Fang Liu (statistician)
From Wikipedia, the free encyclopedia
Fang Liu is a Chinese-American statistician and data scientist whose research topics include differential privacy, data synthesis, trustworthy statistical learning, Bayesian statistics, regularization, missing data, and applications in biostatistics. She is a Notre Dame Collegiate professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame.[1][2]
Liu was talented in mathematics as a child, competed in mathematics competitions, and wanted to become a mathematician, but was discouraged from doing so by her parents, who wanted her to become a physician. As a compromise, she studied biology at Peking University,[2] where she earned a bachelor's degree in 1997.
She began her graduate studies at Iowa State University intending to study genetics, but quickly switched to a program in statistics,[2] and earned a master's degree there in 1999, and a Ph.D. from the University of Michigan in 2003.[1] Her dissertation, Bayesian Methods for Statistical Disclosure Control in Microdata, involved both data privacy and Bayesian statistics, and was supervised by Roderick J. A. Little.[3]
After completing her doctorate, she became a researcher at the Merck Research Laboratories. She returned to academia, joining the Notre Dame faculty, in 2011.[4] Her doctoral students at Notre Dame have included Claire McKay Bowen.[5]
