Donald Sheehy

Donald Sheehy is an Associate Professor in the Department of Computer Science at North Carolina State University's College of Engineering, where he conducts research at the intersection of computational geometry and topological data analysis. His work focuses on developing efficient algorithms for analyzing geometric and topological structures in data.

• B.S.E. in Computer Science from Princeton University (2005)
• Ph.D. in Computer Science from Carnegie Mellon University (2011)
• Postdoctoral researcher at Inria Saclay, France
• Former faculty member at University of Connecticut

Sheehy's research spans computational geometry, topological data analysis, and algorithm design. He develops mathematical frameworks for understanding shape, structure, and complexity in data, with particular expertise in persistence diagrams, Voronoi diagrams, Delaunay triangulations, and metric space analysis. His work bridges theoretical computer science with practical applications in data analysis, often developing sparse representations of complex geometric structures. He has made significant contributions to the understanding of approximation algorithms in geometric settings and has applied his techniques to problems in scientific computing and simulation analysis.

Analysis of his recent publications reveals a consistent focus on developing efficient algorithms for topological data analysis, particularly in creating sparse representations of complex structures like persistence diagrams and Delaunay filtrations. His work demonstrates a progression from fundamental geometric algorithms toward more sophisticated applications in data analysis, with increasing attention to practical computational efficiency while maintaining theoretical guarantees. A notable pattern is his development of approximation techniques that dramatically reduce computational complexity while preserving essential topological features.

• 2022 Fall Workshop on Computational Geometry ($14,700 NSF grant)
• CAREER: Algorithmic Challenges and Opportunities in Spatial Data Analysis ($277,465 NSF grant)

Sheehy has secured significant research funding from the National Science Foundation, including a CAREER award focused on developing new data structures and algorithms for spatial data analysis. His work on the Fall Workshop on Computational Geometry demonstrates leadership in the computational geometry community. While specific student advising information isn't provided in the source material, his research program appears to involve substantial collaboration with graduate students and postdoctoral researchers, as evidenced by his numerous co-authored publications.