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Wong, Tony Instructor

Positions

Research Areas research areas

Research

research overview

  • 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 storm surges, and their impacts on coastal defense decision-making.

keywords

  • Bayesian statistics, storm surge, sea-level rise, coastal adaptation, model calibration and simulation, deep uncertainty, climate risk management

Publications

selected publications

Teaching

courses taught

  • APPM 2350 Calculus 3 for Engineers (Spring 2019)
  • CSCI 1300 Computer Science 1: Starting Computing (Spring 2019)
  • CSCI 3022 Introduction to Data Science with Probability and Statistics (Spring 2019)
  • CSCI 2824 Discrete Structures (Fall 2018)
  • CSCI 2830 Special Topics in Computer Science (Fall 2018)
  • CSCI 3022 Introduction to Data Science with Probability and Statistics (Fall 2018)
  • CSCI 4950 Senior Thesis (Fall 2018)
  • CSCI 3022 Introduction to Data Science with Probability and Statistics (Summer 2018)
  • APPM 2350 Calculus 3 for Engineers (Spring 2018)
  • CSCI 2824 Discrete Structures (Spring 2018)

Background

International Activities

global connections related to teaching and scholarly work (in recent years)

Other Profiles