Summary
Suhana Bedi is a PhD student and consultant specializing in biomedical data science with six years of experience applying computational biology, biostatistics, and machine learning to healthcare problems. She transitioned from hands-on genomics research to building and evaluating foundation models for clinical insights, combining strong Python, Git, and pipeline engineering skills with domain expertise in multi-omics and clinical datasets. Her internships at Google and Microsoft produced scalable biomedical knowledge graphs and ML-ready pipelines that enabled advanced NLP and systems-biology analyses, reflecting a knack for turning complex biological data into usable AI assets. Based in San Jose, she balances rigorous research—co-advised at Stanford by leaders in biomedical AI—with practical product-minded work at OpenEvidence, aiming to move models toward real-world clinical impact. An understated strength is her history of building reproducible lab tooling (Snakemake, Jupyter frameworks) that accelerates collaborative research and model development.
6 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Data Science, Bachelor's degree, Data Science at The University of Texas at Dallas
Doctor of Philosophy - PhD, Biomedical Data Science, Doctor of Philosophy - PhD, Biomedical Data Science at Stanford University
French, English, Hindi