“Mathematics for Sustainability” will cover topics connected to resource assessment including measurement, estimation, equilibrium and flows. We will also study energy stocks and ecological systems/networks; in particular energy flows in the climate system. Various models for growth will be discussed. Exponential and logarithm functions will be used as first approximations of growth (decay) behavior, and logistic models will be studied when considering environmental limits to change. Systems, connections and feedbacks will be focused on in specific case studies selected from (depending on the interests of students) control of wildfires, recycling, population growth and questions of control, genetic engineering and the future of food, nuclear power, efficient use of electricity at home, solar energy, the ecological impacts of electric vehicles, and federal predator controls in the service of the livestock industry. Basic statistics and probability theory will be used to understand and measure risk, payoffs, and when possible, to make careful predictions. Students will complete an individual research project presented at the end of the course that will make use of mathematical tools to better understand a topic in sustainability.

Mathematical models have been used to explain, predict, and control the dynamics of infectious diseases for nearly a century. Beginning with early attempts to explain cholera outbreaks, mathematical epidemiology grew rapidly during the global spread of HIV in the 1980s. In 2020, the spread of novel coronavirus made phrases like 'basic reproductive number' and 'SIR modeling' part of our everyday discourse. This class will explore the construction, analysis, and application of mathematical models of infectious diseases. We will study the relationships between model assumptions and conclusions and learn about what mathematical models can and cannot tell us about epidemics.

Computer networks, algorithms, big data, and artificial intelligence (AI) are an ever-present part of daily life. These systems are often deployed in ways that have serious impacts on society, the economy, and the environment. This course introduces students to the basics of computer programming and how computer systems work. We will cover the basics of the Python programming language with examples drawn from many fields (e.g. chemistry, biology, linguistics, video games, art, music). Additionally, we will discuss more broadly how computers store and manipulate information in each of these areas. We will read and consider a variety of viewpoints that discuss the place of computers in society. Special attention will be placed on the social impacts of computing: how can we build computer systems that are environmentally conscious, accessible, and anti-racist?

This course examines the philosophical and psychological dimensions of the various epistemological platforms upon which we believe our capacity to think is based. Logic, science and mathematics are just a few of the paradigmatic examples of reasoning we will explore, along with failures of reasoning, such as conspiracy theories, logical fallacies and mythology.