Meredith Lee provides strategic guidance and leadership to advance research and education priorities in areas of impact such as health and medicine, climate and sustainability, and human welfare and social justice. She partners across and beyond campus to design and enable transformative collaboration opportunities, leveraging interdisciplinary experience from academia, industry, nonprofits, and government. 

During the Obama Administration, Lee led the White House Innovation for Disaster Response & Recovery Initiative and managed strategic research investments in graph analytics, risk assessment, machine learning, data visualization, and distributed computing. Lee was previously the founding executive director of the National Science Foundation’s West Big Data Innovation Hub, where she launched public-private partnerships including regional, national, and global programs with the U.S. Department of Transportation, U.S. Department of Homeland Security, and U.S. Census Bureau. Earlier in her career, she served as a AAAS Science & Technology Policy Fellow at the Homeland Security Advanced Research Projects Agency, contributing to interagency initiatives through data.gov, challenge.gov, citizenscience.gov, the White House Office of Science and Technology Policy, and the National Science and Technology Council. 

Lee holds bachelor’s, master’s, and Ph.D. degrees in electrical engineering from Stanford University and was a postdoctoral fellow at the Stanford Canary Center for Cancer Early Detection. She has taught human-centered design and innovation at Stanford and in government, and continues to advise organizations with efforts in technology, data science, and multi-stakeholder collaboration. Lee is a California Senate appointee to the governing board of the Cradle-to-Career Data System, vice chair of the board of directors for the California Water Data Consortium, and a National Leadership Council member of the Society for Science and the Public. Her work has been featured by whitehouse.gov, ArsTechnica, Washington Post, Forbes, WIRED, Harvard Data Science Review, Bloomberg, and Nature.