Jianqing Fan

Also known as 范劍青

Jianqing Fan is a Princeton statistician whose work spans high-dimensional statistics, machine learning and generative AI. He earned a doctorate in statistics at Berkeley in 1989, held faculty posts at UNC Chapel Hill, UCLA and the Chinese University of Hong Kong, and joined Princeton in 2003. His 2008 sure independence screening paper proposed correlation learning for high-dimensional data, and his 2021 survey explained deep learning from a statistical point of view. He received the Wald Award in 2025 and became a member of the United States National Academy of Sciences in 2026. As of October 2026, he is a professor of finance and Operations Research and Financial Engineering at Princeton.

Now at: Princeton University
Works: 818
Citations: 62,049
h-index: 111
Rankings: #100 by h-index
Badges: Centurion
Loyal

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

1989–2003

Berkeley Ph.D. and faculty posts

In 1989, he completes a statistics Ph.D. at UC Berkeley under advisers David Donoho and Peter Bickel. He serves as assistant, associate and full professor at UNC Chapel Hill from 1989 to 2003, and as a professor at UCLA from 1997 to 2000. From 2000 to 2003, he serves as chairman and chair professor at the Chinese University of Hong Kong.
2003–2009

Princeton professor and IMS president

At Princeton, he joins as a professor in 2003 and becomes the Frederick L. Moore’18 Professor of Finance in 2006. From 2006 to 2009, he serves as president of the Institute of Mathematical Statistics.
2008

Sure independence screening

In 2008, he and Jinchi Lv publish “Sure Independence Screening for Ultra-High Dimensional Feature Space.” The paper proposes SIS, a correlation-learning method that reduces dimensionality from high to below the sample size.
2012–2015

Chair of Princeton ORFE

From 2012 to 2015, he chairs Princeton’s Operations Research and Financial Engineering department.
2018–2023

Statistics and academy honors

He receives the Noether Senior Scholar Award in 2018 and the Le Cam Award and Lectures in 2021. In 2023, he becomes a foreign member of the Royal Flemish Academy of Belgium for Science and the Arts.
2021

A deep-learning survey

In 2021, he coauthors “A Selective Overview of Deep Learning” with Cong Ma and Yiqiao Zhong. It introduces neural-network models and training methods from a statistical point of view.
February 2025

Dean of an AI school

In February 2025, CUHK-Shenzhen appoints him academic dean of its new School of Artificial Intelligence.
2025

A Wald Award and lecture

In 2025, he receives the Wald Award. In August 2025, the Joint Statistical Meetings schedules him for its Wald Memorial Award & Lecture, Part I, “Neural Causality Learning from Multiple Environments.”
2026

U.S. National Academy membership

In 2026, he becomes a member of the U.S. National Academy of Sciences.
As of October 2026

Princeton finance professor

At Princeton, he is the Frederick L. Moore’18 Professor of Finance and a professor of Operations Research and Financial Engineering. At Tsinghua in June 2026, he is the named speaker for “Intelligence Science and Society” and “SMART Fine-tuning Factor Augmented Neural Lasso,” with the first talk linking statistical learning and policy optimization to generative AI, large language models and digital economics. At the July 2026 Academia Sinica Statistical Summit, he joins the invited speakers as a Princeton professor.