- Angelov, B. (2026). species2vec: Distributed species embeddings that recover range overlap from GBIF co-occurrence (Version v1.2) [Software]. Zenodo. https://doi.org/10.5281/zenodo.20354946
- Angelov, B., & Niedermaier, S. (2025). Closing the loop: Rapid prototyping for data science and AI products. Authorea.
- Angelov, B., & Castro-Gavino, D. (2024). The enabling data model and manifesto.
- Angelov, B. (2024). Visualizing outcomes: From black boxes to viable systems in software and society. Metaphorum, Berlin. Zenodo.
- Angelov, B. (2023). The study of progress: Entropy, complexity, and the great filter.
- Angelov, B. (2022). Managing the century of complexity: Origins, evolution and productive future avenues with systems thinking.
- Ryo, M., Angelov, B., Mammola, S., Kass, J. M., Benito, B. M., & Hartig, F. (2021). Explainable artificial intelligence enhances the ecological interpretability of black-box species distribution models. Ecography, 44(2), 199-205.
- Angelov, B. (2020). Research data strategy: Framework and motivating factors.
- Angelov, B. (2019). Review of species distribution modeling opensource software. ResearchGate.
- Angelov, B. (2018). sdmbench: R package for benchmarking species distribution models. Journal of Open Source Software, 3(29), 847.
- Angelov, B. (2013). Mud volcanoes: A window to the deep biosphere. Investigating succession and functional shifts in marine deep subsurface microbial communities exposed to mud volcanism [Doctoral dissertation, University of Bremen].