Spencer Long

Spencer Long

Staff Scientist

Spencer is a Data Scientist at UC Berkeley working with Dr. Adam Arkin on the ARPA-H funded PROTECT and ASMA initiatives. He joined the Arkin Lab to help build a structured, scalable data infrastructure to support multi-omic microbiome research in the human airway. His background spans astronomy, mathematics, bioinformatics, and machine learning, with experience integrating genomic and lifestyle data for predictive health modeling. Prior to joining the lab, he co-founded and led the bioinformatics division at a startup focused on personalized genetic health, where he developed risk prediction models for over 200 diseases.

In the Arkin Lab, Spencer is developing reproducible pipelines, metadata standards, and automated QC workflows for multi-modal datasets—including isolate genomics, metagenomics, metatranscriptomics, and cytokine data—to enable better understanding of host-microbiome interactions in airway health and disease. He is particularly interested in the intersection of synthetic microbial communities, host-pathogen exclusion, and data-driven hypothesis generation. Above all, he’s fascinated by science and deeply enjoys the research process—from the smallest technical challenge to the biggest biological questions.