Order-restricted Inference Professors and Supervisors

Pagin Peterمشاهده پروفایل

استاد

Graz University of TechnologyAustria

Peter Pagin is a Professor of Theoretical Philosophy at Stockholm University's Department of Philosophy. He holds a PhD from Stockholm University (1987) under the supervision of Dag Prawitz. His academic career includes roles such as Lecturer (1994–2001), Researcher (1991–1993), and Post-doctoral Fellow (1987–1991) at Stockholm University. He has been a Visiting Professor at the University of Barcelona (2008) and EHESS/IEA-Paris (2010). Research Focus: Philosophy of Language, Formal Semantics, Vagueness, Pragmatics, and Epistemology. Key Projects: Led or participated in over a dozen research initiatives, including those funded by The Swedish Research Council and The Bank of Sweden Tercentenary Foundation. Research Interests: Pagin’s work centers on compositionality, pragmatic enrichment, the semantics of vague predicates, and the philosophy of assertion. Notable contributions include theories on coherence-driven enrichment and critiques of structured propositions. Awards & Honors: Member of the Rolf Schock Prize Committee for Logic and Philosophy (2009). Associate member of LOGOS (Barcelona) and CeLL (University of London). Advising: Supervised five PhD students, including Mikael Janvid and Arvid Båve, focusing on epistemology, truth predicates, and vagueness. Labs/Teams: Collaborated with international networks like EURO-XPRAG and PETAF, exploring experimental pragmatics and language training.

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Chuan-Fa Tangمشاهده پروفایل

استادیار

University of Texas at DallasUnited States

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.

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Guihua Wangمشاهده پروفایل

استادیار

University of Texas at DallasUnited States

Guihua Wang is an Assistant Professor of Management at the Naveen Jindal School of Management, University of Texas at Dallas. His research focuses on healthcare analytics, operations research, and health policy, with particular emphasis on improving healthcare system efficiency and patient outcomes through data-driven approaches. Key research themes include analyzing the impact of telemedicine on clinical decisions, evaluating policy measures like stay-at-home orders during pandemics, and optimizing organ transplantation logistics. He has contributed to understanding how public health interventions affect mobility patterns and healthcare access disparities between rural and urban areas. His work frequently employs advanced analytical methods such as instrumental variable forests and causal inference techniques to study heterogeneous treatment effects. Notable studies include examining Medicaid expansion effects on emergency department wait times and analyzing the economic implications of distant referrals for cardiac surgeries. While no formal awards are listed, his active research portfolio demonstrates engagement with critical issues in healthcare operations and policy. Advising and grant details are not specified in available materials. He is affiliated with the Jindal School's Management department and contributes to interdisciplinary projects at the university.

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Charles J Geyerمشاهده پروفایل

استاد

University of Minnesota Twin CitiesUnited States

Charles J Geyer is a Professor in the Department of Statistics at the University of Minnesota, Twin Cities, within the College of Science and Engineering. He has been an active researcher since at least 1988, with a sustained record of scholarly output in statistical theory and methodology. His research focuses on advanced statistical methods including maximum likelihood estimation, exponential families, Markov Chain Monte Carlo (MCMC), likelihood-free inference, and aster models. These methods are applied in interdisciplinary contexts such as evolutionary biology, genetics, and ecological modeling, particularly in life history analysis and phenotypic selection. His work bridges theoretical statistics with practical computational tools for complex data. The recent publications highlight a strong trend toward computationally efficient inference, especially in models where traditional maximum likelihood fails. He has contributed to the development of the R package glmm for generalized linear mixed models and has worked extensively on envelope methods and variance reduction techniques. His research outputs include numerous peer-reviewed articles, book chapters, and publicly shared datasets, reflecting a commitment to open science. Scientific contributions include: Development of MCMC methods for dependent data Foundational work on likelihood inference when MLE does not exist Integration of aster models with envelope methodology Applications in evolutionary and ecological statistics He has collaborated with researchers such as D. J. Eck, R. G. Shaw, and R. D. Cook. While formal advisee relationships are not listed, his collaborative work suggests mentorship and academic leadership. He has not received any explicitly mentioned awards in the provided text, but his sustained impact is evident through citations and methodological influence. His datasets are archived in the University of Minnesota Data Repository, supporting reproducible research.

