Miles A. Moore
Computational Ecologist DOE CSGF FellowPhD Student · CU Boulder
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, I investigate ecological processes across scales.
Research
My work sits at the intersection of ecology, statistics, and computation. I am developing methods that handle the complexity and uncertainty inherent in natural systems.
View publications →Bayesian Ecological Modeling
Hierarchical generative models for phenology and species distributions. Stan · NumPyro · JAX
ML for Ecological Inference
Neural networks + kernel methods paired with mechanistic models. Python · PyTorch
High-Performance Simulation
Supercomputing for large-scale biological simulations. Julia · MPI · Fortran
Uncertainty Quantification
Probabilistic solutions for complex systems (ODEs, Transcendentals).
Common Languages
PythonRJuliaStanBash
Recent Methods
Bayesian InferenceGaussian ProcessesNeural NetworksOrdinary Differential EquationsPredictive Machine Learning
Computing Platforms
High-Performance Computing / SLURMOpenMP / MPI (Parallel Computing)DockerGit / GitHubQuarto / R Markdown