David Kim

415 total citations
15 papers, 276 citations indexed

About

David Kim is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Cognitive Neuroscience. According to data from OpenAlex, David Kim has authored 15 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Human-Computer Interaction and 4 papers in Cognitive Neuroscience. Recurrent topics in David Kim's work include Augmented Reality Applications (6 papers), Interactive and Immersive Displays (5 papers) and Robotics and Sensor-Based Localization (4 papers). David Kim is often cited by papers focused on Augmented Reality Applications (6 papers), Interactive and Immersive Displays (5 papers) and Robotics and Sensor-Based Localization (4 papers). David Kim collaborates with scholars based in United States, Switzerland and Japan. David Kim's co-authors include Shruti Japee, Ikuko Mukai, Sean Marrett, Masaki Fukunaga, Leslie G. Ungerleider, Hsin-Liu Kao, Chris Schmandt, Ruofei Du, Susan R. Ross and Gary K. Beauchamp and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and European Journal of Neuroscience.

In The Last Decade

David Kim

12 papers receiving 272 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Kim United States 7 167 54 42 41 36 15 276
Alper Açık Germany 8 261 1.6× 96 1.8× 55 1.3× 13 0.3× 157 4.4× 11 367
Nobu Shirai Japan 12 284 1.7× 30 0.6× 17 0.4× 15 0.4× 41 1.1× 43 351
Laurent Madelain France 13 398 2.4× 50 0.9× 31 0.7× 14 0.3× 20 0.6× 32 441
S. Martinez-Conde United States 6 242 1.4× 53 1.0× 16 0.4× 8 0.2× 23 0.6× 9 325
Peter Scarfe United Kingdom 11 195 1.2× 95 1.8× 11 0.3× 22 0.5× 56 1.6× 30 345
Fabrizio Santini United States 6 284 1.7× 41 0.8× 13 0.3× 20 0.5× 54 1.5× 8 384
Vivian C. Paulun Germany 12 284 1.7× 53 1.0× 9 0.2× 40 1.0× 64 1.8× 23 339
Hugh S. Lusted United States 9 210 1.3× 31 0.6× 119 2.8× 34 0.8× 50 1.4× 17 324
Vincas Laurutis Lithuania 2 148 0.9× 50 0.9× 10 0.2× 13 0.3× 13 0.4× 10 232
Lili Tcheang United Kingdom 7 263 1.6× 149 2.8× 6 0.1× 19 0.5× 56 1.6× 14 407

Countries citing papers authored by David Kim

Since Specialization
Citations

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

Fields of papers citing papers by David Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Kim

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

All Works

15 of 15 papers shown
1.
Qian, Xun, Mark B. Sherwood, Zheng Xu, et al.. (2025). InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs. 1–22.
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Qian, Xun, Zheng Xu, Yinda Zhang, et al.. (2024). Experiencing InstructPipe: Building Multi-modal AI Pipelines via Prompting LLMs and Visual Programming. 1–5. 4 indexed citations
5.
Dogan, Mustafa Doga, Eric J. Gonzalez, Karan Ahuja, et al.. (2024). Augmented Object Intelligence with XR-Objects. 1–15. 19 indexed citations
6.
Qian, Xun, Feitong Tan, Yinda Zhang, et al.. (2024). ChatDirector: Enhancing Video Conferencing with Space-Aware Scene Rendering and Speech-Driven Layout Transition. 1–16. 7 indexed citations
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Carrasco, Darío I., Seong Su Kang, David Kim, et al.. (2023). Treatments with the specific δ‐secretase inhibitor, compound 11, promote the regeneration of motor and sensory axons after peripheral nerve injury. European Journal of Neuroscience. 58(6). 3555–3568. 1 indexed citations
10.
Li, David, et al.. (2022). RetroSphere. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 6(4). 1–36. 11 indexed citations
11.
Kim, David, et al.. (2020). A rare presentation of sexsomnia in a military service member. Journal of Clinical Sleep Medicine. 17(1). 107–109. 2 indexed citations
12.
Kao, Hsin-Liu, et al.. (2018). Skinmorph: texture-tunable on-skin interface through thin, programmable gel.. 196–203. 1 indexed citations
13.
Kao, Hsin-Liu, et al.. (2018). Skinmorph. 196–203. 36 indexed citations
14.
Mukai, Ikuko, David Kim, Masaki Fukunaga, et al.. (2007). Activations in Visual and Attention-Related Areas Predict and Correlate with the Degree of Perceptual Learning. Journal of Neuroscience. 27(42). 11401–11411. 142 indexed citations
15.
Yamazaki, Kunio, Edward A. Boyse, Judith Bard, et al.. (2002). Presence of mouse mammary tumor virus specifically alters the body odor of mice. Proceedings of the National Academy of Sciences. 99(8). 5612–5615. 44 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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