I build and apply statistical and simulation-based models for studying biological systems under uncertainty by combining Bayesian inference, machine learning, and high-performance computing to investigate ecological processes across scales.
- 🌱 Bayesian hierarchical modeling — phenology, species distributions, generative models fit end-to-end in Stan
- 🔬 Causal inference for ecology — uplift modeling, decision making under uncertainty for conservation / restoration
- ⚙️ HPC & scaling — vectorized/GPU-backed inference, MPI/OpenMP, reproducible Docker environments
| 🌾 New Phytologist, 2025 | Climate drives variation in optimal phenology: 46 years of multi-environment trials in sunflower |
| ⛰️ Environmental Research: Ecology, 2026 | Divergent regional trends in alpine tundra productivity linked to snow-free season length and summer warming |
| 🧊 Scientific Data (Accepted) | Soil moisture and active layer thickness across Alaska & Northwestern Canada |
