I use tools from stochastic processes, probability theory, and differential equations to make sense of complex biological systems. Much of my dissertation research addresses questions arising from the ecology and evolution of infectious pathogens.

Office Location: | 017 Physics |

Office Phone: | (919)660-2870 |

Email Address: | |

Web Page: | http://www.math.duke.edu/~szl |

Starting Year: |
2007 |

Advisor(s): |
Michael C. Reed |

**Education:**BS University of Queensland 2006 MS 2009 BCommerce University of Queensland 2006

**Specialties:**-
Applied Math

Probability

**Research Interests:***Modeling the ecology and evolution of infectious diseases*In my research, I apply mathematics to questions arising from the ecology and evolution of infectious diseases. Systems in this field display nonlinear population dynamics, exhibit important behavior at multiple levels (intrahost and interhost), and are adaptive, that is, they undergo evolution. These properties are common across complex biological systems, and developing tools to tackle them will not only advance our understanding of infectious disease, but may also apply to structurally similar systems in other areas of biology. I approach these problems by seeking the most natural and insightful formulation. This principle, which underlies most of pure mathematics, is also powerful in elucidating fundamental properties of real biological systems. This means that rather than use a particular set of established tools, e.g. differential equations or stochastic processes, individual-based models or mean-field models, numerical solutions or stochastic simulations, I draw on my broad training in applied mathematics to formulate the most appropriate and informative model for addressing a specic biological question.

**Keywords:**Mathematical biology • Infectious diseases • Modeling