Stephen Kuhn

896 total citations
25 papers, 418 citations indexed

About

Stephen Kuhn is a scholar working on Artificial Intelligence, Astronomy and Astrophysics and Computer Networks and Communications. According to data from OpenAlex, Stephen Kuhn has authored 25 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 7 papers in Astronomy and Astrophysics and 6 papers in Computer Networks and Communications. Recurrent topics in Stephen Kuhn's work include Geochemistry and Geologic Mapping (9 papers), Planetary Science and Exploration (7 papers) and Distributed systems and fault tolerance (5 papers). Stephen Kuhn is often cited by papers focused on Geochemistry and Geologic Mapping (9 papers), Planetary Science and Exploration (7 papers) and Distributed systems and fault tolerance (5 papers). Stephen Kuhn collaborates with scholars based in United States, Australia and Russia. Stephen Kuhn's co-authors include Matthew J. Cracknell, Anya M. Reading, Timothy W. Lyons, Michael J. Baker, Jeffrey A. Steadman, Ross R. Large, Adrian Fabris, Peter McGoldrick, В. В. Масленников and Daniel D. Gregory and has published in prestigious journals such as Geophysics, Icarus and Economic Geology.

In The Last Decade

Stephen Kuhn

24 papers receiving 405 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Kuhn United States 9 256 140 100 50 49 25 418
Laura Tuşa Germany 14 342 1.3× 54 0.4× 230 2.3× 23 0.5× 54 1.1× 26 626
Xiangling Li China 11 179 0.7× 67 0.5× 123 1.2× 33 0.7× 31 0.6× 31 382
Robert Jackisch Germany 11 174 0.7× 36 0.3× 64 0.6× 29 0.6× 62 1.3× 25 386
Cecilia Contreras Germany 10 226 0.9× 30 0.2× 127 1.3× 12 0.2× 31 0.6× 21 409
Sheng Zhang China 14 88 0.3× 421 3.0× 97 1.0× 33 0.7× 22 0.4× 77 725
Daniel Wedge Australia 11 243 0.9× 131 0.9× 101 1.0× 28 0.6× 50 1.0× 38 395
Yongxian Zhang China 11 95 0.4× 165 1.2× 13 0.1× 27 0.5× 11 0.2× 66 360
René Booysen Germany 9 152 0.6× 25 0.2× 57 0.6× 19 0.4× 44 0.9× 16 284
E M Schetselaar Canada 11 235 0.9× 186 1.3× 36 0.4× 182 3.6× 74 1.5× 29 503
Xiaohui Li China 16 577 2.3× 200 1.4× 199 2.0× 186 3.7× 174 3.6× 54 772

Countries citing papers authored by Stephen Kuhn

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Kuhn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Kuhn

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Kuhn. A scholar is included among the top collaborators of Stephen Kuhn 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 Stephen Kuhn. Stephen Kuhn 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
1.
Verma, Vandi, Mark Maimone, Daniel Gaines, et al.. (2023). Autonomous robotics is driving Perseverance rover’s progress on Mars. Science Robotics. 8(80). eadi3099–eadi3099. 51 indexed citations
2.
Kuhn, Stephen, et al.. (2022). Cross-Cutting Flight Infrastructure Improvements on M2020. 2022 IEEE Aerospace Conference (AERO). 1–15. 1 indexed citations
3.
Chien, Steve, et al.. (2021). Enabling Limited Resource-Bounded Disjunction in Scheduling. Journal of Aerospace Information Systems. 18(6). 322–332. 8 indexed citations
4.
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Verma, Vandi & Stephen Kuhn. (2019). Refactoring the Curiosity Rover's Sample Handling Architecture on Mars. 343. 1–12. 2 indexed citations
7.
Cracknell, Matthew J., Peter McGoldrick, Stephen Kuhn, et al.. (2019). A comparison of random forests and cluster analysis to identify ore deposits type using LA-ICPMS analysis of pyrite. UTAS Research Repository. 3. 1274–1277. 1 indexed citations
8.
Kuhn, Stephen, Matthew J. Cracknell, & Anya M. Reading. (2019). Lithological mapping in the Central African Copper Belt using Random Forests and clustering: Strategies for optimised results. Ore Geology Reviews. 112. 103015–103015. 32 indexed citations
9.
10.
Verma, Vandi, Joseph Carsten, & Stephen Kuhn. (2019). The evolution of the curiosity rover sampling chain. Journal of Field Robotics. 37(5). 729–753. 7 indexed citations
11.
Kuhn, Stephen, Matthew J. Cracknell, & Anya M. Reading. (2018). The Utility of Machine Learning in Identification of Key Geophysical and Geochemical Datasets: A Case Study in Lithological Mapping in the Central African Copper Belt. ASEG Extended Abstracts. 2018(1). 1–4. 3 indexed citations
12.
Chien, Steve, et al.. (2018). Embedding a Scheduler in Execution for a Planetary Rover. Proceedings of the International Conference on Automated Planning and Scheduling. 28. 312–320. 12 indexed citations
13.
Kuhn, Stephen, Matthew J. Cracknell, & Anya M. Reading. (2018). Lithologic mapping using Random Forests applied to geophysical and remote-sensing data: A demonstration study from the Eastern Goldfields of Australia. Geophysics. 83(4). B183–B193. 78 indexed citations
14.
Large, Ross R., Matthew J. Cracknell, Stephen Kuhn, et al.. (2017). Random Forest classification of pyrite trace element composition to identify ore deposit type in far-field exploration and vectoring. eCite Digital Repository (University of Tasmania). 1 indexed citations
15.
Kuhn, Stephen, et al.. (2017). Fast Model Learning for the Detection of Malicious Digital Documents. 1–8. 7 indexed citations
16.
Kuhn, Stephen, Matthew J. Cracknell, & Anya M. Reading. (2016). Lithological mapping via Random Forests: Information Entropy as a proxy for inaccuracy. ASEG Extended Abstracts. 2016(1). 1–4. 8 indexed citations
17.
Anderson, Robert C., L. W. Beegle, J. A. Hurowitz, et al.. (2015). The Mars Science Laboratory scooping campaign at Rocknest. Icarus. 256. 66–77. 6 indexed citations
18.
Minitti, M. E., K. S. Edgett, R. A. Yingst, et al.. (2014). MAHLI After Dark: Nighttime Mars Hand Lens Imager Observations Under LED Illumination. LPI. 2029. 2 indexed citations
19.
Levy, Jonathan I., et al.. (2014). Assessing the impact of aviation environmental policies on public health. Transport Policy. 34. 21–28. 25 indexed citations
20.
Gilmore, Christopher K., et al.. (2011). Environmental Cost-Benefit Analysis of Ultra Low Sulfur Jet Fuel.

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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