Sally Benson

About

Sally Benson joined Stanford University in 2007 and is the Precourt Family Professor in the Department of Energy Resources Engineering within the School of Earth, Energy & Environmental Sciences. Her research focuses on technologies and pathways to reduce greenhouse gas emissions, including geologic storage of CO2 in deep underground formations and energy systems analysis for a low-carbon future. She has served as the Energy Division Director and Chief Strategist for the Energy Transition at the White House Office of Science and Technology Policy from 2021 to 2023. Benson has also been Co-Director of the Stanford Center for Carbon Storage and the Stanford Carbon Removal Initiative, and she served as Director and Co-Director of the Precourt Institute for Energy from 2013 to 2020. Her prior roles include Director of the Global Climate and Energy Project and positions at Lawrence Berkeley National Laboratory, where she was Division Director for Earth Sciences, Associate Laboratory Director for Energy Sciences, and Deputy Director. She is a Trustee of the Packard Foundation, a member of the Breakthrough Energy Innovation Council, and a Board Member of the Global Carbon Capture and Storage Institute. In 2023, she was elected to the American Academy of Arts and Sciences. Her extensive service includes participation in numerous advisory boards, research assessments, and editorial roles related to energy and climate change.

Research topics

• Physics
• Atmospheric sciences
• Environmental science
• Geology
• Meteorology
• Remote sensing
• Climatology
• Materials science
• Mechanics
• Geography

Selected publications

• U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow

  arXiv (Cornell University) · 2021-09-03 · 32 citations

  preprintOpen accessSenior author

  Numerical simulation of multiphase flow in porous media is essential for many geoscience applications. Machine learning models trained with numerical simulation data can provide a faster alternative to traditional simulators. Here we present U-FNO, a novel neural network architecture for solving multiphase flow problems with superior accuracy, speed, and data efficiency. U-FNO is designed based on the newly proposed Fourier neural operator (FNO), which has shown excellent performance in single-p…

  PublisherOA PDFDOI

• Real-time high-resolution CO$_2$ geological storage prediction using nested Fourier neural operators

  arXiv (Cornell University) · 2022-10-31 · 18 citations

  preprintOpen accessSenior author

  Carbon capture and storage (CCS) plays an essential role in global decarbonization. Scaling up CCS deployment requires accurate and high-resolution modeling of the storage reservoir pressure buildup and the gaseous plume migration. However, such modeling is very challenging at scale due to the high computational costs of existing numerical methods. This challenge leads to significant uncertainties in evaluating storage opportunities, which can delay the pace of large-scale CCS deployment. We int…

  PublisherOA PDFDOI

• Life Cycle Comparison of Industrial-Scale Lithium-Ion Battery Recycling and Mining Supply Chains

  SSRN Electronic Journal · 2022-01-01 · 4 citations

  articleOpen access
  PublisherDOI

• Securing the nuclear fuel supply chain for a growing energy future

  Nature Energy · 2025-12-29

  article
  PublisherDOI

• What Will it Take to Get to Net-Zero Emissions in California?

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

Frequent coauthors

• Gerald G. Mace

  University of Utah

  29 shared

• Charlotte Garing

  13 shared

• Alain Protat

  Australian Antarctic Division

  11 shared

• Ruhi S. Humphries

  9 shared

• Jacques A. de Chalendar

  Stanford University

  8 shared

• Ronny Pini

  Imperial College London

  8 shared

• Qilong Min

  University at Albany, State University of New York

  8 shared

• Ferdinand F. Hingerl

  7 shared

Labs

• Benson LabPI

  Not provided

Education

• Ph.D., Energy Resources Engineering

  Stanford University

  2013

• M.S., Energy Resources Engineering

  Stanford University

• B.S., Geophysics

  Stanford University

Awards & honors

• John Tyndall Award for Research in Carbon Capture and Storag…
• Elected Member, American Academy of Arts and Sciences (2023)
• Lifetime Achievement Award, Abdullah bin Hamad Al-Attiyah Fo…
• Engineers Health, Safety, and Environmental Award, Society O…
• Arthur D. Storke Lecturer, Columbia University (2018)

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