Clarence Mah is a computational biologist with 11 years of experience building open-source software and machine learning tools to extract subcellular insights from spatial omics and RNA biology. He developed bento-tools, a widely used Python framework for subcellular spatial transcriptomics analysis (part of the Scverse ecosystem) and applied deep learning, computer vision, and probabilistic models to decode MERFISH and in situ sequencing data. His work spans academia and industry—from a Genome Biology–published PhD and UCSD postdoc to roles at Singular Genomics and Stellaromics—bringing production-focused engineering practices (CI, unit testing, Nextflow pipelines) to high-content imaging and omics workflows. Comfortable with GPUs, HPC, and large public datasets (ENCODE, TCGA, GTEx), he blends rigorous biology with software craftsmanship to turn complex imaging and sequencing data into actionable biological hypotheses.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Science (B.S.), Bioinformatics, Bachelor of Science (B.S.), Bioinformatics at University of California, San Diego
Doctor of Philosophy - PhD, Bioinformatics and Systems Biology, Doctor of Philosophy - PhD, Bioinformatics and Systems Biology at University of California San Diego
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.