Organized around questions that matter for water systems

Streamflow and baseflow generation

Understanding how recharge, infiltration, and runoff pathways shape low-flow realism in dry regions.

Soil moisture persistence

Studying how land models represent memory, retention, and land-atmosphere interactions over time.

Hydrologic tools and reproducibility

Packaging methods into software that supports repeatable analysis and broader research reuse.

Climate impacts on water resources

Examining drought, precipitation intensity, and resilience across hydrologic systems.

Scientific machine learning

Designing interpretable ML architectures for routing, rainfall-runoff prediction, and hybrid physical plus data-driven modeling.

Data products and analytical systems

Building dashboards, statistical analyses, and data-management tools that turn environmental data into decisions.

Soil Moisture Memory

A deeper look at how soil hydraulic representation affects persistence, climate feedbacks, and model performance.

Baseflow Index

An investigation of baseflow generation mechanisms and their consequences for streamflow prediction in the arid Southwest.

RiverGraphNet

A new graph-based routing framework that uses directed river-network topology and Noah-MP runoff to improve streamflow routing skill.

SoilSolver

A process-aware mass-conserving neural framework for rainfall-runoff modeling with interpretable storage-flux dynamics.

Streamflow Prediction

A sequence-modeling project comparing LSTM and Transformer approaches for streamflow prediction, with a live dashboard for result exploration.

Coffee suitability & forest-loss analysis

YAML-driven geospatial workflow combining NDVI, rainfall, soil moisture, and forest-loss layers. Harmonizes inputs to a common monthly grid and applies configurable suitability thresholds. Includes a clearly labeled synthetic demo.

Python · Remote sensing · Raster processing

Remote data jobs: SQL analysis

PostgreSQL analysis of job-posting data to compare skill demand and reported salaries, with reproducible Python visualizations. Results describe the source dataset rather than the current job market.

SQL · PostgreSQL · Data visualization

Bayesian inference and uncertainty

Probabilistic estimation projects using MCMC and multi-view geometry show my comfort with inference, uncertainty, and model structure.

Applied machine learning

Prediction and classification work on crash severity, climate trends, and neural-network benchmarks show a broader ML toolkit beyond hydrology.

Visualization and decision support

Interactive dashboards and analytical summaries translate raw data into interpretable patterns for public safety and planning contexts.

Data infrastructure

SQL and smart water distribution work demonstrate database design, query logic, and system thinking for operational water problems.