Diego Coelho
Visiting Professor at Universidade Federal do Rio Grande do Norte
Rio Grande do Norte, Brazil
Summary
👤
Senior🎓
Top SchoolDiego Coelho is a bioinformatics software engineer and visiting professor with 11 years of experience building production-ready genomics pipelines and analytical tools across academia and industry. He blends hands-on development (Python, R, SQL, Bash, Git) with workflow and cloud expertise—Nextflow, WDL, Docker, Kubernetes and AWS/GCP—to deliver scalable NGS, scRNA-seq and variant analysis solutions. At EMBL-EBI he contributed backend improvements to the high-profile Ensembl Variant Effect Predictor, enhancing gnomAD integration and frequency reporting, and more recently has led pipeline modernization and mentoring at Ryvu Therapeutics. He advises and teaches graduate students pro-bono through UFRN’s PPGBioinfo while continuing independent research and publications, reflecting a rare mix of production engineering and academic scholarship. Comfortable moving between Perl/MySQL legacy systems and modern cloud-native stacks, he’s known for pragmatic cleanups that improve data provenance and reproducibility.
10 years of coding experience
2 years of employment as a software developer
Master's degree Neuroscience, Master's degree Neuroscience at Federal University of Rio de JaneiroFederal University of Rio Grande do NorteResearch Doctorate Bioinformatics, Research Doctorate Bioinformatics at Johns Hopkins Bloomberg School of Public HealthBachelor's degree Biomedical Science, Bachelor's degree Biomedical Science at UERJ
Portuguese, English, Spanish, polonês
Github Skills (5)
bioinformatics10
configuration-management10
perl10
vcf-files9
data-processing9
Programming languages (10)
Github contributions (5)
Ensembl/ensembl-vep
Feb 2022 - Jan 2023
The Ensembl Variant Effect Predictor predicts the functional effects of genomic variants
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 reviews, 207 commits, 38 PRs in 11 months
Contributions summary:Diego primarily contributed to the Ensembl Variant Effect Predictor (VEP) project by modifying configuration files and core modules related to variant frequency data. They focused on integrating and updating the handling of gnomAD data, including adding new versions of gnomAD, renaming prefixes, and adjusting population names. The user also performed code cleanup, such as removing commented lines and ESP related hardcodes. Their contributions improved VEP’s ability to process and output variant frequency data from various sources.
ensemblgenomicsbioinformaticspredictorgenomic
Lexanomics/lexanomics.github.io
Jul 2023 - Nov 2024
Contributions:2 reviews, 7 PRs, 74 pushes in 1 year 4 months
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