Metrics and Algorithms for Computational Imaging and Systems Biology

My research interests broadly include the mathematics of data science, signal processing and computational imaging. I develop novel metrics and algorithms built on solid mathematical foundations that have application to diverse types of biological data spanning from single-cell RNA-sequencing to cryogenic electron microscopy.

Current research topics: 1) Single-cell RNA-sequencing data integration, 2) Cryo-EM heterogeneity analysis,
3) Algorithms for optimal transport

Research Interests

• Mathematics of data science
• Signal processing / Optimal transport
• Computational imaging / Cryo-EM
• Systems biology / Single-cell RNA-sequencing

Selected Publications

1. Y. Shi, A. Singer, and E. J. Verbeke, “Fast rigid alignment of heterogeneous images in sliced wasserstein distance,”
   SIAM Journal on Imaging Sciences, vol. 19, no. 3, pp. 1469–1515, 2026. doi: 10.1137/25M1742916.
2. E. J. Verbeke, M. A. Gilles, T. Bendory, and A. Singer, “Self Fourier shell correlation: properties and application to
   cryo-ET,” Communications Biology, vol. 7, no. 1, p. 101, Jan. 2024, issn: 2399-3642. doi: 10.1038/s42003-023-05724-y.
3. W. Sae-Lee, C. L. McCafferty, E. J. Verbeke, et al., “The protein organization of a red blood cell,” Cell Reports, vol.
   40, no. 3, p. 111 103, 2022. doi: 10.1016/j.celrep.2022.111103.