Sung Q Lee

649 citations
41 papers · 487 · h-index 13

Impact in

Papers in

Sung Q Lee

37 papers receiving 459 citations

Peers

Sung Q Lee
Comparison fields: 5 of 73
  • Signal Processing 131
  • Biomedical Engineering 249
  • Cognitive Neuroscience 86
  • Electrical and Electronic Engineering 182
  • Computational Mechanics 65
Replace Li Fan with:
Li Fan China
José Escolano Spain
Swen Müller Brazil
Shuichi Sakamoto Japan
Harinath Garudadri United States
Juan J. García‐Bonito United Kingdom
Keisuke Hasegawa Japan
Yung-Hung Wang Taiwan
Paulo M. Massarani Chile
Kejing Ma China
Sung Q Lee relative to Li Fan China Li Fan's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sung Q Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sung Q Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sung Q Lee. 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 Sung Q Lee. The network helps show where Sung Q Lee may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201099
2 200355
3 202037
4 200928
5 202323
6 201321
7 200920
8 201618
9 202118
10 200016
11 201115
12 201413
13 202013
14 201911
15 202311
16 200410
17 200610
18 20069
19 20109
20 20208

About Sung Q Lee

Sung Q Lee is a scholar working on Biomedical Engineering, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Electrical and Electronic Engineering and Human-Computer Interaction, having authored 41 papers that have together received 487 indexed citations. Recurring topics across this work include Advanced MEMS and NEMS Technologies (12 papers), Acoustic Wave Resonator Technologies (7 papers), Neuroscience and Neural Engineering (6 papers), EEG and Brain-Computer Interfaces (6 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Gaze Tracking and Assistive Technology (4 papers), Innovative Energy Harvesting Technologies (4 papers) and Mechanical and Optical Resonators (4 papers). The work is most often cited by research in Signal Processing (131 citations), Biomedical Engineering (249 citations), Cognitive Neuroscience (86 citations), Electrical and Electronic Engineering (182 citations) and Computational Mechanics (65 citations). Sung Q Lee has collaborated with scholars based in South Korea, United States and Hong Kong. Frequent co-authors include Kee S. Moon, Dae‐Gab Gweon, Moon Gu Lee, Semyung Wang, Dae Sung Kim, Mincheol Shin, Philip A. Nelson, Filippo Maria Fazi, Jeongil Seo and Hye Jin Kim. Their work appears in journals such as Sensors, ETRI Journal, Advanced Healthcare Materials, Mechatronics and The Journal of the Acoustical Society of America.

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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