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Denis Chetverikovمشاهده پروفایل

استاد

University of California, Los AngelesUnited States

Denis Chetverikov is a Professor of Economics at the University of California, Los Angeles (UCLA). His research focuses on econometric theory, with emphasis on high-dimensional models, empirical process theory, bootstrap methods, and applications to asset pricing and policy analysis. He has published in top journals such as Econometrica , Review of Economic Studies , and Annals of Statistics . Education: PhD from the Massachusetts Institute of Technology (MIT). His work bridges theoretical econometrics and computational methods, addressing challenges in modern data analysis. Key contributions include advancements in nonparametric estimation, rank-based inference, and regularization techniques for high-dimensional datasets. Research trends in his articles emphasize methodological innovations for handling complex economic data structures, including factor models, quantile regression, and robust inference frameworks. He has developed statistical software tools like the csranks R package for rank-based analysis. His grants and lab affiliations (if any) are not explicitly detailed in the provided text.

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Harold B. Sackrowitzمشاهده پروفایل

استاد

Rutgers, The State University of New JerseyUnited States

Harold B. Sackrowitz is a Distinguished Professor and Undergraduate Director in the Department of Statistics at Rutgers University, within the School of Arts and Sciences. He is actively involved in both teaching and research, with a strong emphasis on theoretical statistical methodologies. His primary research interests include statistical inference , decision theory , multiple endpoint procedures , and order restricted inference . These areas focus on improving the validity and efficiency of statistical decisions under complex constraints and multiple testing scenarios. Dr. Sackrowitz is recognized as a Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics (IMS) , two of the most prestigious honors in the field of statistics, reflecting his substantial contributions to statistical theory. Fellow of the American Statistical Association (ASA) Fellow of the Institute of Mathematical Statistics (IMS) He advises undergraduate programs and contributes to academic leadership as Undergraduate Director. While no specific graduate students or research grants are listed in the available text, his long-standing position and fellowships suggest an extensive history of mentorship and scholarly impact. Dr. Sackrowitz is based at Hill Center 563, 110 Frelinghuysen Road, Piscataway, NJ 08854, and can be reached via email at sackrowi@stat.rutgers.edu .

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Iliopoulos Georgiosمشاهده پروفایل

استاد

University of PiraeusGreece

Iliopoulos Georgios is a Professor and Department Chair at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus. He has held this position since 2015, following his progression from Assistant Professor (2003-2010) to Associate Professor (2010-2015) at the same institution. Education: 1993: B.A. in Mathematics, Department of Mathematics, University of Patras 1999: PhD in Statistics, Department of Mathematics, University of Patras Iliopoulos specializes in statistical theory and methodology, with particular expertise in Markov chain Monte Carlo methods, Statistical Decision Theory, and Scale parameter estimation. His research focuses on accurate inference under censorship and constrained inference arrangement, addressing fundamental challenges in statistical analysis of complex data structures. His work bridges theoretical statistics with practical applications in reliability analysis and survival analysis. His publication record shows consistent contributions to exact statistical inference methods, particularly for censored data and complex distributions like Laplace and Gamma. His research demonstrates expertise in both parametric and semiparametric approaches, with significant work on variance reduction techniques in computational statistics and solutions to the label switching problem in Bayesian mixture models. Iliopoulos teaches undergraduate courses including Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics), as well as the postgraduate course Computational Statistical Techniques for the Master of Science in Applied Statistics.

