Speed & Feedback Study pipeline
Developing a Python pipeline for the City's Speed & Feedback Study, organizing and processing study data for reproducible analysis and reporting.
Experience
Putting models to work.
Where my research meets street-level decisions—currently at the City of Kenmore, following data-science work at the Puget Sound Regional Council.
City of Kenmore
Traffic & Data Engineer Intern · 2026 – Present · Kenmore, WA
Photo-enforcement revenue forecasting
Building revenue forecasts for the City's photo-enforcement program to support budgeting and program planning.
Puget Sound Regional Council
Data Science Intern · 2025 – 2026 · Seattle, WA
Future Land Use · flagship project
An AI pipeline that read the region's zoning codes
For the Future Land Use project, the region needed a consistent, machine-readable picture of zoning across every jurisdiction in central Puget Sound. It is a notoriously messy task, because each city and county writes its zoning code differently, in its own PDFs, tables, and municipal-code formats.
I designed and built an AI-driven pipeline that ingested and parsed those codes and populated a standardized zoning dataset across all 80+ jurisdictions in the region. It turned thousands of pages of inconsistent legal text into structured, comparable zoning attributes, work that would have taken a team months of manual reading. The result gives planners a single regional view of allowed land uses and densities.
80+jurisdictions covered
1standardized regional dataset
AILLM-assisted code parsing
Household Travel Survey cleaning
Cleaned and processed regional Household Travel Survey (HTS) data, wrangling messy, multi-source travel-diary records into analysis-ready datasets used downstream by the planning and modeling teams.
EV ownership analysis
Analyzed regional electric-vehicle ownership patterns to help the agency understand where and how EV adoption is spreading across the central Puget Sound region.
Travel demand modeling
SoundCast ActivitySim vehicle-ownership model
Worked alongside PSRC's modeling team to implement the SoundCast ActivitySim vehicle-ownership model for the region, bringing the open-source ActivitySim framework into SoundCast so the agency's activity-based travel model can simulate how many vehicles regional households own. This connects directly to my doctoral research on car-ownership decisions.
More experience
Graduate Researcher
Sustainable Transportation Lab, University of Washington
EV charging optimization, demographic microsimulation, and travel-behavior modeling. See the research →
Teaching Assistant ×4
University of Washington
- IT Systems & Supply Chain Integration · Bill Keough
- Finance & Performance Management in Logistics · Dan Stull
- Freight Transport · Curt Heaslet
- Inventory Management · Dr. Apurva Jain
Teaching Assistant
Sharif University of Technology & Kharazmi University
Theory of Structures · Fluid Mechanics