Tareq Al-Shargabi is a biomedical engineer with education and training in data science, physiological signal analysis, and biomedical research. He earned a master’s degree in biomedical engineering in December 2013, and worked at Children’s National Hospital in Washington, D.C. until 2021, with focus during those studies and work on analyzing physiological signals in newborns and comparing patterns between healthy and critically ill infants. The work involved close collaboration with clinicians and statisticians in study design and interpretation.
His expertise includes data analytics and research impact evaluation. He has worked extensively with NIH grant data—categorizing applications, analyzing funding trends, evaluating scoring systems, and studying the relationship between funding and outcomes such as publications and patents.
Al-Shargabi is passionate about integrating AI into biomedical data analysis. He develops data-driven web applications using R Shiny and Python (Voila) to support decision-making and to track spending. He has acquired experience in applying machine learning and topic modeling to biomedical texts, and he continuously explores new tools and methodologies to uncover insights. He applies technical skills and subject-matter understanding to interpret findings in the context of biomedical relevance, translating data into insights that inform strategy, policy, and research priorities.