Benjamin Risse

2.1k total citations · 1 hit paper
52 papers, 970 citations indexed

About

Benjamin Risse is a scholar working on Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Benjamin Risse has authored 52 papers receiving a total of 970 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cellular and Molecular Neuroscience, 9 papers in Computer Vision and Pattern Recognition and 7 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Benjamin Risse's work include Neurobiology and Insect Physiology Research (15 papers), Insect and Arachnid Ecology and Behavior (6 papers) and Species Distribution and Climate Change (5 papers). Benjamin Risse is often cited by papers focused on Neurobiology and Insect Physiology Research (15 papers), Insect and Arachnid Ecology and Behavior (6 papers) and Species Distribution and Climate Change (5 papers). Benjamin Risse collaborates with scholars based in Germany, United Kingdom and United States. Benjamin Risse's co-authors include Christian Klämbt, Xiaoyi Jiang, Nils Otto, Michael Mangan, Dimitri Berh, Barbara Webb, Devis Tuia, Mackenzie Weygandt Mathis, Tanya Berger‐Wolf and Holger Klinck and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Benjamin Risse

48 papers receiving 935 citations

Hit Papers

Perspectives in machine learning for wildlife conservation 2022 2026 2023 2024 2022 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. Perspectives in machine learning for wildlife conservation
    2022 348 citations Devis Tuia, Benjamin Kellenberger et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Benjamin Risse Germany 15 261 219 141 139 135 52 970
Alfonso Pérez‐Escudero Spain 15 130 0.5× 254 1.2× 150 1.1× 90 0.6× 468 3.5× 34 1.6k
Robert C. Hinz Portugal 5 95 0.4× 138 0.6× 82 0.6× 50 0.4× 259 1.9× 6 926
Alice A. Robie United States 11 679 2.6× 136 0.6× 181 1.3× 48 0.3× 507 3.8× 15 1.4k
John A. Bender United States 13 594 2.3× 218 1.0× 140 1.0× 87 0.6× 609 4.5× 25 1.5k
Blair R. Costelloe United States 7 37 0.1× 240 1.1× 57 0.4× 151 1.1× 133 1.0× 9 801
Sara Arganda Spain 11 186 0.7× 131 0.6× 73 0.5× 33 0.2× 399 3.0× 15 953
Sachit Butail United States 19 46 0.2× 130 0.6× 96 0.7× 45 0.3× 278 2.1× 59 1.2k
Gordon J Berman United States 13 400 1.5× 119 0.5× 89 0.6× 14 0.1× 359 2.7× 21 1.4k
Jacob M. Graving Germany 7 76 0.3× 108 0.5× 29 0.2× 43 0.3× 151 1.1× 9 656

Countries citing papers authored by Benjamin Risse

Since Specialization
Citations

This map shows the geographic impact of Benjamin Risse'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 Benjamin Risse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Risse more than expected).

Fields of papers citing papers by Benjamin Risse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin Risse. 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 Benjamin Risse. The network helps show where Benjamin Risse may publish in the future.

Co-authorship network of co-authors of Benjamin Risse

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Risse. A scholar is included among the top collaborators of Benjamin Risse 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 Benjamin Risse. Benjamin Risse is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Valkov, Dimitar, H. J. Schulze, H. Ahrens, et al.. (2025). Teach the Unteachable with a Virtual Reality (VR) Brain Death Scenario – 800 Students and 3 Years of Experience. Perspectives on Medical Education. 14(1). 44–54. 4 indexed citations
3.
Ernsting, Jan, et al.. (2025). pyAKI—An open source solution to automated acute kidney injury classification. PLoS ONE. 20(1). e0315325–e0315325. 1 indexed citations
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Fisch, L., Daniel Emden, Jan Ernsting, et al.. (2024). deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks. Computers in Biology and Medicine. 179. 108845–108845. 3 indexed citations
6.
Risse, Benjamin, et al.. (2024). Accelerating finite-difference frequency-domain simulations of inverse designed structures in nanophotonics using deep learning. Journal of the Optical Society of America B. 41(4). 1039–1039. 1 indexed citations
7.
Valkov, Dimitar, et al.. (2024). VR-based Competence Training at Scale: Teaching Clinical Skills in the Context of Virtual Brain Death Examination. Proceedings of the ACM on Human-Computer Interaction. 8(EICS). 1–31. 1 indexed citations
8.
Schulze, H. J., et al.. (2024). Immersive learning in medical education: analyzing behavioral insights to shape the future of VR-based courses. BMC Medical Education. 24(1). 1413–1413. 5 indexed citations
9.
Schwarz, Sebastian, et al.. (2024). Compensation to visual impairments and behavioral plasticity in navigating ants. Proceedings of the National Academy of Sciences. 121(48). e2410908121–e2410908121. 3 indexed citations
10.
Thiele, Sebastian, et al.. (2024). Towards a Dynamic Vision Sensor-based Insect Camera Trap. 7142–7151. 3 indexed citations
11.
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Risse, Benjamin, et al.. (2023). Inverse design of nanophotonic devices using dynamic binarization. Optics Express. 31(10). 15747–15747. 2 indexed citations
13.
Mangan, Michael, et al.. (2023). CATER: Combined Animal Tracking & Environment Reconstruction. Science Advances. 9(16). eadg2094–eadg2094. 13 indexed citations
14.
Thiele, Sebastian, Jörg Gromoll, Stefan Schlatt, et al.. (2023). Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears. Blood Advances. 8(1). 70–79. 10 indexed citations
15.
Tuia, Devis, Benjamin Kellenberger, Sara Beery, et al.. (2022). Perspectives in machine learning for wildlife conservation. Nature Communications. 13(1). 792–792. 348 indexed citations breakdown →
16.
Dierkes, Cathrin, et al.. (2022). Volumetric imaging reveals VEGF-C-dependent formation of hepatic lymph vessels in mice. Frontiers in Cell and Developmental Biology. 10. 949896–949896. 4 indexed citations
17.
Leenings, Ramona, Nils R. Winter, Lucas Plagwitz, et al.. (2021). PHOTONAI—A Python API for rapid machine learning model development. PLoS ONE. 16(7). e0254062–e0254062. 12 indexed citations
18.
Steffes, Georg, et al.. (2019). The Drosophila NCAM homolog Fas2 signals independently of adhesion. Development. 147(2). 13 indexed citations
19.
Mangan, Michael, et al.. (2019). Towards image-based animal tracking in natural environments using a freely moving camera. Journal of Neuroscience Methods. 330. 108455–108455. 29 indexed citations
20.
Risse, Benjamin, Michael Mangan, Luca Del Pero, & Barbara Webb. (2017). Visual Tracking of Small Animals in Cluttered Natural Environments Using a Freely Moving Camera. Figshare. 2840–2849. 31 indexed citations

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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