Vida Ravanmehr is a Senior Bioinformatics Analyst with nine years of multidisciplinary experience applying machine learning, genomics, and computational methods to translational and population-scale sequencing studies. She has developed and maintained production NGS pipelines at MD Anderson and led rare variant association analyses at Baylor College of Medicine, uncovering novel links such as ITSN1 with Parkinson’s disease and VSX2 with retinal detachment. Her background spans postdoctoral work in text mining and predictive models for cancer-kinase relationships, immune profiling analyses, and algorithm design from a PhD in Electrical and Computer Engineering. Skilled at mentoring trainees, optimizing HPC workflows, and translating methods across WES/WGS, RNA-seq, ATAC-seq and ChIP-seq, she combines deep technical rigor with a track record of novel biological discoveries. Notably, she brings a rare blend of signal-processing and graph-compression research experience to bioinformatics problems, enabling creative solutions to large-scale genomic data challenges.
9 years of coding experience
8 years of employment as a software developer
The University of Arizona
Master of Science (M.Sc.), Applied Mathematics, Master of Science (M.Sc.), Applied Mathematics at Isfahan University of Technology
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