JordanĀ Eizenga
Postdoctoral Researcher at University of California, Santa Cruz
California, United States
Summary
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Top SchoolJordan Eizenga is a postdoctoral researcher at the UCSC Genomics Institute with a decade of experience applying computational methods to genomics and pangenomics. He earned a PhD in Bioinformatics from UCSC after a mathematics BS from the University of Michigan, blending rigorous theory with applied algorithm development. At UCSC he contributes to graph-based genome analysis and has made substantive back-end contributions to the widely used vg project, improving core components like the surjector algorithm, multipath mapper, and indexing systems. His work sits at the intersection of algorithm optimization and practical tooling for genome alignment and variation graphs, translating research prototypes into maintainable code. Based in California, he combines deep domain knowledge in computational genomics with hands-on software engineering to tackle large-scale bioinformatics challenges.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at University of MichiganUniversity of California Santa Cruz
Stackoverflow
151reputation
2kreached
0answers
9questions
Github Skills (14)
data-structures10
bioinformatics10
algorithms10
graph-algorithms10
c-language10
cprogramming-language10
data-structure10
back-end-development9
graph6
algorithm6
partitioning6
machine-learning6
concurrency6
multithreading6
Programming languages (13)
Github contributions (5)
vgteam/vg
May 2016 - Jan 2023
tools for working with genome variation graphs
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 releases, 4 reviews, 2324 commits in 6 years 9 months
Contributions summary:Jordan's commits indicate they were primarily involved in developing back-end functionality, with a focus on implementing and modifying core components related to the "surjector" algorithm, and general maintenance of the underlying graph data structures. Their contributions involve bug fixes and optimizations within the "vg" codebase, specifically focusing on components like "splicing", "multipath mapper", and the "index registry", implying interactions with core functionality for alignment and indexing. The commits demonstrate a working knowledge of bioinformatics tools related to graph-based genome analysis.
genomegenome-graphdnagenomicsbioinformatics
jeizenga/SeqPrep2
Mar 2016 - May 2018
Contributions:11 commits, 11 pushes in 2 years 2 months
mergingoverlap
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