Research Interests

Dynamic processes such as cell growth, stress responses, and differentiation are controlled by the intricate interplay of genomic and metabolic programs. To understand how cells determine their phenotypes from environmental and historical cues requires characterizing these programs in single live cells. However, almost all assays in biology are inherently destructive, severely limiting our ability to track dynamic changes over time.

My lab is interested in developing novel optical, genomic, and computational tools for non-destructive, single-cell analysis of gene regulation and metabolism. One example is Raman2RNA, which combines Raman microscopy with machine learning to predict RNA expression profiles in single living cells, enabling “live-cell omics” measurements without destroying the cell. This approach makes it possible to follow gene expression dynamics in individual cells over time, opening new directions for the field. By bringing in tools from optical engineering and computational biology, we aim to tackle the toughest challenges in biology and medicine.