About PI

I am Perelman Professor of Biostatistics, Epidemiology and Informatics in Perelman School of Medicine at Penn.

I did my undergradute study in mathematics at Peking University in Beijing and received a Ph.D. degree in Statistics in 1995 from the University of Washington in Seattle under the supervision of Professor Elizabeth Thompson. I worked as a research associate biostatistician in the Section of Biostatistics at the Mayo Clinic in Minnesota for three years. I then joined the Rowe Program in Human Genetics at the University of California at Davis School of Medicine in the fall of 1998 as an Assistant Professor and was promoted to Associate Professor with tenure in 2001. I joined the University of Pennsylvania as a Professor of Biostatistics with tenure in May 2005. From April to June and also August 2004 I was a Visiting Associate Professor in the Department of Statsitics at Stanford University. From September 2011 to now, I am also a Professor of Statistics with a secondary appointment in the Department of Statistics and Data Science at the Wharton School of the University of Pennsylvania. I became the Perelman Professor of Biostatistics, Epidemiology and Informatics in Perelman School of Medicine at Penn in 2019.

I am an elected Fellow of The American Association for the Advancement of Science (AAAS), Fellow of the American Statistical Association (ASA), elected Fellow of the Institute of Mathematical Statistics (IMS) and elected member of the International Statistical Institute (ISI). I was elected as a Fellow of the AAAS for "distinguished contributions to statistical genetics methodology, promotion of statistical reasoning in society, and modeling of high dimensional genomic and metagenomic data."

My research has been at the interface between statistics and biology.

Teaching

I am a faculty member in three graduate groups: Biostatistics, Genomics and Computational Biology (GCB) and Applied Mathematics and Computational Sciences (AMCS). I have taught (1) Statistical methods for genomic data analysis; (2) Probability theory for 1st year Biostatistics PhD students.

  • Probability Theory: I used Casella and Berger's book and Ferguson's book.
  • Statistical Methods for Genomic Data Analysis: I use my own lecture note on "High Dimensional Statistics in Genomics: Methods and Applications".
  • Statistical Methods for Big Data in Biomedical Research: I use my own lecture note on "Statistical Methods for Big Data in Biomedical Research".