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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