S.W. Nam

1.2k citations
89 papers · 958 · h-index 14

Impact in

Papers in

S.W. Nam

80 papers receiving 864 citations

Peers

S.W. Nam
Comparison fields: 5 of 106
  • Signal Processing 157
  • Human-Computer Interaction 67
  • Virology 48
  • Control and Systems Engineering 255
  • Computational Mechanics 177
Replace Alberto Landi with:
Alberto Landi Italy
Daniela Iacoviello Italy
Chris Kyriakakis United States
Jindong Liu United Kingdom
Hyun‐Chool Shin South Korea
Shin’ichi Warisawa Japan
Maarten van Walstijn United Kingdom
Sunil L. Kukreja United States
Steve Rothberg United Kingdom
Yujie Dong China
S.W. Nam relative to Alberto Landi Italy Alberto Landi's profile →
Citations per field
00.5×5.5×
Alberto Landi · 1×
Citations per year

Countries citing papers authored by S.W. Nam

Since Specialization
Citations

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

Fields of papers citing papers by S.W. Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.W. Nam. 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 S.W. Nam. The network helps show where S.W. Nam may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998149
2 1994106
3 200282
4 200772
5
Optimal Scheduling of Drug Treatment for HIV Infection : Continuous Dose Control and Receding Horizon Control
200368
6 201341
7 201337
8 200635
9 201726
10 199822
11 198921
12 201217
13 201417
14 199715
15 200313
16 200313
17 201511
18 198710
19 20029
20 20029

About S.W. Nam

S.W. Nam is a scholar working on Signal Processing, Electrical and Electronic Engineering, Computational Mechanics, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 89 papers that have together received 958 indexed citations. Recurring topics across this work include Advanced Adaptive Filtering Techniques (30 papers), Microwave Engineering and Waveguides (24 papers), Blind Source Separation Techniques (24 papers), Speech and Audio Processing (18 papers), Radio Frequency Integrated Circuit Design (17 papers), Image and Signal Denoising Methods (12 papers), Digital Filter Design and Implementation (7 papers) and Control Systems and Identification (6 papers). The work is most often cited by research in Signal Processing (157 citations), Human-Computer Interaction (67 citations), Virology (48 citations), Control and Systems Engineering (255 citations) and Computational Mechanics (177 citations). S.W. Nam has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include E.J. Powers, Chanan Singh, Sun I. Kim, I.D. Robertson, C.H. Lee, Mark D. Wiederhold, Brenda K. Wiederhold, Jin H. Seo, Dong Pyo Jang and Joon‐Hyuk Chang. Their work appears in journals such as Electronics Letters, IEEE Transactions on Microwave Theory and Techniques, IEEE Access, IEEE/ACM Transactions on Audio Speech and Language Processing and IEEE Transactions on Instrumentation and Measurement.

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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