Data Science and ST304 Time Series and Forecasting at LSE. He has contributed to interdisciplinary research in medical statistics, including work on kidney and liver transplantation outcomes. His software contributions include R packages like 'not', 'scar', and 'Sshaped', which implement his methodological advancements in statistical computing. His research has been published in top-tier journals such as the Journal of the Royal Statistical Society and Biometrika. Key areas of application span econometrics, actuarial science, and biomedical research. He actively engages in collaborative projects addressing practical data challenges across disciplines.

Kenichi Nagasawaمشاهده پروفایل

استادیار

• Econometrics
• Bootstrap Methods
• Statistical Inference
• +۱ مورد دیگر

Kenichi Nagasawa is an Assistant Professor in the Department of Economics at the University of Warwick. He specializes in econometrics with a focus on bootstrap-assisted inference, treatment effect estimation, and asymptotic theory. His research develops methodologies for statistical inference in complex econometric models. He teaches EC226: Econometrics 1 and has secured funding through the BA/Leverhulme Small Research Grants (2024-2026). His work frequently involves collaborative research with institutions globally. Research Focus: Development of robust inference techniques for econometric models, particularly using bootstrap methods for nonstandard distributions and treatment effect estimation with imperfect data.

Jeremy Smithمشاهده پروفایل

استاد

• Time Series Econometrics
• Forecasting Theory
• Forecast Evaluation Criteria
• +۳ مورد دیگر

Jeremy Smith is a Professor of Economics at the University of Warwick. He holds a formal academic position within the Department of Economics. His research focuses on time series econometrics, forecasting theory, non-linear models, and higher education outcomes. He has published extensively in top journals such as Journal of Econometrics , Economic Journal , and Journal of Applied Econometrics . His work spans topics like wage premium analysis, educational returns, and policy evaluation. Teaching responsibilities include courses such as EC124 Statistical Techniques B and EC226 Econometrics 1. No awards are explicitly mentioned, but his contributions to econometric methodologies and education policy analysis are notable. He advises students through scheduled meetings.

Orimar Sauri Arreguiمشاهده پروفایل

دانشیار

• Mathematical Statistics
• Stochastic Processes
• Nonparametric Estimation
• +۷ مورد دیگر

Orimar Sauri Arregui is an Associate Professor in the Department of Mathematical Sciences at Aalborg University's Faculty of Engineering and Science, Denmark. His research lies at the intersection of mathematical statistics, stochastic processes, and financial modeling. Research Interests: His work focuses on ambit fields , trawl processes , Lévy and infinite divisible random fields , and nonparametric estimation in continuous time. He investigates asymptotic behavior, limit theorems, and statistical inference for complex stochastic models, with applications in financial market microstructure and energy flux modeling. The analysis of his recent publications reveals a strong trend in theoretical statistics and probability, particularly in developing and analyzing models driven by non-Gaussian noise and long-range dependence. His work often involves high-frequency data and contributes to the foundations of spatiotemporal modeling. Scientific Contributions: Developed mathematical frameworks for financial market microstructure. Advanced theory for nonparametric estimation of trawl processes. Derived asymptotic error distributions for numerical schemes in stochastic delay equations. Proved local limit theorems for energy fluxes in random fields. Advising and Research Activity: He has been involved in PhD supervision and maintains an active research output, primarily through preprints on arXiv and SSRN. His collaborations span topics in financial econometrics and statistical physics. Though specific grants are not listed, his consistent publication record suggests ongoing research funding. Laboratory and Teams: While no formal lab is mentioned, his work is part of the broader research network in mathematical statistics and financial mathematics at Aalborg University, with notable collaborations in stochastic modeling and econometrics.

Charles S. Peskinمشاهده پروفایل

استاد

• Immersed Boundary Method
• Mathematical Physiology (Heart, Neuro)
• Partial Differential Equations in Biology
• +۷ مورد دیگر

Charles S. Peskin is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He specializes in mathematical modeling and simulation of biological systems, particularly cardiovascular physiology and neurophysiology. His work focuses on the Immersed Boundary Method, a computational framework for fluid-structure interaction problems. Peskin has authored influential textbooks such as Modeling and Simulation in Medicine and the Life Sciences (2nd ed., 2002) and developed simulation tools used in biomechanics research. His research spans mathematical biology, computational fluid dynamics, and stochastic processes in biological systems. He advises PhD students on interdisciplinary projects at the interface of mathematics and life sciences. Key contributions include modeling heart valve dynamics, neural signaling mechanisms, and biomolecular motor systems. Affiliations: Courant Institute, NYU Research: Immersed Boundary Method, Cardiac Mechanics, Neurophysiology Modeling Publications: 100+ articles, 2 books Teaching: Courses on PDEs in Biology, Biomolecular Motors, and Simulation Techniques Software: MATLAB programs for cardiovascular system simulations His work bridges applied mathematics with biomedical engineering, emphasizing computational methods for complex biological systems. Recent work includes studies on entropy principles in biology and rotary molecular motor mechanisms.

