Research Lab
Applied research at the intersection of statistical methodology, software engineering, and clinical data science. We build tools and methods that survive contact with real-world data.
Focus areas
Clinical Biostatistics
Adaptive trial design, survival analysis, and longitudinal modeling for medical studies.
Reproducible Pipelines
End-to-end workflows that go from raw data to publication-ready results without manual steps.
Statistical Machine Learning
Predictive modeling with rigorous uncertainty quantification for healthcare applications.
Bayesian Methods
Prior elicitation, MCMC sampling, and hierarchical modeling for complex research designs.
Current collaborations
In progress
Immunotherapy trial
Adaptive Bayesian monitoring + realtime dashboards for a phase II oncology sponsor.
Live
Population health pipeline
Automated ingestion + reproducible transforms for a public health surveillance program.
Drafting
Methodology preprint
MGF-based variance estimators for small-sample experiments.
Interested in collaborating?
We welcome partnerships with research groups, clinical teams, and graduate students. Reach out with a brief description of your project.
Contact the lab →Selected publications
- Thornton, M. (2025). Reproducible Bayesian Monitoring for Clinical Trials.
- Thornton, M. & Team (2024). Automating Population Surveillance Workflows.
- Thornton, M. (2023). MGFs in Modern Inference.