
Data for the Public
EV-SIENT
Planning safe, code-responsive public EV charging
- What it is
- A decision-support model and planner for public EV charging
- The problem
- Every city wants more EV chargers, but few can show where the first ones should go, and why.
- What he built
- EV-SIENT ranks twelve public sites in Northern Virginia, and runs the same model on your own sites, right in your browser.
- The Method
- Score sites on four weighted parts
- Size ports and simulate waits
- Reweight the model 2,000 times
- Run it on your own sites
- The number
- 2,000reweightings of the model, to show how sure each rank is
- Role
- Built the model and its platform
- Stack
- Python, queueing and discrete-event simulation, in-browser planner
- Year
- 2026
- Team
- Five George Mason students, 2026 Future City Fellowship
























