Mathematics is a powerful tool which enables us to answer interesting questions. In my research, I use mathematical and statistical tools to characterize uncertainty in physical models. In the classroom, I aim to draw on these experiences to show students that mathematics and computational science are much more than just a set of prerequisites for their other coursework.

## Google Scholar:

## Current work:

Instructor, Computer Science

University of Colorado Boulder

## Research interests:

Uncertainty in climate model projections, sea level rise in particular, can lead to suboptimal, ineffective, and - at worst - outright dangerous policy decisions. To avoid this, we must use the information we have available make the best possible policy decisions. This requires accounting for not only varying forms of uncertainty in model parameters and projections, but deep uncertainty - uncertainty **in the uncertainty** in model structure and parameters. Statistical calibration approaches allow us to constrain these models and characterize the uncertainties inherent in both the model and data, and are a critical part of any modeling effort.

In particular, I am interested in future projections of sea-level rise and their impacts on coastal defense decision-making.

## Education:

PhD, Applied Mathematics, University of Colorado at Boulder, 2016

MS, Applied Mathematics, University of Colorado at Boulder, 2012

BA, Mathematics (hons.) and Astrophysics, Ohio Wesleyan University, 2010

## Contact information:

Office: ECOT 623

Email: anthony.e.wong@colorado.edu

Department of Computer Science

430 UCB

University of Colorado Boulder

Boulder, CO 80309-0430, USA