Yoshiki Vazquez-baeza
Bioinformatics Lead
San Diego, California, United States
Summary
🤩
Rockstar🎓
Top SchoolYoshiki Vazquez-baeza is a Bioinformatics Lead in San Diego with 14 years of experience applying software engineering, machine learning, and statistics to high-dimensional biological data, especially human microbiome studies. He has led bioinformatics initiatives at BiomeSense and UC San Diego’s Center for Microbiome Innovation, coordinating large-scale, multi-omic analysis and industry-academia collaborations with IBM Research. A core open-source contributor, he has improved key scientific libraries like QIIME, scikit-bio, SciPy and NumPy—contributions that include implementing Procrustes analysis and enhancing plotting and testing infrastructure for datasets at the scale of hundreds of thousands of samples. Yoshiki pairs rigorous academic training (PhD and MS in Computer Science) with hands-on engineering across back-end development, QA, and statistical method implementation, enabling reproducible, production-ready research tools. He is passionate about elegant engineering and open science, and often turns complex statistical problems into robust, well-tested code used by the broader bioinformatics community.
14 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of California San DiegoDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of California, San DiegoBachelor of Science (BS), Biomedical/Medical Engineering, Bachelor of Science (BS), Biomedical/Medical Engineering at Universidad Iberoamericana, Ciudad de México
English, Spanish
Github Skills (22)
data-visualizations10
unit-testing10
algorithms10
scipy10
python10
testing10
pandas10
statistics10
data-visualisation10
statistic10
numpy10
bioinformatics10
data-visualization10
unit-test10
scientific-computing10
Programming languages (20)
Github contributions (5)
scikit-bio/scikit-bio
Dec 2013 - Nov 2019
scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources.
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:3 releases, 8 reviews, 373 commits in 6 years
Contributions summary:Yoshiki contributed primarily to the bioinformatics library, focusing on the development and integration of statistical analysis capabilities. They implemented functions for various statistical distributions and tests, including chi-square, binomial, and F-distributions. They also incorporated new methods for calculating correlations and performing Procrustes analysis, indicating expertise in statistical and mathematical methodologies relevant to the repository's domain.
scikitlicensedpythondata-sciencealgorithms-and-data-structures
biocore/qiime
Jun 2012 - Dec 2015
Official QIIME 1 software repository. QIIME 2 (https://qiime2.org) has succeeded QIIME 1 as of January 2018.
Role in this project:Back-end Developer
Back-end DeveloperContributions:292 commits, 10 PRs, 4 pushes in 3 years 6 months
Contributions summary:Yoshiki primarily contributed to the development of the `make_3d_plots` script. Their commits show efforts to add new features, such as the "first difference" option, which likely involves analyzing the differences between data points to produce a plot. They also made modifications to improve the script's functionality, like resolving option types and adding the functionality to weight the vector by a given metadata column. There are many tests confirming and testing their contributions.
qiimeanalysismicrobiomeqiime2
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