Peter Siew
PhD
Specialty: Climate Science, Machine learning
Te Herenga Waka - Victoria University of Wellington
Peter Siew has a research background in climate science, focusing on the interactions between the cryosphere and large-scale atmospheric circulation. He utilizes a range of statistical and modeling tools (e.g., causal algorithms, Bayesian statistics, and machine-learning methods, ranging from idealized to complex models) to improve long-term climate projections and diagnose underlying physical processes.
Working with the Antarctic Science Platform, Siew has built statistical emulators to model future changes in the Greenland and Antarctic ice sheets. These emulators are computationally efficient, allowing for the full quantification of uncertainty in future ice loss.