Summary
Paul Lott is a postdoctoral scholar with 13 years of experience applying computational genomics to cancer research, currently focusing on the genetics of breast, gastric, thyroid, and colon cancers in Central and South America. He leverages GWAS and both germline and somatic WGS/WES to dissect population-specific cancer risk and tumor biology. Trained at UC Davis where he developed StochHMM, a C++ HMM library for diverse biological datasets, he brings a strong algorithmic background to genomic analyses. His work bridges statistical modeling and practical sequencing pipelines, enabling discovery in underrepresented populations. Based in Elk Grove, California, he pairs deep academic rigor with hands-on lab and computational experience dating back to the University of Utah. An offbeat strength is his history of building flexible bioinformatics tooling that adapts classical HMMs to modern genomic problems.
13 years of coding experience
University of California, Davis
The University of Utah