Tian Zheng

WORK HISTORY

EDUCATION

SKILLS

ABOUT TIAN ZHENG

At Columbia, my research is to develop novel methods and improve existing methods for exploring and analyzing interesting patterns in complex data from different application domains. My current projects are in the fields of statistical genetics, bioinformatics and computational biology, feature selection and classification for high dimensional data, network analysis, modeling relational data, spatiotemporal modeling of remote sensing data (images, videos, LiDAR, etc). Especially, I have been developing statistical and computational tools for high dimensional data, searching for genetic interactions associated with complex human disorders, quantifying social structure and studying hard-to-reach populations using survey questions, with more than 80 peer-reviewed publications in journals including JASA, AOAS and PNAS. My work was recognized with the 2008 Outstanding Statistical Application Award from the American Statistical Association, The Mitchell Prize from ISBA and a Google research award. I became a Fellow of ASA in 2014. From 20••••20, I was Columbia Data Science Institute (DSI)\'s associate director for Education, committee member of the center for Foundations of Data Science in the Data Science Institute (DSI) at Columbia, and chair of the education committee of DSI. At Columbia, I teach two popular courses in data science, Applied Data Science (http://tzstatsads.github.io/) and Introduction to Data Science. I also led the production of Columbia\'s MOOC \"Statistical Thinking for Data Science and Analytics\" on edX in 20••••16. In 2017, I was recognized by the Columbia’s Presidential Award for Outstanding Teaching. I was the section chair for American Statistical Association’s section on Statistical Learning and Data Science in 2019.