Texas Tech University

Dan Cheng

College of Arts & Sciences, Department of Mathematics & Statistics

Dan ChengDr. Cheng studies statistical inference of random fields and dependent data, with applications in image analysis, signal detection, neuroscience and astronomy. He is also interested in probability theory, focusing on Gaussian random fields and extreme value theory. Dr. Cheng received his PhD in statistics from the Department of Statistics and Probability at Michigan State University in 2013. Prior to joining TTU, he did postdocs in the Department of Statistics at NC State University and the Division of Biostatistics at UC San Diego.

Recent Scholarship: Cheng, D. and Schwartzman, A. Multiple testing of local maxima for detection of peaks in random fields. To appear in Annals of Statistics.