Stanford University has announced that economist and Nobel laureate Guido W. Imbens will assume the role of faculty director at Stanford Data Science (SDS) starting April 1. Imbens, a distinguished figure in econometrics, will succeed Professor Emmanuel Candès, who has led SDS since its inception seven years ago.
David Studdert, vice provost and dean of research, praised Imbens’ involvement with SDS from its early days. “Guido is an extraordinary data scientist who has been centrally involved in SDS from its earliest beginnings – most recently, as associate director and leader of the Stanford Causal Center,” said Studdert.
Professor Emmanuel Candès plans to return to full-time research after stepping down on March 31 but will continue his work with Marlowe, Stanford’s GPU-based supercomputer. He expressed confidence in Imbens’ capabilities: “I am thrilled to continue collaborating with Guido.”
Imbens holds positions at Stanford Graduate School of Business and the Department of Economics and is a senior fellow at the Stanford Institute for Economic Policy Research (SIEPR). His expertise lies in econometrics and causal inference methods.
In 2021, Imbens was awarded the Nobel Memorial Prize in Economic Sciences for his contributions to causal inference analysis alongside David Card and Joshua Angrist.
Imbens also leads the Stanford Causal Science Center, one of five SDS research centers focused on causality studies. “Stanford Data Science has proven to be a critical convener to advance interdisciplinary research ideas across campus,” said Imbens regarding his new role.
SDS was established in 2018 to foster interdisciplinary collaboration among data scientists. It offers advanced computational resources like Marlowe for AI-driven research. The initiative supports early-career faculty specializing in various fields including neurolinguistics and statistical methods for data science.
The center hosts doctoral students from all seven schools at Stanford annually, promoting cross-disciplinary learning and innovation through specialized research centers dedicated to scientific discovery via data science methodologies.
