Gustavo Arango is a Machine Learning Engineer with a PhD in Computer Science and a decade of experience applying deep learning, bioinformatics, and cloud technologies to interdisciplinary genomics and metagenomics problems. He blends strong academic training—from electronic engineering and pattern recognition to advanced computational biology—with hands-on software skills across Python, JavaScript/TypeScript, Java, and C++, enabling end-to-end solutions from models to web deployment. Recognized with a 2018 outstanding student award for multidisciplinary research, he has a track record of translating complex biological data into practical ML systems. Based in Arlington, MA, Gustavo is equally comfortable prototyping models, building cloud-native pipelines, and shipping user-facing web applications. A self-described programming and ML enthusiast, he brings research rigor and full-stack fluency to projects that sit at the intersection of biology and scalable software.
10 years of coding experience
Bachelor's degree (Electronic Engineering), Pattern Recognition, Bioinformatics, and Computational Biology, Bachelor's degree (Electronic Engineering), Pattern Recognition, Bioinformatics, and Computational Biology at Universidad Nacional de Colombia
Curation of Antibiotic Resistance Genes by using crowdsourcing
Contributions:5 commits, 10 PRs, 182 pushes in 7 days
pythonresistancecurationbioinformaticsgenes
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Gustavo Arango - Machine Learning Engineer at Virginia Tech