Nina Otter

973 total citations · 1 hit paper
9 papers, 416 citations indexed

About

Nina Otter is a scholar working on Computational Theory and Mathematics, Mathematical Physics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Nina Otter has authored 9 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 5 papers in Mathematical Physics and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Nina Otter's work include Topological and Geometric Data Analysis (7 papers), Homotopy and Cohomology in Algebraic Topology (4 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Nina Otter is often cited by papers focused on Topological and Geometric Data Analysis (7 papers), Homotopy and Cohomology in Algebraic Topology (4 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Nina Otter collaborates with scholars based in United States, United Kingdom and Germany. Nina Otter's co-authors include Mason A. Porter, Heather A. Harrington, Ulrike Tillmann, Peter Grindrod, Roger J. Daly, Terry Kwok, Píetro Lió, Jiangning Song, Alex Boussioutas and Yiqun Hu and has published in prestigious journals such as Climate Dynamics, Journal of Pure and Applied Algebra and npj Precision Oncology.

In The Last Decade

Nina Otter

8 papers receiving 405 citations

Hit Papers

A roadmap for the computation of persistent homology 2017 2026 2020 2023 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A roadmap for the computation of persistent homology
    2017 369 citations Nina Otter, Mason A. Porter et al. EPJ Data Science profile →

Peers

Nina Otter
Ulrich Bauer Germany
Mikael Vejdemo‐Johansson United States
Vidit Nanda United Kingdom
Miroslav Kramár United States
José A. Perea United States
Peter Bubenik United States
Brittany Terese Fasy United States
Paul Bendich United States
Katharine Turner Australia
Jan Reininghaus Germany
Ulrich Bauer Germany
Nina Otter
Citations per year, relative to Nina Otter Nina Otter (= 1×) peers Ulrich Bauer

Countries citing papers authored by Nina Otter

Since Specialization
Citations

This map shows the geographic impact of Nina Otter's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nina Otter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Otter more than expected).

Fields of papers citing papers by Nina Otter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nina Otter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nina Otter. The network helps show where Nina Otter may publish in the future.

Co-authorship network of co-authors of Nina Otter

This figure shows the co-authorship network connecting the top 25 collaborators of Nina Otter. A scholar is included among the top collaborators of Nina Otter based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nina Otter. Nina Otter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Otter, Nina, et al.. (2024). Amplitudes in persistence theory. Journal of Pure and Applied Algebra. 228(12). 107770–107770. 1 indexed citations
2.
Otter, Nina, et al.. (2023). Alpha magnitude. Journal of Pure and Applied Algebra. 227(11). 107396–107396. 1 indexed citations
3.
Otter, Nina. (2022). Magnitude meets persistence: homology theories for filtered simplicial sets. Homology Homotopy and Applications. 24(2). 365–387. 3 indexed citations
4.
Wang, Yanan, Yu Guang Wang, Changyuan Hu, et al.. (2022). Cell graph neural networks enable the precise prediction of patient survival in gastric cancer. npj Precision Oncology. 6(1). 45–45. 35 indexed citations
5.
Strømmen, Kristian, et al.. (2022). A topological perspective on weather regimes. Climate Dynamics. 60(5-6). 1415–1445. 5 indexed citations
6.
Baez, John C., et al.. (2022). Applied Category Theory in Chemistry, Computing, and Social Networks. Notices of the American Mathematical Society. 69(2). 1–1. 1 indexed citations
7.
Otter, Nina, et al.. (2017). MOESM1 of A roadmap for the computation of persistent homology. Figshare. 1 indexed citations
8.
Otter, Nina, Mason A. Porter, Ulrike Tillmann, Peter Grindrod, & Heather A. Harrington. (2017). A roadmap for the computation of persistent homology. EPJ Data Science. 6(1). 17–17. 369 indexed citations breakdown →
9.
Baez, John C. & Nina Otter. (2017). Operads and phylogenetic trees. Theory and applications of categories. 32. 1397–1453.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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