Jennifer A. Dionne

Gold-nanorod surface-enhanced Raman spectroscopy with LightGBM separates CAR T from untransduced T cells, tracks antigen-specific activation dynamics, and discriminates sorted CAR+ from CAR- patient T cells.

This paper uses single-cell Raman spectroscopy and machine learning to predict therapeutic response in melanoma, achieving >96% accuracy in cell line classification and 91% accuracy in patient drug resistance inference.

This paper develops a label-free, scalable method for bacterial detection in wastewater using SERS and machine learning, achieving over 85% accuracy at 10^9 cells/mL.

The paper shows p53 maintains nuclear architecture to reduce carcinogen sensitivity and mutagenic potential by altering chromatin structure and UV lesion abundance.