Summary
Veronika Dubinkina is a bioinformatics fellow with 11 years of research experience applying computational and statistical methods to metagenomics, human microbiome studies, and bacterial evolution. Trained at MIPT and pursuing a PhD in Bioengineering at UIUC, she has built reference-free tools for fast WGS comparison, reconstructed metabolomes from microbial abundance, and modeled consumer-resource dynamics of bacterial ecosystems. Her work spans hands-on pipeline development in R and Python, machine learning for tumor drug-response prediction, and molecular dynamics modeling of bacterial membranes, reflecting a rare blend of theoretical, statistical, and systems-level approaches. Based in Chicago and authorized to work in the US for any employer, she excels at translating complex genomic and transcriptomic data into actionable biological insight. An understated strength is her track record of creating lightweight, custom tools that accelerate large-cohort metagenomic analyses across diverse collaborators.
11 years of coding experience
10 years of employment as a software developer
Bachelor’s Degree, Applied Physics and Mathematics, 4.75 out of 5.00, Bachelor’s Degree, Applied Physics and Mathematics, 4.75 out of 5.00 at Moscow Institute of Physics and Technology (State University) (MIPT)
University of Illinois Urbana-Champaign
English, French, Russian