Hi, I’m Keren — a Senior Bioinformatics Scientist at Tempus AI, where I develop statistical models and algorithms that turn next-generation sequencing data into clinically actionable insights. My work spans Bayesian models for tumor purity estimation, copy-number variant detection, and short-variant and structural-variant calling — including validation studies for Tempus’s first FDA-approved tumor assay (xT CDx).
I hold a PhD in Epidemiology from the Keck School of Medicine of the University of Southern California, where I studied variant discovery in human DNA sequencing data and (epi)genome-wide association analysis to better understand the genetic and epigenetic risk factors of hematologic malignancies, such as childhood acute lymphoblastic leukemia and Hodgkin’s lymphoma. Earlier, I earned an MPH in Epidemiology from Columbia University’s Mailman School of Public Health and a BS in Pharmaceutical Sciences in Shanghai, China.
I’m passionate about genomic data science, data visualization, and precision medicine — finding clarity in large, messy biological datasets and communicating it well.
Research interests
- Cancer genomics and next-generation sequencing analysis
- Statistical genetics: GWAS, EWAS, polygenic risk scores, and causal mediation
- Reproducible bioinformatics pipelines and data visualization