I’m a multidisciplinary computational scientist based in Portland, Oregon, working where climate physics, energy systems, and software engineering meet. I came to this work as an environmentalist first, convinced that we have a real responsibility to be the best stewards of this planet we can be, and I’ve spent my career making sure that conviction is backed by rigorous data rather than good intentions alone. I specialize in large-scale environmental and energy data: the kind that’s too big for memory, too messy for spreadsheets, and far too consequential to get wrong.

Most recently, as a Senior Python Developer in parallel computing at ICF, I refactored experimental climate workflows into production-grade, Dask-optimized packages running across HPC and cloud clusters, and standardized analysis-ready geospatial data (Zarr/NetCDF on AWS S3). That work underpinned climate-risk tooling for the physical energy infrastructure our communities depend on, from transformers to coastal substations.

Earlier, at the Electric Power Research Institute, I designed the statistical methodology and backend behind EPRI’s Technology Radar, a confidence-weighted foresight platform spanning roughly 69 energy technologies, and authored widely-referenced analyses of AI and data-center energy demand. My scientific foundation comes from Portland State’s Center for Climate and Aerosol Research, where I ran global atmospheric-chemistry simulations (GEOS-Chem) and analytical Bayesian emission inversions to investigate the methane and ethane trends driving a changing atmosphere.

My approach blends technical rigor with clear communication, and it’s rooted in a simple belief: the better we understand our impact on the planet, the better we can choose to protect it. I care as much about reproducibility, documentation, and helping teams move together as I do about the models themselves, because work this important shouldn’t live or die with one person.

Education

B.S., Applied Environmental Physics (Honors) — Portland State University Dual minors in Geographic Information Systems & Mathematics

Certifications

  • Certified Energy Manager (CEM) — Association of Energy Engineers (in progress, 2026)
  • Certified Sustainable Development Professional (CSDP) — Association of Energy Engineers (in progress, 2026)
  • IBM Data Science Professional Certificate — IBM (2025)
  • Google Advanced Data Analytics Professional Certificate — Google (2024)
  • GHG Protocol Scope 2 & 3 Certificates — World Resources Institute (2023)
  • GHG Accounting Certificate — Corporate Finance Institute (2023)

Technical Skills

Languages & Core Tools

Python SQL R MATLAB C/C++ FORTRAN Scala JavaScript VBA Bash

High-Performance & Cloud

Dask AWS / S3 Coiled Azure Snowflake Docker SSH / Unix Distributed Computing

Geospatial & Climate

ArcGIS Pro QGIS xESMF Regridding Zarr / NetCDF ARCO Standards GEOS-Chem GCHP HEMCO WRF AERMOD ENVI

Statistical & Scientific Modeling

Monte Carlo Bayesian Inference Uncertainty Quantification Time-Series Forecasting Extreme-Value Statistics

Instrumentation & Hardware

System Design & Fabrication Experimental Instrumentation Optical Measurement LTspice Simulation Precision Calibration System Diagnostics AutoCAD

Data Engineering & Visualization

Pipeline Design Ingestion & Cleaning Tableau Power BI matplotlib seaborn hvplot Quarto

Practices

Git / Jira CI/CD Unit Testing Containerization API Design QA/QC Reproducible Research

Selected Recognition

  • NASA Pathways Intern (2021–2024)
  • NSF Division of Atmospheric & Geospace Sciences, Grant 1950702 (2021–2023)
  • PSU Honors College Thesis & Academic Achievement Awards
  • President’s Equal Access Scholarship · Vernier STEM Scholarship