Johan Pensarمشاهده پروفایل

دانشیار

• Statistical Machine Learning
• Probabilistic Graphical Models
• Causal Learning
• +۳ مورد دیگر

Johan Pensar is an Associate Professor of Statistics and Data Science at the University of Oslo's Department of Mathematics. He holds a PhD from Åbo Akademi University (2016) and was a postdoc at the University of Helsinki (2016–2020). His research focuses on statistical machine learning, probabilistic graphical models, causal inference, and applications in genomics. He has supervised multiple PhD students and co-supervised others in interdisciplinary projects, including causal modeling in healthcare and machine learning for microbiology. Education: PhD in Statistics, Åbo Akademi University, 2016 Postdoctoral Researcher, University of Helsinki, 2016–2020 Research Interests: Pensar's work integrates statistical theory with practical applications. Key areas include developing methods for causal discovery, probabilistic graphical models (e.g., Bayesian networks), and their use in genomics and healthcare. He emphasizes interpretable machine learning and robust statistical frameworks for complex data. Publications: Recent work spans causal inference, microbial genome analysis, and housing market prediction. His methods address challenges like confounding bias, generalization in ML, and uncertainty quantification in valuation models. Awards: Finnish Statistical Society Doctoral Thesis Award (2013–2016) Teaching & Advising: Pensar teaches advanced courses in statistical learning and probabilistic graphical models. He advises PhD students on causal modeling, ML in healthcare, and data science applications. He collaborates with industry partners like Integreat and Eiendomsverdi AS. Lab/Teams: He is affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) and leads research on Bayesian methods in ML.

Marco Ercolaniمشاهده پروفایل

دانشیار

• Applied Econometrics
• Labour Economics
• Health Economics
• +۱۲ مورد دیگر

Marco Ercolani is an Associate Professor in Econometrics at the Department of Economics , Birmingham Business School , University of Birmingham . His research applies econometric methods to socio-economic issues in health, ageing, education, and labour markets. He teaches courses in quantitative methods, labour economics, and time series regression. Education: B.A. in Economics, University of Sussex M.A. in Econometrics, University of Essex Ph.D. in Economics, University of Essex His research interests focus on applied econometrics , particularly using cross-sectional, panel, and time-series data to test theories against real-world data. Key areas include sickness absence behaviour, seasonal economic cycles, Euro adoption effects on prices, and labour market outcomes across age groups. He emphasizes 'bringing data to theories' and develops custom statistical programming for non-standard analyses. The recent publications reflect a strong trend in interdisciplinary applied research, combining econometrics with public health (antibiotic disposal, antimicrobial resistance), environmental economics (climate change and migration), education policy (subject choice, student performance), and development economics (time poverty in Ghana, intergenerational mobility). His work increasingly involves policy-relevant analysis, including commissioned reports for the UK Department for Transport. Scientific Contributions: Developed statistical software (SAVE9) for Stata. Authored book chapters on China's economic dualism and Euro inflation effects. Published book reviews in The Economic Journal . He supervises PhD students in labour econometrics and collaborates widely across disciplines. His work appears in journals such as Economics of Education Review , Feminist Economics , The Energy Journal , and Higher Education . He is actively engaged in current research and policy analysis, contributing to both academic discourse and practical policy solutions. Laboratory/Research Group: Member of the Econometrics Research Group within the Department of Economics at the University of Birmingham.

Pieter Serneelsمشاهده پروفایل

استاد

• Applied Microeconomics
• Behavioural Economics
• Labour Economics
• +۱۰ مورد دیگر

