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.
Land, Buildings & Real Estate developed an ongoing commissioning (OCx) program to identify and implement opportunities to improve energy performance. The OCx team tackles one building at a time in month-long phases, looking for and implementing low-cost, high-outcome efficiency improvements. In 2023, OCx resolved more than 100 issues across the Thornton, Wallenberg, Havas, and Varian buildings. Many of these improvements were achieved through programming changes, which required no new hardware or space modifications. For example, over $4,000 per year was saved at Wallenberg with no-cost changes to the control systems.
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Sustainable Research Computing
Academics, Carbon, Community Engagement, Construction & Demolition, Efficiency, Emissions, Maintenance
Danica Sun ’28 explored smarter resource use for one of Stanford’s major computing clusters.
Decarbonizing Process Steam
Rachel Porter, PhD candidate, investigated alternatives for reducing reliance on Stanford’s natural gas-fired steam plant.