Dr.(Prof.) George Karabatsos

Dr. George Karabatsos is a Professor in the Department of Educational Psychology at the University of Illinois-Chicago (UIC), where he is also affiliated with the MESA (Measurement, Evaluation, Statistics, and Assessments) program and serves as an Adjunct Professor in the Department of Mathematics, Statistics, and Computer Science. With a Ph.D. in Measurement, Evaluation, and Statistical Analysis from The University of Chicago, Dr. Karabatsos has established himself as a leading expert in Bayesian statistics, psychometrics, and nonparametric methods. Dr. Karabatsos' research career spans over two decades and reflects a deep commitment to advancing statistical methodology and its practical application across various fields, including education, psychology, biostatistics, and computational science. His work is renowned for its methodological rigor, innovation, and interdisciplinary reach. His published work exceeds 60 peer-reviewed journal articles, covering Bayesian nonparametrics, item response theory, causal inference, density estimation, meta-analysis, and regression modeling. As a recipient of multiple NSF grants, including funding for his work on Bayesian density regression and causal inference, Dr. Karabatsos has demonstrated a strong track record in securing competitive research support. His collaborative research has had measurable impact in areas ranging from mental health to educational testing, highlighting his versatile and applied research orientation. He has developed specialized Bayesian software tools, delivered international workshops, and given over 70 invited talks and presentations at top conferences worldwide. He also contributes significantly to academic publishing, having served as Associate Editor of Psychometrika and on editorial boards of leading journals such as Computational Statistics and Data Analysis, Journal of Applied Measurement, and Journal of Research on Educational Effectiveness. Dr. Karabatsos has mentored numerous students and faculty in advanced quantitative methods and has helped shape the next generation of quantitative researchers. His career is further distinguished by his service as a reviewer for major statistical and psychometric journals and as a grant reviewer for prestigious institutions such as the National Science Foundation and the Institute of Educational Sciences. With a research philosophy rooted in methodological clarity, computational efficiency, and practical application, Dr. Karabatsos' contributions continue to push the boundaries of statistical theory and its real-world utility. His interdisciplinary collaborations and commitment to open-source tools embody a modern scientific ethos aimed at transparency and reproducibility.

• Bayesian Inference
• Nonparametric Statistics
• Item Response Theory
• Hierarchical Modeling
• Regression Analysis
• Meta-Analysis
• Density Estimation
• Model Selection
• Statistical Software Development
• Causal Inference
• MCMC Methods
• EM Algorithms
• Dirichlet Process Modeling
• Teaching and Training
• Scientific Programming
• Measurement Theory
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