Kevin Keegan is an independent computational biologist with a PhD and 14 years of experience building scalable bioinformatics pipelines and cloud-native tools using R, Python, AWS, and Docker. He has led interdisciplinary projects at institutions including the University of Chicago and Argonne National Laboratory, translating large-scale genomic and metagenomic datasets into actionable insights and visualization platforms. His work spans research, tool development (including contributions to MG-RAST and KBase integrations), and mentoring scientists to adopt computational methods. Based in Glen Ellyn, Illinois, he manages multiple simultaneous client and research projects as a self-employed scientist, emphasizing reproducible, efficient data processing. Uncommonly for a computational biologist, he combines deep wet-lab experience from his PhD and early technician roles with sustained software engineering practice, producing practical tools still used by research labs.
14 years of coding experience
4 years of employment as a software developer
Boston College High School (BC High)
PhD Biology/ Biochemistry/ Biotech, PhD Biology/ Biochemistry/ Biotech at Northwestern University
BA in Classics and Biology with High Honors in Classics, BA in Classics and Biology with High Honors in Classics at Brandeis University
Contributions:249 pushes, 1 branch in 9 years 3 months
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Kevin Keegan - Independent Scientist at Self employed