Carnegie Mellon University

Jing Lei

Jing Lei

Professor (on leave Spring 2025)

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

After graduating from the Department of Statistics at UC, Berkeley, in May 2010 with a Ph.D. under the supervision of Professor Peter Bickel, I worked at Google as a statistician for one year before I joined the Statistics Department at Carnegie Mellon University as a visiting research scientist.

Specific Research Interests

My main research area is statistical theory and methodology, including: Analyzing statistical properties of some popular methods and algorithms in machine learning and engineering, such as the particle filter, spectral clustering, and sparse PCA; Developing new statistical methods that are suitable for high-dimensional, complex data, including dimension reduction, regression, clustering, hypothesis testing, etc; Understanding the meaning and properties of relevant concepts and methods in related fields from a statistical perspective, such as data privacy, data assimilation, and conformal prediction. These insights will usually lead to useful improvements or modifications. I am also working on applied problems in astronomy and genetics, using nonparametric smoothing, network estimation, and multiple testing techniques.

Areas of Research