Author

A. Y. Hsiang

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Evolutionary Biology· 2 Ecology· 1 Paleontology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:phylogenetics / evolution· 2 Approach:Bayesian inference· 1 Approach:deep learning· 1 Research Focus:ecology & biodiversity· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

A. Watanabe· 1 shared C. Ma· 1 shared C. Yu· 1 shared D. J. Field· 1 shared E. M. Steell· 1 shared E. Rayfield· 1 shared F. Qin· 1 shared H. Wang· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperPaleontology

A. Watanabe

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4 papers

Recent·Most cited

Relative Homoplasy Index: A New Cross-comparable Metric for Quantifying Homoplasy in Discrete Character Datasets

E. M. Steell, A. Y. Hsiang, D. J. Field

This paper introduces a new metric, the relative homoplasy index (RHI), to quantify homoplasy in phylogenetic datasets, showing it outperforms existing methods like CI and RI.

Zoological Journal of the Linnean Society · May 13, 2025Peer-reviewedEvolutionary Biology

AI in Paleontology

C. Yu, F. Qin, A. Watanabe, W. Yao, Y. Li, Z. Qin, Y. Liu, H. Wang, Q. Jiangzuo, A. Y. Hsiang, C. Ma, E. Rayfield, M. J. Benton, X. Xu

This paper reviews AI applications in paleontology, highlighting a gap between paleontological AI and mainstream AI studies, and discusses future directions for integrating AI into paleontological research.

bioRxiv · Aug 7, 2023 · PreprintPaleontology

Automated community ecology using deep learning: a case study of planktonic foraminifera

A. Y. Hsiang, P. M. Hull

This study uses deep learning to automate taxonomic identification of planktonic foraminifera, showing high congruence with traditional methods and reducing biodiversity bias.

bioRxiv · Oct 31, 2022 · PreprintEcology

Stepwise Bayesian Phylogenetic Inference

S. Hoehna, A. Y. Hsiang

This paper introduces a stepwise Bayesian approach to phylogenetic inference that propagates uncertainty through analysis steps, demonstrating its equivalence to joint inference under certain conditions and improved computational efficiency.

bioRxiv · Nov 11, 2020 · PreprintEvolutionary Biology