Qianying Lin

Postdoctoral Researcher Los Alamos National Lab

I am a postdoctoral researcher in Theoretical Biology and Biophysics (T-6) at Los Alamos National Laboratory (LANL), working with Drs. Ethan O. Romero-Serverson, Carmen Polina-Paris, and Thomas Leitner. Prior to LANL, I was a Data Science fellow of Michigan Institute for Data Science (MIDAS) at the University of Michigan, mentored by Profs. Aaron A. King and Edward L. Ionides. I received by Ph.D. and M.Phil degrees in Applied Mathematics from the Hong Kong Polytechnic University, under the supervision of Dr. Daihai He.

Infectious Disease Modelling
I apply statistical methods and build mathematical models to explore the growing patterns, disease characteristics, and transmission mechanisms of infectious diseases, including Human Influenza, HIV, Middle East Respiratory Syndrome (MERS), Ebola, Tuberculosis, COVID-19, etc. These studies help answer urgent and key questions on known or novel infectious diseases from the public and propose controling and prevention strategies.

The integration of data streams is highlighted in epidemiology and phylodynamics is in the spotlight. I work on developing the theoretical foundation for phyloynamic studies from the aspect of stochastic population processes, which is called Markov Genealogy Process (i.e., MGP). This system offers a unique and intuitive representation for genealogies and processes that generate them, unifies phylodynamic methods with different foundations, provides a novel interpretation for genealogies in phylodynamics through the filtering equation, and proposes efficient algorithms and implementation for statistical inferences. Furthermore, it’s extensible and can be applied to structured population, segmented viruses, and multifurcating phylogenies.