I am a Professor of Statistics at Penn State and the associate chair of the Bioinformatics and Genomics graduate program. My research focuses on developing statistical methods to uncover complex patterns in large-scale biological data, with a long-standing emphasis on assessing and improving reproducibility in high-throughput genomics. I develop latent variable models and machine learning approaches to identify scientifically meaningful structure in high-dimensional data.

More recently, my work has expanded to social science data and the study of large language models, with a focus on human–AI collaboration and the reliability and reproducibility of data-driven scientific workflows. 

I received my Ph.D. in Statistics from the University of Washington and completed my postdoctoral training at the University of California, Berkeley. 

News:

• 09/15/26: Excited to share that our Nature Communications paper, “RETROFIT: Reference-free deconvolution of cell-type mixtures in spatial transcriptomics”, has been selected for the journal’s Editors’ Highlights collection in Computational and Theoretical Biology. 

• 09/05/26: We presented our paper "When F1 Is Not Enough: Auditing Codebooks for LLM-Assisted Annotation" in the American Political Science Association 2026

• 09/01/26: Our paper "OT-knn: a neighborhood-aware optimal transport framework for aligning spatial transcriptomics data" has been accepted by PLoS Computational Biology. Congratulations to Jia

• 07/30/26: Our paper "Scalar-Comparison Collapse in Autonomous Visualization Agents" has been accepted by IEEE VIS conference 2026, VAxAutoSci workshop. Congratulations to Abhinav, Qiuhai and Claire. Special congratulations to Abhinav Chinnaiyan, an undergraduate student in our group, for publishing his first 1st-authored paper

• 07/01/26: Our project with Huijuan Xu and Manyyu Du, "AI-Enabled Quantification of Transcriptional Condensate Dynamics to Predict Gene Regulation in Live Cells”" was selected for Huck seed grant