Ashlynn Crisp

My research focuses on developing methods to model massive data. Scientific problems such as drug discovery and climate modeling require working with a massive amount of multivariate data, typically varying across time and space. Modern methods able to tackle scientific problems like these have become more accessible and commonplace in many fields. However, past a certain data size, even these methods may become infeasible due to their computational complexity. My work focuses on adapting algorithms to scale with the size and complexity of the data while reducing the tuning effort required. The aim of my research is to develop tools that enable scientists to make sense of datasets that were previously impossible to analyze.