Education & Certifications


  • MS, University of Rochester, Optics (2024)
  • BS, University of Rochester, Optics (2023)

Current Research and Scholarly Interests


Interested in using light to improve our understanding of the world around us through novel optical sensing devices and computational techniques.

All Publications


  • Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy. bioRxiv : the preprint server for biology Stiber, A., Quach, B., Ogunlade, B., Georgiadis, A., Chang, K., Li, Y., Quinn, P., Wang, H., Tsui, K. C., Ang, C., Sotillo, E., Mackall, C., Good, Z., Dionne, J. A. 2026

    Abstract

    Chimeric antigen receptor (CAR) T cell therapies have reshaped treatment for cancers and immune-mediated diseases, yet their safety and efficacy depend on both the proliferation of engineered cells and their dynamic functional state - features that remain challenging to monitor in real-time clinical settings. Current methods require labels, extensive processing, and provide only static snapshots of cell identity and activation. Here, we introduce a surface-enhanced Raman spectroscopy and machine learning approach that enables label-free single-cell identification of engineered CAR T cells and time-resolved, semi-continuous monitoring of their functional activation state. Using the intrinsic vibrational signatures from live cells, we detect spectral differences resulting from engineered receptor expression in donor-derived CD19- and GD2-targeted CAR T cells (nine and five donors, respectively) with 81-85% donor-level accuracy and resolve dynamic antigen-specific activation trajectories with temporal precision. These capabilities stem from biochemical signatures consistent with processes such as receptor expression, tonic signalling, and immune synapse formation, demonstrating a single method that reports both cellular identity and activation state with biochemical specificity. Our results extend CAR T cell monitoring beyond static phenotyping and establish the potential of SERS-ML analysis for rapid, point-of-care assessment of engineered immune cells.

    View details for DOI 10.64898/2026.02.22.707331

    View details for PubMedID 42124718

    View details for PubMedCentralID PMC13160088