I am an Astronomy and Astrobiology PhD Candidate at the University of Washington. I am interested in the intersection of statistics, data science, and Astronomy. I like to work on problems where computational methods can streamline efficiency and improve result quality.
My thesis work revolves around novel computation methods for detecting very faint moving objects in existing datasets. The KBMOD algorithm (https://github.com/dirac-institute/kbmod) is a “digital tracking” or “track before detect” algorithm that uses massively-parallel GPU-accelerated statistical methods to detect faint Solar System objects in stacks of images. Candidate trajectories are then analyzed using a myriad of filtering techniques ranging from clipped mean filtering to DEEP learning. KBMOD is written in CUDA, C++, and python.