Sungdong Kim

735 citations
22 papers · 221 indexed · h-index 9

Sungdong Kim

21 papers receiving 215 citations

Peers

Sungdong Kim
Comparison fields: 5 of 54
  • Health Informatics 10
  • Artificial Intelligence 111
  • Human-Computer Interaction 18
  • Applied Psychology 14
  • Atomic and Molecular Physics, and Optics 44
Replace Magdalena Garlińska with:
Magdalena Garlińska Poland
Yu-Ping Huang United States
Aayushi Dangol United States
Zhiwei Wu China
Siddhartha Banerjee United States
K. Quan United States
Ann Ackaert Belgium
Naoya Tate Japan
Xiaofei Zhou United States
Cory Stephenson United States
Sungdong Kim relative to Magdalena Garlińska Poland Magdalena Garlińska's profile →
Citations per field
00.5×5.5×
Magdalena Garlińska · 1×
Citations per year

Countries citing papers authored by Sungdong Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sungdong Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Sungdong 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 Sungdong Kim Line = papers co-authored together Sungdong Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20251
3 202433
4 20240
5 20242
6 202314
7 20231
8 20236
9 202313
10 20227
11 202214
12 20223
13 202215
14 202219
15 20197
16 20131
17 20121
18
Intra-Sentence Segmentation using Maximum Entropy Model for Efficient Parsing of English Sentences
20051
19
AR over MPEG-2 TS
20052
20 200457

About Sungdong Kim

Sungdong Kim is a scholar working on Artificial Intelligence, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 221 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (12 papers), Speech and dialogue systems (4 papers), Multimodal Machine Learning Applications (3 papers), Force Microscopy Techniques and Applications (2 papers), AI in Service Interactions (2 papers), Electronic Packaging and Soldering Technologies (2 papers) and 3D IC and TSV technologies (2 papers). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (111 citations) and Human-Computer Interaction (18 citations). Sungdong Kim has collaborated with scholars based in South Korea, Canada and Australia. Frequent co-authors include Hongsik Park, Hyunjung Shin, Seungbum Hong, Juhwan Jung, Young‐Ho Kim, Sang-Woo Lee, Donghyun Kwak, Minsuk Chang, Sang‐Woo Lee and Juho Kim. Their work appears in journals such as Applied Physics Letters, Japanese Journal of Applied Physics and Journal of Nanoscience and Nanotechnology.

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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