RyeAnne Ricker

Position: Pre-doctoral IRTA/PhD Student

Education: BS, Microbiology, Montana State University
BS, Biological Engineering, Montana State University
Graduate Certificate in Data Science, Foundation of Advanced Education in the Sciences

RyeAnne’s research focuses on utilizing machine learning for the detection of viral pathogens using Raman spectroscopy. Her early research focused on the direct detection of viruses from both cultured and clinical samples using both traditional (KNN, Logistic Regression, Random Forest, XGBoost) and deep learning (CNN, RNN) models. 

Her current research includes the comparison of Raman wavenumbers (features) with different incident wavelengths, the generation (GANs) of Raman spectra in data-limited studies, and the detection of viruses in low titer samples using signal processing techniques.

Career Goals: Upon completion of her PhD, RyeAnne will pursue a research position in either industry or government where she plans to continue using machine learning to explore biological problems. 

Fellowships and Awards

AIPR Best Manuscript Award – 2023
Fellows Award for Research Excellence – 2022
SEAS Graduate Service Award – 2022
National Science Foundation Fellow (NSF GRFP) 2021-2023
National Institute of Health Fellow (GPP) 2021-current
Collins Distinguished Doctoral Fellow 2021
SEAS Research Symposium Winner – 2021

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