Assistant Staff, Lead Data Scientist · Cardiovascular Outcomes, Registries and Research (CORR) Heart, Vascular & Thoracic Institute · Cleveland Clinic Clinical Assistant Professor (Joint Appointment) · Cleveland Clinic Lerner College of Medicine
I develop statistical methods and machine learning tools for cardiovascular outcomes research — with a focus on survival analysis, longitudinal data, and reproducible clinical workflows.
📄 CV (PDF) | 📝 CV (Web) | 🔗 LinkedIn | 📘 ORCID
| Package | Description |
|---|---|
| ggRandomForests | Visual exploration of random forest models (survival, regression, classification) via randomForestSRC and ggplot2 |
| boostmtree | Boosted multivariate trees for flexible modeling of multivariate continuous longitudinal outcomes |
| hazard | SAS and C implementation of multi-phase hazard analysis for time-to-event decomposition. (Maintainer) |
| mixhazard | R port of the C computational core underlying the Cleveland Clinic Hazard SAS module |
| hvtiPlotR | Publication-quality graphics conforming to HVTI statistical reporting standards |
| hvtiRutilities | Utility functions for reproducible research workflows within the Heart, Vascular & Thoracic Institute |
Applied statistical machine learning research conducted in close collaboration with cardiovascular surgeons and clinicians. Methodological focus spans random forest and ensemble methods, clustering, deep learning, and time series analysis, with emphasis on time-to-event and longitudinal data in cardiovascular outcomes. A sustained focus is the translation of methodological advances into clinical practice through open-source software development and reproducible analytical workflows, with current work centered on open-source implementations of multi-phase hazard analysis methods.
PhD Statistics, Case Western Reserve University (2011) Dissertation: Regularization: Stagewise Regression and Bagging · Advisor: Hemant Ishwaran