Lauren Anderson works on applying computational data analysis techniques to interesting astronomy problems. She combines data-driven models with physical models to harness both flexibility and interpretability. She also works on making models computationally tractable such that the model parameter space can be explored efficiently. Currently, Anderson is building a 3D dust map of the Milky Way galaxy using scalable Gaussian processes. She is also interested in falsifying dark matter models using stellar streams around the Milky Way galaxy observed by Gaia.