Haike Xu

Haike Xu is a PhD candidate in electrical engineering and computer science whose research is focused on analyzing and designing algorithms. With the vast amount of data generated and collected today, nearest-neighbor search algorithms find applications in various domains, from constructing information retrieval systems to enhancing large language models for improved factuality. Supported by a MathWorks Fellowship, Haike will expand on his successful work on the nearest neighbor search problem, including building a theoretical understanding of why one such algorithm, DiskANN, is more efficient in practice than in theory, and identifying the relevant properties of datasets for which the algorithm is efficient. Going forward, Haike plans to explore additional new directions in nearest neighbor search, such as efficiently searching according to non-similarity-based metrics and constructing search indices with limited space and time resources. His research holds the potential to offer valuable new directions in algorithm analysis and design and serve broader needs for fast, efficient data processing and computing for research and industry.