hedward.com

Harley Edwards is a biochemical engineering PhD and machine learning data scientist specializing in bioinformatics and computational biology. With 13 publications and eight years of combined academic and industry experience, Edwards develops scientific software and analytical methods that help researchers explore complex biological data. The work focuses on machine learning, next-generation sequencing (NGS), proteomics, systems biology, and synthetic biology.

Edwards builds machine learning models, bioinformatic pipelines, and graphical user interface applications for genomics, proteomics, and biological discovery. Featured tools include DPoP, clustering and Gene Ontology term analysis, and dynamic volcano plotting, designed to support investigation of time-dependent NGS and proteomic data. Research also applies unsupervised clustering, random forests, and inverse-design methods to identify useful biological features from omics and screening datasets.

Additional work includes kinetic modeling and network inference that connect molecular dynamics with cellular and fungal phenotypes, alongside CRISPR-based genome editing and genetic marker design for microbial hosts such as Yarrowia lipolytica. Based in Baltimore, Edwards shares research, career information, publications, and software through a professional portfolio.