Jessica received the 2018 International Chinese Statistical Association (ICSA) Conference Junior Researcher Paper Award for the manuscript titled “Budget-Constrained Feature Selection for Binary Classification: a Neyman-Pearson Approach,” co-authored with Yiling Chen and Dr. Xin Tong.
Wei Vivian Li received the Dissertation Year Fellowship. Congratulations Wei (Vivian)!
Jessica was named as one of the six inaugural Johnson & Johnson WiSTEM2D (Women in Science, Technology, Engineering, Mathematics, Manufacturing, and Design) Scholars [ Johnson & Johnson Announcement ] [ Johnson & Johnson Profiles ] [ UCLA News ]
[ UCLA News ] Vivian and Jessica published an article on Nature Communications about a statistical method scImpute for imputing missing gene expression values due to dropout events in single-cell RNA-sequencing (scRNA-seq) data.
Vivian and Jessica published an article on The Annals of Applied Statistics about a statistical method MSIQ for more accurate and robust estimation of messenger RNA (mRNA) isoform abundance from multiple RNA sequencing (RNA-seq) data sets.
Jessica was named as one of the 2018 Sloan Research Fellows. [ Sloan Foundation Announcement ] [ New York Times ] [ University of California News ] [ UCLA News ] [ UCLA Physical Sciences News ]
Jessica and two collaborators (Dr. Xin Tong at USC and Dr. Yang Feng at Columbia) published an article on Science Advances about an umbrella algorithm to implement general binary classification algorithms the Neyman-Pearson (NP) paradigm, which aims to control the type I error (or the type II error by symmetry) under a pre-specified threshold with high probability while minimizing the other type of […]
Xinzhou and Kexin were named the best performers in the conference round of the NCI-CPTAC DREAM Proteogenomics Challenge (Subchallenge 1) and presented at the RECOMB/ISCB Conference on Regulatory & Systems Genomics with DREAM Challenges. Congratulations!
Jessica and Dr. Biggin published an article on Nucleic Acids Research about using statistics to quantitate translational control in yeast, adding a new work to their line of research on quantitating the central dogma (Li et al, PeerJ 2014; Li and Biggin, Science 2015).
Zahra received her Ph.D. in Statistics. Her dissertation title is “Community Detection in Networks with Node Covariates.” Surui received his M.S. in Statistics. His thesis title is “Imbalanced Binary Classification for Detecting Transcription Factor Binding Sites in H1 Human Embryonic Stem Cells.” Congratulations, Zahra and Surui!