Amanda Mejia is an Associate Professor of Statistics at Indiana University and PI of the StatMIND lab, where she develops practical, user-friendly statistical methods and software to improve individual-level fMRI feature discovery. With a PhD in Biostatistics from Johns Hopkins and nearly a decade of academic experience, she bridges rigorous methodology and applied neuroimaging to boost accuracy and power in functional brain analyses. Her background in industrial engineering and early roles in risk analysis and operations research inform a pragmatic, systems-oriented approach to statistical tool design. She has a track record of translating advanced techniques into accessible software, making cutting-edge methods usable by neuroscientists and clinicians.
9 years of coding experience
9 years of employment as a software developer
Master of Science (MS) Industrial Engineering, Master of Science (MS) Industrial Engineering at Georgia Institute of Technology
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Johns Hopkins Bloomberg School of Public Health
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