Kevin P. Keegan—Page *

Kevin P. Keegan, Ph.D.

*** ****** ******, **** *****, IL 60137

847-***-****

ad1t5m@r.postjobfree.com

LinkedIn: https://www.linkedin.com/in/kevinkeegan

Google Scholar: https://scholar.google.com/citations?hl=en&user=0QH6bsQAAAAJ SUMMARY

Versatile Big Data Analyst and Computational Biologist with a proven track record of leveraging cloud-based computing to extract actionable insights from intricate, multidisciplinary datasets. Proficient in developing scalable analytical tools and adept at seamlessly transitioning between traditional wet-lab biology and advanced computational methodologies. Skilled in managing diverse research projects spanning genomics, circadian biology, metagenomics, and more. Agile learner, and teacher, known for swiftly mastering new programming languages and technologies to address complex biological inquiries with computational precision.

EDUCATION

Northwestern University, Evanston, IL

Doctor of Philosophy in Biology, Computational Biology Focus, 2002 - 2009

• Conducted pioneering research in daily biology rhythms using computational methods

• Developed software for large-scale data analysis, contributing to highly cited scientific articles

• National Science Foundation Graduate Research Fellowship Honorable Mention (2003 & 2004) Brandeis University, Waltham, MA

Bachelor of Arts in Classics and Bachelor of Arts in Biology, 1996 - 2000

• Graduated with High Honors in Classics and Honors in Biology

• Howard Hughes Undergraduate Research Fellowship recipient (1998 & 1999) SKILLS

Computational Skills:

• R, Matlab, Python, Perl, Shell scripting

• Windows, OSX, Unix/Linux

• Microsoft Office, Apache Open Office

• Cloud computing tools: Amazon EC2, Github, APIs, Docker, Common Workflow Language Analytical Proficiency:

• PCA, PCoA, Clustering, Heatmap-dendrograms, Time series analyses

• Machine Learning/AI techniques, Modeling

• Automated error detection in DNA sequence data, pattern recognition algorithms Biological Expertise:

• Experimental methods in biological and biochemical wetlab research

• DNA/RNA high throughput sequencing technologies

• Expertise in circadian biology, genomics, metagenomics, human and soil microbiome EXPERIENCE

Self Employed, Chicago, IL (2017 - Present)

Independent Scientist, Big Data Analyst

• Diverse projects catering to client requirements in computational biology Center for Data Intensive Science, University of Chicago, Chicago, IL (2015 - 2017) Senior Bioinformatician

• Managed interdisciplinary research projects with private and academic collaborators

• Led cloud-based computational resources for diverse research goals Kevin P. Keegan—Page 2

• Developed software tools for large-scale data analysis and visualization Argonne National Laboratory, Lemont, IL (2013 - 2015) Assistant Computational Biologist

• Spearheaded large-scale data-science-based research for US Department of Energy

• Built software tools for data analysis in projects such as MG-RAST, KBase, and the GDC

• Mentored biologists to utilize computational tools for analysis of metagenomics data TEACHING & LEADERSHIP

• Graduate student TA in Biology & Molecular Biology, Northwestern University

• Invited Instructor for Comparative Analyses of Metagenomic Data, MSU Microbial Metagenomics Summer Course

• Mentored high school, undergraduate, and graduate students in computational biology AUTHORED SOFTWARE

• AMETHST: Analysis method selection tool (https://github.com/MG-RAST/AMETHST)

• matR: Metagenomic Analysis Tools for R (http://cran.r-project.org/web/packages/matR/)

• DRISEE: Duplicate Read Inferred Sequencing Error Estimation (https://github.com/MG-RAST/DRISEE) SELECTED PUBLICATIONS

1. KBase: The United States Department of Energy Systems Biology Knowledgebase. (Nat Biotechnol, 2018) 2. The MG-RAST metagenomics database and portal in 2015. (Nucleic Acids Res, 2015) 3. Bacterial community structure and functional contributions to emergence of health or necrotizing enterocolitis in preterm infants. (Microbiome, 2013)