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Andreas Beerliمشاهده پروفایل

مدرس

ETH ZurichSwitzerland

Labor Economics
Immigration
Public Policy
+۱۲ مورد دیگر

Andreas Beerli is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich. He works as a postdoctoral researcher at the KOF Economic Institute and the Immigration Policy Lab, focusing on labor markets, immigration, and public policy. He co-founded Policy Analytics , a platform supporting evidence-based social programs. His research employs causal methods like field experiments and administrative data analysis. PhD in Economics from the University of Zurich Beerli's work bridges health economics , social policy design , and economic integration . He investigates how immigration affects labor markets and political attitudes, how technology shapes migration patterns, and how public policies can be rigorously evaluated for impact. His recent projects explore cannabis regulation , mental health interventions for refugees, and criminal justice reforms . His peer-reviewed articles analyze immigration's effects on Swiss firms and workers, skill-biased technology's role in migration, and technical change in Chinese manufacturing. Current working papers examine refugee employment restrictions, procedural justice in criminal trials, and cannabis policy. Media outlets like Foreign Policy , VoxEU , and Tagesanzeiger have featured his work. Beerli collaborates with institutions such as the Swiss Federal Office of Public Health (FOPH) , Kununu , Harvard's Access to Justice Lab , and the Swiss National Science Foundation . His methodological focus includes randomized evaluations , linked administrative datasets , and psychological mechanisms in policy design.

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Georgios Iliopoulosمشاهده پروفایل

استاد

University of PiraeusGreece

Professor Georgios Iliopoulos is a distinguished academic serving as Professor and Department Chair of the Department of Statistics and Actuarial Science at the University of Piraeus. With an extensive academic career spanning over two decades, Professor Iliopoulos has established himself as a leading expert in statistical theory and methodology. His leadership as Department Chair demonstrates his significant contribution to the academic community and his commitment to advancing statistical education and research. Professor Iliopoulos completed his educational journey at the University of Patras, earning his B.A. in Mathematics in 1993 followed by a PhD in Statistics in 1999. His academic career progressed through various institutions before he settled at the University of Piraeus, where he has held positions from Assistant Professor (2003-2010) to Associate Professor (2010-2015) and ultimately to Professor (2015-present). Professor Iliopoulos's research focuses on several key areas of statistical theory, with particular emphasis on Markov chain Monte Carlo methods, Statistical Decision Theory, Scale parameter estimation, Accurate inference under censorship, and Constrained inference arrangement. His work bridges theoretical statistics with practical applications, demonstrating how sophisticated statistical methods can solve real-world problems across various domains. His research has consistently addressed challenging theoretical questions while maintaining relevance to practical statistical challenges faced by researchers and practitioners. Analysis of Professor Iliopoulos's publication record reveals a strong focus on theoretical statistics with applications in reliability analysis, Bayesian inference, and censoring methodologies. His work demonstrates a consistent pattern of advancing statistical theory while maintaining practical relevance, particularly in the areas of parameter estimation, confidence interval construction, and inference with censored data. The interdisciplinary nature of his research is evident in publications spanning journals in statistics, biostatistics, and computational statistics. Professor Iliopoulos is actively involved in teaching both undergraduate and postgraduate courses. At the undergraduate level, he teaches Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics). For postgraduate students, he offers Computational Statistical Techniques as part of the Master of Science in Applied Statistics program. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of advanced statistical methods.

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Benjamin Spectorمشاهده پروفایل

دانشیار

École Normale SupérieureFrance

Benjamin Spector is a Research Director at the CNRS and an Associate Professor at École Normale Supérieure (ENS-PSL) , affiliated with the Institut Jean-Nicod (CNRS/ENS/EHESS). His work bridges natural language interpretation , formal logic , and experimental psychology , focusing on the interplay between compositional semantics and pragmatic reasoning . Research Interests: Syntax-semantics interface, scalar implicatures, presuppositions, plural predication, quantification, vagueness, and polarity sensitivity. Teaching: Courses on logic, semantics, and the Rational Speech Act (RSA) framework, including at ENS and ESSLLI. Collaborations: Extensive co-authorship with scholars like Paul Egré, Danny Fox, and Emmanuel Chemla, exploring topics from exhaustivity in RSA to trivalent logic for presuppositions . Labs: Associate Director of the CONCEPTS, LOGIC, REASONING research network at Institut Jean-Nicod.

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