
Project: Using Machine Learning for Calculating Construction Emissions
Ponsu Muthuraman ’26 evaluated the use of a machine learning tool to improve construction carbon emission estimation.

Ponsu Muthuraman ’26 evaluated the use of a machine learning tool to improve construction carbon emission estimation.

Danica Sun ’28 explored smarter resource use for one of Stanford’s major computing clusters.

Rachel Porter, PhD candidate, investigated alternatives for reducing reliance on Stanford’s natural gas-fired steam plant.

Kai Blakenship ’26 increased event frequency and outreach, as well as institutionalized and expanded admin and student partnerships.

For her Living Lab Project, Molly Tian worked with Mail & Package Services to lower emissions and decrease waste from mail deliveries.

Project Background There is significant value in buildings (carbon, cost, historical significance) that is lost when the business-as-usual approach of demolition and rebuilding is continued. …

Elanna Mak conducted outreach to promote the switch from plastic to recycled lab supplies and explored factors impeding sustainable alternatives for compounds.

Sammy Puckett, B.S. ’22, M.S. ’24, created narrative content to encourage Transportation site visitors to visualize changes for more sustainable commutes.

Yuan Tang, M.S. 2024, identified promising climate action plans for the Travel/Study program within the Stanford Alumni Association by analyzing emissions data.

Nikita Salunke helped shape Stanford’s electric vehicle (EV) charging infrastructure as a Living Lab Fellow.