Broadly, I am interested in studying how spatiotemporal organization and interaction networks affect the function of biological systems. Below are some specific interests and projects.


Can we uniquely estimate the parameters of a mathematical model from the data for the system it represents? Structural identifiability is a necessary condition to do this! Moreover, a model that is unidentifiable may have the same behavior for different combinations of parameters: two sets of parameters could fit the data equally well but tell vastly different stories about the underlying mechanism of the system. This can lead to erroneous interpretation and over-interpretation of parameter fitting and modelling results. With Professor Marisa Eisenberg, I have worked on this problem for very general classes of infectious disease models (report).

Mathematical Biology

With Professor Marisa Eisenberg, I have studied phenomena where spatial organization contributes to the progression of an outbreak (population scale) or disease (cell/tissue scale). I am interested in developing simple mechanistic models to give insights into the role of spatiotemporal dynamics in these processes. See my papers for two papers on Ebola dynamics in West Africa (population scale) and a report on modelling the interaction between cancer adn the nerve (cell/tissue scale).

Cancer/RNA Biology

I also work on molecular biology and computational/RNA biology projects at the Chinnaiyan lab. I am interested in the causes, patterns, and implications of gene expression heterogeneity. I am currently developing software to gather and analyze data cell-level heterogeneity (transcriptional and morphological). Our lab hopes to apply these tools to study rare-cell populations in the context of cancer.

Schematic of smFISH analysis, Hagoromo chalk on blackboard, 2018.