Abstract

In the modern data analysis paradigm, fitting models is easy, but knowing how to design or evaluate them is difficult. In this talk, we will adapt insights from graphical statistics and goodness-of-fit testing to modern problems, illustrating them with applications to microbiome genomics and climate systems science.

For the microbiome, we show how linking complementary displays can make it easy to query structure in raw data. We then describe connections between microbiome and text data, and how those connections suggest novel visual summaries and model diagnostics. Finally, we explain how artificial intelligence can be used to accelerate climate simulations, and introduce techniques for characterizing goodness-of-fit of the resulting models.

Viewed broadly, these projects provide opportunities for human interaction in the automated data processing regime, facilitating (1) streamlined navigation of data and (2) critical evaluation of models.

For more information about Kris visit: https://mila.quebec/en/person/kris-sankaran/