Pieter Serneels is Professor of Economics at the University of East Anglia, School of Global Development, and holds a PhD from the University of Oxford. He is also a Visiting Professor at the University of Oxford, and affiliated with multiple research networks including IZA, CSAE, J-PAL, EGAP, and CBESS. His research focuses on development economics using behavioural and experimental methods in low-income countries. Education: PhD, University of Oxford His research interests span applied microeconomics, behavioural and labour economics, and political economy, with applications in education, health, service delivery, and climate change. He leads the Behavioural and Experimental Development Economics Research Group (BEDERG) and is an executive member of the Centre for Behavioural and Experimental Social Sciences (CBESS) at UEA. His recent work explores climate change impacts on labour, mental health in conflict zones, teacher incentives, and health interventions in developing contexts. His publications appear in leading journals such as American Economic Review , Journal of the European Economic Association , World Bank Economic Review , and The Lancet Global Health . Key themes across his recent articles include the role of health in productivity, educational reforms, psychological aspects of poverty, and experimental policy evaluation. He has led major research projects funded by US AID, British Academy, FCDO, and Innovations for Poverty Action. Scientific Awards: Mid-Career Fellowship, British Academy Pieter Serneels advises on policy through affiliations with RISE and FCDO, where he served as Economics Senior Research Fellow. He teaches development economics, microeconomics, and econometrics at undergraduate and postgraduate levels, and co-directs the MSc in Development Economics. He has also contributed to policy blogs including Development Impact and VoxDev, emphasizing evidence-based decision-making. Research Groups and Labs: Behavioural and Experimental Development Economics Research Group (BEDERG), UEA – Team Leader Centre for Behavioural and Experimental Social Sciences (CBESS), UEA – Executive Member Tyndall Centre for Climate Change Research – Member Impact Evaluation – Member

Ho Kimمشاهده پروفایل

دانشیار

• Digital Marketing
• Social Media Marketing
• Consumer Behavior
• +۹ مورد دیگر

Ho Kim is an Associate Professor of Digital and Social Media Marketing at the Ed G. Smith College of Business, University of Missouri-St. Louis , where he has taught courses like Digital Marketing Strategies, Marketing Analytics, and Statistical Modeling since 2015. His research focuses on online consumer behavior, econometric modeling, and digital marketing strategies. Education Ph.D. in Marketing, UCLA Anderson School of Management (2013) M.E. in Management Engineering, KAIST (1999) B.B.A. in Business Administration, Yonsei University (1997) Kim's research spans online word-of-mouth, search behavior, paywall economics, and causal inference , with methodological expertise in econometric/statistical models and text mining. His work analyzes how marketing activities influence consumer decisions in digital environments. His publications appear in top journals like Journal of the Academy of Marketing Science and Journal of Business Ethics , with media coverage in Forbes , Huffington Post , and Harvard Business School Working Knowledge . He was invited by South Korea's Maeil Business Newspaper to present his 2017 research to practitioners. Scientific Awards 2019 Emerald Literati Award 2019 Durand Award for Research Excellence 2023 UMSL CoBA Research Excellence Award for Marketing & Entrepreneurship

Antje Jantschمشاهده پروفایل

پژوهشگر

• Empirical Microeconomics
• Agricultural Economics
• Rural Development
• +۴ مورد دیگر

Antje Jantsch is a researcher at the Institute of Agricultural Development in the Global South (IAMO), affiliated with Martin Luther University Halle-Wittenberg, and an associate researcher at the World Database of Happiness (Erasmus Happiness Economics Research Organization EHERO) at Erasmus University Rotterdam. She leads the Leibniz Junior Research Group RuWell , focusing on rural well-being. Rural Well-being Empirical Microeconomics Social Comparison Processes Her work connects empirical microeconomics with quality-of-life metrics, emphasizing multidimensional welfare, job satisfaction, and social comparison dynamics. Her studies span Southeast Europe, Eastern Germany, Thailand, and Latin America. Recent publications explore town-size well-being disparities, wealth-happiness links, and pandemic-induced social dynamics. Her research philosophy integrates quantitative analysis with rural policy frameworks. She collaborates with institutions like the International Society for Quality-of-Life Studies (ISQOLS) and the European Association of Agricultural Economists (EAAE).

Nicholas Floresمشاهده پروفایل

استاد

• Environmental Economics
• Resource Economics
• Behavioral Economics
• +۳ مورد دیگر

Nicholas Flores is a Professor of Economics at the University of Colorado Boulder, affiliated with the Department of Economics and the Institute of Behavioral Science. He also serves as a Faculty Research Associate at the Institute of Behavioral Science and as a Principal Investigator at the National Center for Earth-surface Dynamics. PhD in Economics (1995), MA in Economics (University of California, San Diego) MS in Mathematical Statistics (UC San Diego), BA in Economics (University of Texas at Austin) His research focuses on the valuation of environmental and public goods, contingent valuation methodologies, and the economics of natural hazards. He has developed frameworks for understanding wildfire risk mitigation behaviors and the role of social norms in environmental decision-making. Recent work includes empirical studies on wildfire policy and theoretical advancements in benefit-cost analysis. His publications span environmental economics, behavioral economics, and risk mitigation. Trends in his research include the interplay of social interactions in environmental risk perception, refinement of contingent valuation methods, and the economics of natural disasters. Notable collaborations involve urban stream restoration analysis and decision-making under uncertainty. Host of the annual CU Environmental and Resource Economics Workshop since 1999 Principal Investigator at the National Center for Earth-surface Dynamics Faculty Research Associate at the Institute of Behavioral Science since 2004