(Topics include but are not limited to)
Bayesian statistical modeling and inference
High dimensional data statistical analysis and dimensionality reduction methods
Causal inference and structural equation modeling
Statistical Learning Theory and Generalization Analysis
Regression modeling and variable selection
Time series statistical modeling and prediction
Spatial Statistics and Geographically Weighted Models
Survival analysis and reliability statistics
Mixed effects model and longitudinal data analysis
Non parametric and semi parametric statistical methods
Statistical Fundamentals in Machine Learning
Statistical interpretation of deep learning models
Ensemble learning and model averaging methods
Anomaly detection and robust statistics
Analysis of missing and incomplete data
Data Mining and Feature Selection
Large scale data computing and distributed statistics
Uncertainty quantification and interval prediction
Model selection and cross validation methods
Statistical Simulation and Monte Carlo Method
Experimental Design and Causal Effect Estimation
Network Data Analysis and Graph Modeling
Statistical modeling of text and image data
The application of statistical methods in finance and healthcare
Explainable machine learning and statistical visualization