| Epidemiologist decoding the chaos of real-world data |
| Real-World Evidence (RWE) and Health Economics & Outcomes Research (HEOR) professional with experience across direct patient care, pharmacovigilance, and real-world data analytics. I design and execute global RWD studies using rigorous epidemiologic and causal inference methods, with a focus on reproducible analysis and clear interpretation for decision-making. |
| Area | Focus |
| Causal inference | Target trial emulation, MSMs, g-formula, IPTW, instrumental variables |
| Bayesian methods | Hierarchical models, Stan, PyMC |
| RWE & comparative effectiveness | RCT duplication, emulation, prediction and risk modeling |
| Data | Claims, EHR, registries (SEER), NHANES, OMOP CDM |
| Implementation | Python, R, SQL, Stata |
| Project | Description |
| Causal Inference Tutorials | Target trial emulation, MSMs, g-formula, SNMs (Python) |
| Pregnancy Cohort Toolkit | R toolkit for pregnancy cohort construction from claims/EHR |
| Clone–censor–weight (CCW) | Immortal time bias: clone–censor–weight with simulated data (Python) |
| GFORMULA-SAS | Parametric g-formula for time-varying treatments and confounders (SAS) |
| Depression and Obesity | Causal analysis of depression and obesity using NHANES |
| The Emperor of All Maladies: A Biography of Cancer — Siddhartha Mukherjee |
| Interested in causal inference, real-world evidence, and oncology applications. |