|
|
|
|
Zero-inflated GLMM with hierarchical random effects
Zero-Inflated Gamma GLMM across 142k+ daily observations from 49 Australian locations. Covers model selection (M0–M6), DHARMa residual diagnostics, spatial heterogeneity estimation, and Markov chain temporal dependence analysis. 
|
Scalable Bayesian inference for policy evaluation via INLA
Bayesian Structural Time Series for policy evaluation via INLA. Laplace approximation, causal identification assumptions, and interrupted time series design with a focus on efficient posterior computation and uncertainty quantification. 
|
SPDE approximations for efficient spatial inference
SPDE approximations for spatial GLMMs. CAR models, spatial random effects, and Bayesian hierarchical inference with geographic autocorrelation modelling and posterior spatial field estimation.
|
|
Multi-agent patient-to-trial matching pipeline
|
Graph-based RAG pipeline for medical literature
|
Agentic RAG pipeline for biomedical report synthesis
|
|
R Statistical Analysis |
 Tidyverse Data Wrangling |
 ggplot2 Data Visualization |
 tidymodels ML Framework |
glmmTMB Generalized Linear Mixed Models |
|
INLA Bayesian Inference |
DHARMa Residual Diagnostics |
Git Version Control |
 Quarto Reproducible Docs |
PostgreSQL Database |
|
Python Primary Language |
 NumPy Scientific Computing |
 Pandas Data Manipulation |
PyTorch Deep Learning |
TensorFlow Neural Networks |
 Scikit-learn Machine Learning |
Docker MLOps |
Git Version Control |
Jupyter Notebooks |
MongoDB NoSQL |
No activity tracked
|
|
|
|