Research Interests
Research Overview: Immune Aging, Frailty, and Resilience Across AncestryMy lab studies why immune systems age at different rates—and why some individuals or populations become vulnerable to infections, poor vaccine responses, and frailty, while others remain resilient. A central unsolved problem is that immune aging cannot be explained by static changes in gene expression alone. Instead, it reflects a breakdown in the dynamic control rules that govern how immune cells respond to threats, commit to action, and return to equilibrium.To decode these rules, we developed scIDiff (single-cell Inference of Differential operators), a computational framework that reconstructs the regulatory “operators” of immunity from time-resolved single-cell data. These operators—mathematically, time-dependent Jacobians—quantify the stability, sensitivity, and recovery capacity of immune cell states. They reveal not just where the immune system is, but how it is controlled.
A central discovery from this work is that immune regulation is built from a limited set of reusable operator archetypes. By decomposing dynamical tensors, we can track how these archetypes are deployed—or degrade—with age, ancestry, and environment. This allows us to formally distinguish:
Immune frailty — loss of stabilizing and restorative control
Immune exhaustion — dominance of hypersensitive or unstable modes
Immune resilience — rapid restoration of balanced regulatory architecture following perturbation
This operator-based approach is particularly powerful for studying ancestry-associated differences in immune aging, because it focuses on dynamical regulatory structure rather than baseline gene expression, reducing confounding from environment, socioeconomic factors, and technical bias. By comparing regulatory architectures across populations, we identify which control strategies are evolutionarily conserved and which are shaped by genetic background, metabolism, and lifetime immune history.