Department Research
Statistical Methodology
- Statistical Methods for Data Analysis
- meta-analysis (Hedges, Tipton)
- model selection (W. Jiang, H. Jiang, )
- multiple comparisons (H. Jiang)
- robust standard errors and inference (Tipton)
- Bayesian and Likelihood Inference
- Bayesian inference in moment-based models (W. Jiang)
- computational methods for Bayesian inference (Tanner)
- higher-order asymptotic theory (Severini)
- inference based on the Gibbs posterior (W. Jiang, Tanner)
- likelihood inference (Andrews, Severini, Samia)
- Nonparametric and Semiparametric Inference
- nonparametric likelihood inference (Severini, Wang)
- mixture-of-experts models (W. Jiang, Tanner)
- semiparametric regression models (Severini)
- Linear and Nonlinear Time Series Analysis
- GARCH models (Andrews)
- models for data with infinite variance (Andrews)
- models for panels of time series (Samia)
- rank-based estimation (Andrews)
- threshold models (Samia)
- dependent data (Samia)
- spatio-temporal statistical modeling and methodologies (Samia)
Machine learning and AI
- Statistical Machine Learning
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deep learning and reinforcement learning (H. Liu, Stadie)
- deep foundation models with applications in natural language processing, vision and financial time series (H. Liu, Stadie)
- optimization and decision making under uncertainty (H. Liu)
- theoretical foundations of machine learning (H. Liu)
- large language models and foundation models (Ding)
- training and deploying large language models (Stadie)
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- Graph learning and graph neural networks (Ding)
- Robotic control (Stadie)
- AI
- reliable and efficient AI (Ding)
- AI for science (Ding)
Interdisciplinary Research
- Computational Biology
- CRISPR-cas9 cleavage efficiency prediction (Wang)
- DNA bendability prediction (Wang)
- RNA-seq data analysis (Wang)
- metagenomics (H. Jiang)
- multi-omics data analysis (H. Jiang)
- nucleosome mapping and positioning prediction (Wang)
- Education, Policy, and Social Science
- statistics and the law (Zabell)
- design and analysis of cluster-randomized experiments (Hedges, Tipton)
- education statistics and program evaluation (Hedges, Tipton)
- human rights statistics (Spencer)
- generalizability of causal findings to policy relevant populations (Tipton)
- psychology, social psychology, and methods for heterogeneity and replication (Hedges, Tipton)
- Epidemiology, Biology and Biostatistics
- statistical ecology (Samia)
- estimation of species richness and population size (Wang)
- forensic DNA identification (Zabell)
- models for infectious diseases (Samia)
- dynamics of biological systems (Samia)
- Evidence Based Social and Health Policy (Hedges, Tipton)
- Financial Data Analysis
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graphical statistical arbitrage (H. Liu)
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scientific technical analysis (H. Liu)
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financial time series forecasting (H. Liu)
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- History and Philosophical Foundations
- history and philosophical foundations of probability and statistics (Zabell)
- Statistical applications to biomedical research (Samia)