Summary
Kathryn Langenfeld is a postdoctoral researcher with nine years of experience at the intersection of environmental microbiology, virology, and computational biology, currently based at the University of Michigan. She develops and implements machine learning–enabled bioinformatic pipelines and quantitative metagenomic frameworks to improve absolute target quantification and reproducibility in environmental monitoring. Skilled in R, Python, Snakemake, HPC, and containerized workflows, she pairs computational rigor with hands-on lab expertise in NGS, qPCR/ddPCR, and viral concentration assays. Her work spans academia (Stanford and Michigan) and emphasizes method validation and robust pipelines that translate complex sequencing data into actionable environmental insights. Colleagues value her detail-oriented problem solving and ability to integrate interdisciplinary perspectives into novel methodological solutions. She brings the uncommon combination of deep quantitative training (Ph.D. in Environmental Engineering) and practical virology lab skills to tackle real-world monitoring challenges.
9 years of coding experience
11 years of employment as a software developer
Ph.D., Environmental Engineering, Ph.D., Environmental Engineering at University of Michigan
B.S.E., Civil Engineering (Focus in Environmental Engineering), B.S.E., Civil Engineering (Focus in Environmental Engineering) at University of Iowa