Morgan Prior

Morgan Prior, class of 2024, has been working for 2 years with Prof. Noah Daniels’ research group. She originally attended a Ram Hacks meeting at which Dr. Daniels presented his work on manifold mapping, and applied to be an Arts & Sciences Fellow for Summer 2022 with Dr. Daniels as a mentor. Beyond the fellowship, she continued research through her junior and senior years. 

Morgan’s project has focused on a fast, sublinear-time algorithm for k-nearest neighbor (kNN) search, an important and commonly used algorithm for recommendation systems, data science, and machine learning. The resulting algorithm and software implementation (in the Rust programming language) provides fast, exact kNN search on very large datasets. This approach, called CAKES (CLAM-accelerated K-nearest-neighbor Entropy-scaling Search), allows for search of enormous datasets such as those seen in genomics and astronomy.

Morgan is first author on a paper introducing CAKES, titled “Let them have CAKES: A Cutting-Edge Algorithm for Scalable, Efficient, and Exact Search on Big Data”, currently under review at SIAM Mathematics of Data Science (SIMODS). A preprint is available on the arXiv. Since graduating, Morgan is moving up to the Boston area to pursue a Ph.D in Theoretical Computer Science at Tufts University.