Homology-Separating Triangulated Euler Characteristic Curve
Summary
A novel Euler characteristic curve construction capable of separating homology classes while maintaining computational efficiency relative to traditional persistent homology techniques.
Research Context
This publication reflects graduate research conducted at the University of Cincinnati College of Engineering and Applied Science. It is included here to document the technical foundation behind Convergent Analytics' work in industrial analytics, applied AI, high-performance computing, and topological data analysis.
This peer-reviewed conference publication was produced as part of graduate research conducted at the University of Cincinnati College of Engineering and Applied Science.
The work introduces a triangulated Euler characteristic curve representation designed to capture topological structure that traditional Euler characteristic approaches may lose. The method improves the ability to distinguish homological features while preserving computational scalability.
The research contributes to ongoing efforts to develop practical topological descriptors that can be applied to large scientific, engineering, and industrial datasets without the computational expense of full persistent homology.
Citation
Malott, N.O., Lewis, R.R., Wilsey, P.A. Homology-Separating Triangulated Euler Characteristic Curve. IEEE ICDM 2022. DOI: 10.1109/ICDM54844.2022.00136