Yang Feng is an associate professor of Statistics at Columbia University. He obtained his PhD from Princeton University in 2010. His research is in high-dimensional statistical learning, a rapidly growing area in statistics that arises from the emergence of the "big data". In particular, he works on high-dimensional variable selection and classification, nonparametric and semi-parametric methods, bioinformatics and network models. The significance and recognition of his researches are evidenced by many publications in top statistical journals including the Annals of Statistics, Journal of the American Statistical Association, Journal of Royal Statistical Society Series B, etc. He is now on the editorial board of Statistical Analysis and Data Mining.
Faculty website: http://www.stat.columbia.edu/~yangfeng