Peter Macgregor

Peter Macgregor is a Lecturer at the School of Computer Science, University of St Andrews, specializing in algorithms for data science and machine learning. His research focuses on graph theory, clustering algorithms, and computational geometry for similarity search.

• Primary Affiliation: School of Computer Science, University of St Andrews
• Research Themes: Spectral clustering, Clustering algorithms, Graph algorithms, Similarity search, Theoretical computer science

Research Interests:
Data Science and Machine Learning are at the core of Peter Macgregor's research, with a particular emphasis on Spectral Clustering, Clustering Algorithms, and Computational Geometry. He explores topics like kernel density estimation for similarity graphs, efficient data structures for dynamic datasets, and theoretical guarantees for clustering methods.

Scientific Output Trends:
His recent work (2022-2025) spans spectral clustering optimizations, dynamic DBSCAN variants, and similarity graph approximations. Publications focus on algorithmic efficiency, clustering quality metrics, and theoretical foundations of machine learning.