Research Scientist, Computation Institute, University of Chicago

Areas of Expertise:

Analysis and prediction of nonlinear systems
Data Assimilation
Parameter estimation
Forecast interpretation and evaluation

Hailiang's research ranges from the advancement of the theory of nonlinear dynamical systems to the application of these insights in the context of large-scale numerical models including weather and climate. He is particularly interested in advancing the understanding of predictability in the context of those models, and better understanding the dynamics, analysis, and interpretation (for decision support) of climate models in general. His previous research work includes parameter estimation via examining the dynamical consistency of the model and via probabilistic skill score; advancing pseudo-orbit data assimilation approach for state estimation; evaluating probabilistic skill in real world ensemble forecasts, and forecast interpretation using sustainable odds.

Hailiang received his PhD in statistics from the London School of Economics and Political Science (LSE) in 2009. He held post-doctoral positions within the Centre for Climate Change Economics and Policy and the Centre for the Analysis of Time Series at LSE before joining RDCEP at the University of Chicago in 2014.