Joshua Chiou is a computational scientist and senior advisor with 9+ years translating human genetics, single-cell genomics, and machine learning into drug discovery impact across industry and academia. He has led cross-functional target identification programs at Pfizer—modernizing workflows with LLMs, cloud data lakehouses, and CRISPR screen prioritization—and now advises at Eli Lilly. His work spans end-to-end analytics: GWAS and biobank-driven target discovery, deep learning models for genomic data, Nextflow pipelines for statistical genetics, and visualization platforms that inform portfolio decisions. A Nature and Nature Genetics first-author during his PhD, he pairs rigorous publication track record with practical assay and diagnostic experience (including a companion diagnostic acquisition), and a habit of mentoring junior scientists.
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