Patterns in Static: Identifying Causal Relationships In Environmental Data, Understanding chemical and biological interactions in the environment often requires studying a cumbersome amount of information. Yet understanding them is critical to solving a wide variety of problems: from air pollution and climate change to natural disaster recoveries. The complexity of these studies - the number of variables, the rapid evolution of these variables, and the difficulty in knowing or measuring all the variables involved - demands a unique approach to problem-solving.
This talk will cover a wide variety of environmental problem-solving that I have encountered in my scientific career. Subjects will range from air pollution to metagenomics, and some problems on the border of chemistry and biology. Rather than focus on “big-data” analytics, this talk will focus on straightforward approaches to simplifying problems and arriving at reasonable solutions.
