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Eight Stanford faculty elected to National Academy of Sciences

Eight Stanford faculty are among the newest members of an organization created in 1863 to advise the nation on issues related to science and technology.

Eight Stanford University researchers are among the 120 newly elected members of the National Academy of Sciences. Scientists are elected to the NAS by their peers.

Image credit: Courtesy National Academy of Sciences

The new members from Stanford are Greg Beroza, the Wayne Loel Professor of Earth Science and professor of geophysics in the School of Earth, Energy and Environmental Sciences; Yi Cui, director of the Precourt Institute for Energy, and Fortinet Founders Professor, and professor of materials science and engineering; Amir Dembo, the Marjorie Mhoon Fair Professor of Quantitative Science and professor of mathematics and of statistics in the School of Humanities and Sciences; Lance Dixon, a professor of particle physics and astrophysics at SLAC National Accelerator Laboratory; Matthew Gentzkow, Landau Professor of Technology and the Economy in the School of Humanities and Sciences, and senior fellow at the Stanford Institute for Economic Policy Research (SIEPR); Leonidas Guibas, the Paul Pigott Professor of Engineering and professor of computer science; Guido Imbens, Applied Econometrics Professor at Stanford Graduate School of Business, professor of economics in the School of Humanities and Sciences, and senior fellow at SIEPR; and Mark Kasevich, professor of physics and of applied physics in the School of Humanities and Sciences.

Greg Beroza’s research explores source processes for shallow earthquakes, intermediate-depth earthquakes, induced earthquakes, and slow earthquakes. He works to improve earthquake monitoring by applying data mining and machine learning techniques, and develops methods to anticipate the strength of shaking in earthquakes using the ambient seismic field. His recent research has included detecting millions of imperceptibly small quakes using AI in diverse tectonic environments, developing protocols for managing risks from human-induced earthquakes, and developing the use of fiber-optic networks for earthquake studies.

Yi Cui studies nanoscience to enable clean energy and sustainability technologies. He is known for his seminal contributions on inventing breakthrough battery technologies for electric transportation and for storing renewable energy. He also has broad contributions on solar energy conversion, carbon-free hydrogen generation, cooling and warming textile, water and air filtration, and cryogenic electron microscopy for materials science.

Amir Dembo’s research focuses on probability theory and stochastic processes, information theory, and large deviations theory. His work has applications in communications, control systems, and biomolecular sequence analysis. Dembo is co-author of the textbook Large Deviations Techniques and Applications.

Lance Dixon works on developing methods for high-precision calculations in quantum chromodynamics, a part of the Standard Model of elementary particle physics that deals with quarks and their interactions. Such calculations are essential to interpreting experimental particle physics data from the Large Hadron Collider at CERN. He has applied related methods to studying other quantum theories, including one known as supergravity.

Matthew Gentzkow studies applied microeconomics, empirical industrial organization, and political economy with a focus on the media, politics, and health. Recently, Gentzkow has published studies on political polarization, social media use and disinformation, health care disparities, and consumer choices. Some of his most notable work is in media bias – including whether there’s demand for it.

Leonidas Guibas works on algorithms for sensing, modeling, reasoning, rendering, and acting on the physical world. His interests span geometric and topological data analysis, machine learning and learning architectures for geometric data, 3D computer vision and robotics, geometric modeling and 3D content synthesis, geometric algorithms, and natural language and emotional affect as it relates to shape and form.

Guido Imbens is most recognized for his work in econometrics, a method of studying economics using statistics. His research focuses on developing methods for drawing causal inferences in observational studies, using matching, instrumental variables, and regression discontinuity designs. In 2021, Imbens shared the Sveriges Riksbank Prize in Memory of Alfred Nobel Prize with David Card and Joshua Angrist “for their methodological contributions to the analysis of causal relationships.”

Mark Kasevich is an experimental physicist whose work informs development of high-accuracy navigation and sensing. His current research interests include quantum sensors of rotation and acceleration based on cold atoms (also known as quantum metrology), precision tests of general relativity, many-body quantum effects in Bose-condensed vapors, ultra-fast laser-induced phenomena, and advanced microscopy techniques.

The academy is a private, nonprofit institution that was created in 1863 to advise the nation on issues related to science and technology. Scholars are elected in recognition of their outstanding contributions to research. This year’s election brings the total of active academy members to 2,512.

Cui is also a senior fellow of the Stanford Woods Institute for the Environment, a member of Stanford Bio-X and the Wu Tsai Neurosciences Institute, and principal investigator of the Stanford Institute for Materials and Energy Sciences. Gentzkow is also an affiliate of the Institute for Human-Centered Artificial Intelligence (HAI). Guibas is also a member of Stanford Bio-X and the Institute for Computational and Mathematical Engineering (ICME), and an affiliate of HAI and the Stanford Woods Institute for the Environment. Imbens is also an affiliate of HAI and director of the Stanford Causal Science Center, which is part of the Stanford Data Science Initiative.

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