Summary
Mikaela Cashman is a research software engineer who bridges computer science and the biological sciences, currently advancing R&D for the DOE Systems Biology Knowledgebase (KBase) at Berkeley Lab. With a PhD in Computer Science and a postdoc at Oak Ridge National Laboratory, she specializes in high-performance computing for biology, multi-omics integration, explainable machine learning, and GPU-accelerated workflows. Her background in software engineering research gives her a strong foundation in interpretable, testable scientific software, including combinatorial interaction testing and test prioritization studies applied to biological systems. She has led interdisciplinary projects spanning climate-scale analyses, network-based multi-omics integration, and high-throughput phenotype studies in collaboration with national labs and research institutes. Comfortable moving between production-scale HPC and rigorous software engineering methods, she brings 11 years of experience solving complex, interpretable problems at the intersection of systems biology and dependable software. An often-overlooked strength is her sustained focus on explainability—making biological models and configurable scientific software auditable and usable by domain scientists.
11 years of coding experience
9 years of employment as a software developer
Bachelor of Arts (B.A.), Mathematics and Computer Science, Bachelor of Arts (B.A.), Mathematics and Computer Science at Coe College
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Iowa State University
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Nebraska-Lincoln