
About
Corrine F Elliott is a Statistical Scientist at the University of California, Berkeley, where she earned her Ph.D. in Statistics in 2024. Her research bridges statistical methodology and interdisciplinary applications, including biostatistics, energy storage technologies, and materials science. She specializes in developing data-driven frameworks for scientific problem-solving, such as MERITS-Driven Simulation, and has contributed to clinical trial design, battery technology innovation, and policy analysis. Her work spans topics like PET imaging in oncology, redox shuttle chemistry for overcharge protection in batteries, and statistical methodologies for model validation.
Education highlights include a B.S. in Mathematics from the University of Kentucky (2017) and an M.S. in Statistics (2018). Her dissertation, 'MERITS-Driven Simulation: A Framework and Case Studies for Data Science Intervention in Scientific Problem-Solving,' was advised by Prof. Bin Yu. She has published extensively on redox flow batteries, phenothiazine derivatives, and statistical computing tools like the rFSA R package.
Her research interests emphasize interdisciplinary collaboration, with notable contributions to electrochemistry, medical research, and public policy. Though currently no awards are listed, her work reflects significant engagement in both technical and applied domains.
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