San Kim

559 citations
38 papers · 382 · h-index 8

Impact in

Papers in

San Kim

30 papers receiving 352 citations

Peers

San Kim
Comparison fields: 5 of 75
  • Developmental and Educational Psychology 165
  • Human-Computer Interaction 68
  • Experimental and Cognitive Psychology 83
  • Language and Linguistics 46
  • Computer Vision and Pattern Recognition 51
Replace Jonas Braasch with:
Jonas Braasch United States
Dan Mikami Japan
Federico Domínguez Ecuador
Wolfgang Müeller-Wittig Singapore
Dmitry Ryumin Russia
Maryam Sadat Mirzaei Japan
Sylvie Gibet France
Stavroula–Evita Fotinea Greece
Denis Ivanko Russia
Frank R. Hartman United States
San Kim relative to Jonas Braasch United States Jonas Braasch's profile →
Citations per field
00.5×4.6×
Jonas Braasch · 1×
Citations per year

Countries citing papers authored by San Kim

Since Specialization
Citations

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

Fields of papers citing papers by San Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside San Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with San Kim Line = papers co-authored together San Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999188
2 202067
3 202025
4 202114
5 202110
6 20178
7 20208
8 20187
9 20216
10
Acidity and Chemical Composition of Precipitation at Background Area of the Korean Peninsula (Anmyeon, Uljin, Gosan)
20065
11 20205
12 20245
13 20214
14 20213
15 20193
16 20123
17 20213
18 20182
19
Comparison of the Effect of Various Chemical Peeling Agents on the Skin Barrier
20022
20 20252

About San Kim

San Kim is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Ocean Engineering and Electrical and Electronic Engineering, having authored 38 papers that have together received 382 indexed citations. Recurring topics across this work include Speech and dialogue systems (5 papers), Topic Modeling (3 papers), Robotics and Sensor-Based Localization (3 papers), Power Line Inspection Robots (2 papers), Marine and Coastal Research (2 papers), Fluid Dynamics Simulations and Interactions (2 papers), Technology and Data Analysis (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Developmental and Educational Psychology (165 citations), Human-Computer Interaction (68 citations), Experimental and Cognitive Psychology (83 citations), Language and Linguistics (46 citations) and Computer Vision and Pattern Recognition (51 citations). San Kim has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Melissa Singer, Susan Goldin‐Meadow, Dong-Geun Kim, Siheon Jeong, Ki‐Yong Oh, Jin Yea Jang, Mun-Kyeom Kim, Hoyoung Kim, Hyun Chung and Lawrence Amsel. Their work appears in journals such as ACS Sensors, IEEE Access, Scientific Reports, IEEE Transactions on Power Delivery and International Journal of Intelligent Systems.

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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