Teaching at UCLA
Environment 10: Introduction to Environmental Sciences
This course serves as an introduction to environmental science as a discipline and as a way of thinking. It will include discussion of critical environmental issues at local and global scales, with a focus on climate change, resource management on a finite planet, and biodiversity and ecosystem health. It will cover fundamental aspects of physical, chemical, and biological processes important to environmental science through a lens of earth science, atmospheric and oceanic sciences, and ecology and evolutionary biology, with a goal of introducing students to fields of study relevant to some of the minors available to the Environmental Science major (conservation biology, environmental systems and society, environmental health, environmental engineering, geography, atmospheric and oceanic sciences, and earth and space sciences). The course also serves as a prerequisite for upper division Earth Science requirement for the major.
Statistics 202C: Monte Carlo Methods
During the twentieth century, the development of statistical computing played a crucial facilitating role for the growth of the statistics discipline and the adoption of statistical methods within the scientific community and beyond. In the twenty-first century digital age, the amounts of data available for statistical analysis has grown tremendously, yielding new opportunities for statistical computing, as well as new challenges. Statistical computing constitutes an important part of a statistics education, and is highly valuable for statisticians in both academia and industry. This graduate level course introduces Monte Carlo methods for simulation, optimization, estimation, and learning. While the methods are general, the framing and motivation will often be from a Bayesian perspective.
Statistics M235: Modern Environmental Statistics
This course is focused on a practical understanding and application of statistical tools for environmental datasets. We cover a range of topics, including hypothesis testing, regression models, spatiotemporal modeling, and Bayesian approaches. Over the second half of the quarter, students work in small teams to complete and present a project analyzing an environmental dataset of their choice.
Environmental Science Senior Practicum
During the two-quarter practicum, seniors in Environmental Science work with an outside organization to solve an important problem related to the environment or sustainability. Over winter and spring of 2019, our practicum group is working with the NRDC to improve estimates of air pollution near the Port of Los Angeles related to diesel truck emissions.