Courses Taught

Some of the classes I have offered in recent years, including pointers to upcoming courses and other resources, when they are available. Classes are listed only for the most recent time I have taught them.


  • Introduction to Climate Change

    This course, for undergraduate students, has two major parts:

    1. The basic scientific principles of the earth’s climate.

    2. Human dimensions of climate change.


  • Bayesian Statistical Methods

    This course, for graduate students, provides an introduction to Bayesian statistics, with a focus on both practical application of Bayesian regression methods to data as well as philosophical background on statistical inference and interpretation of statistical analyses. Topics include Bayes’s theorem and tools for applying it, including quadratic approximations, and Hamiltonian Monte Carlo sampling. Advanced methods include mixture models, multilevel regression methods, models incorporating ordinary differential equations, and critical evaluation of statistical models and modeling analyses.

  • Global Climate Change

    This course, for undergraduate and graduate students, has three major parts:

    1. The basic scientific principles of the earth’s climate.

    2. Impacts and possible responses to climate change.

    3. The politics of climate change.

    A laboratory section gives students a chance to analyze climate data and work with interactive computer models of the climate system.


  • Agent- and Individual-Based Computational Modeling

    This course (for undergraduate and graduate students) introduces agent-based and individual-based computational modeling with applications to ecological, social, and behavioral sciences and engineering. It covers designing and programming models and using the mnodels to conduct experiments.


  • Climate and Society: Drowning Cities

    This interdisciplinary class will explore legendary floods and the physical and cultural phenomena of the world’s “drowning cities,” bringing together diverse perspectives from environmental science and the history of architecture, engineering, and urbanism."

  • Data Science Methods for Smart City Applications

    A University Course offered under the auspices of the Vanderbilt Strategic Plan, this team-taught, project-based course will integrate technological and socio-economic approaches to challenges facing metropolitan areas experiencing unprecedented growth. It will address the infrastructure and resources needed for sustainable development and to maintain quality of life.