Research Partnerships
Stanford’s lands provide a living laboratory for groundbreaking research and innovation. Here, students, faculty, and operational staff collaborate to address real-world challenges, harnessing the university’s unique resources and diverse ecosystems to test theories and develop solutions that can make a lasting impact. From sustainable energy projects to cutting-edge technologies in water systems, the living lab approach allows researchers to engage with the community and the environment in meaningful ways.
Codiga Project
The William and Cloy Codiga Resource Recovery Center (CR2C) at Stanford accelerates the deployment of water and energy resource recovery systems. This innovative facility enables pilot testing of technologies for recovering clean water, nutrients, energy, and renewable materials from waste. Fostering collaboration between operational partners in LBRE, Stanford researchers, and external groups, CR2C advances promising technologies from the lab to real-world impact.
COOLER Research Project
The COOLER Research Project aims to enhance the resilience of Stanford’s utility chilled water system through smarter buildings. The project quantitatively assesses different chilled water demand management strategies using smart building control systems and advanced data platforms. A collaboration between Stanford LBRE, the Energy Resources Engineering Department, and the Precourt Institute for Energy, the project experiments with chilled water load management in various buildings, even down to individual rooms, enabling precise control and gradual demand reductions in non-critical areas while preserving critical zones.
SEEKER Project
SEEKER is an extension of the original COOLER research project, contributing to the overall goal of improving building control sequences, to enhance thermal comfort for occupants and energy performance. As the number of buildings that require retrofitting decreases, prioritization for additional building enhancement becomes necessary.
SEEKER aims to develop cheaper, faster, more accurate, and automated diagnostics to form a more accurate list of potential buildings to upgrade. To do so, SEEKER will leverage distributed sensors and modern data-driven methods, including AI and machine learning models. In addition, new datasets will be generated through experimentation for more robust modeling. Ultimately, the project will culminate in an automated data-driven diagnostic toolkit in order to detect zones that are short of optimal thermal comfort, as well as a novel experiment protocol and software.
Partnering with the Graduate School of Business to Understand Motivations Behind Environmental Actions
To better understand how highlighting specific motivations for performing sustainable actions may impact intentions and interest in sustainable behavior - specifically sorting waste - the Office of Sustainability partnered with Associate Professor of Marketing at the Graduate School of Business, Szu-chi Huang, to assess. In addition to furthering Stanford’s sustainability research, the study provides critical data to inform campus waste operations and communications.
