Sungbin Im

948 total citations
92 papers, 701 citations indexed

About

Sungbin Im is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Signal Processing. According to data from OpenAlex, Sungbin Im has authored 92 papers receiving a total of 701 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Electrical and Electronic Engineering, 20 papers in Biomedical Engineering and 18 papers in Signal Processing. Recurrent topics in Sungbin Im's work include PAPR reduction in OFDM (14 papers), Speech and Audio Processing (12 papers) and Underwater Acoustics Research (11 papers). Sungbin Im is often cited by papers focused on PAPR reduction in OFDM (14 papers), Speech and Audio Processing (12 papers) and Underwater Acoustics Research (11 papers). Sungbin Im collaborates with scholars based in South Korea, United States and United Kingdom. Sungbin Im's co-authors include E.J. Powers, Rong Huang, Yoan Shin, S. N. Atluri, Hojoon Lee, Daniel Gianola, Jean Louis J. L. Foulley, Magali San Cristobal, Geonwook Yoo and Taehyung Park and has published in prestigious journals such as ACS Nano, Nano Energy and IEEE Transactions on Signal Processing.

In The Last Decade

Sungbin Im

81 papers receiving 666 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sungbin Im South Korea 14 254 163 121 114 89 92 701
Bo Huang China 18 218 0.9× 162 1.0× 176 1.5× 264 2.3× 135 1.5× 79 1.1k
Antonio Iula Italy 22 286 1.1× 450 2.8× 104 0.9× 138 1.2× 369 4.1× 88 1.2k
Raimundo C. S. Freire Brazil 16 566 2.2× 340 2.1× 176 1.5× 147 1.3× 34 0.4× 231 1.1k
J. Hanson Germany 14 335 1.3× 189 1.2× 61 0.5× 97 0.9× 22 0.2× 127 725
Qiukun Zhang China 15 276 1.1× 206 1.3× 62 0.5× 250 2.2× 10 0.1× 53 896
Hongjun Xu South Africa 18 936 3.7× 119 0.7× 249 2.1× 202 1.8× 54 0.6× 147 1.2k
Zhao Zhang China 18 381 1.5× 414 2.5× 92 0.8× 697 6.1× 65 0.7× 68 1.1k
Jinyi Liu China 11 284 1.1× 130 0.8× 32 0.3× 40 0.4× 106 1.2× 25 562

Countries citing papers authored by Sungbin Im

Since Specialization
Citations

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

Fields of papers citing papers by Sungbin Im

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungbin Im

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

All Works

20 of 20 papers shown
1.
Im, Sungbin & Jae‐Seon Lee. (2025). Unified Sim-and-Real Scoring Methods for Robot Policy Selection. The Journal of Korea Robotics Society. 20(3). 371–380.
2.
Im, Eunji, Sungbin Im, Changgu Lee, et al.. (2025). Full Spin–Orbit Torque Switching of the Magnetic Cluster Octupole in Mn 3 Sn/W Bilayer via Interface Engineering. ACS Nano. 19(46). 39747–39756.
3.
Im, Sungbin, et al.. (2025). Robust TDOA Estimation Using Kernel Density Estimation for Noisy Environments. 1–5. 1 indexed citations
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Jing, Dalei, et al.. (2025). Fractal-shaped droplet microfluidics for highly scalable cell mechanoporation. Lab on a Chip. 26(1). 10–17.
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Im, Sungbin, et al.. (2023). Application of CNN Models to Detect and Classify Leakages in Water Pipelines Using Magnitude Spectra of Vibration Sound. Applied Sciences. 13(5). 2845–2845. 23 indexed citations
8.
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Im, Sungbin, et al.. (2020). Performance Evaluation of CNN-Based End-Point Detection Using In-Situ Plasma Etching Data. Electronics. 10(1). 49–49. 19 indexed citations
10.
Im, Sungbin, et al.. (2018). Drone Detection Using Convolutional Neural Networks with Acoustic STFT Features. 1–6. 52 indexed citations
11.
12.
Kim, Sunho, et al.. (2017). Design of SONAR Array for Detection of Bottoming Cylindrical Objects. Journal of the Institute of Electronics Engineers of Korea. 54(3). 15–21. 1 indexed citations
13.
Kim, Sun-Ho, et al.. (2016). Optimum Frequency Analysis for Sonar Transmit Signal design. Journal of the Institute of Electronics and Information Engineers. 53(5). 47–54. 1 indexed citations
14.
Im, Sungbin, et al.. (2013). Performance of the Contraction Mapping-Based Iterative Two-Dimensional Equalizer for Bit-Patterned Media. IEEE Transactions on Magnetics. 49(6). 2620–2623. 3 indexed citations
15.
Im, Sungbin, et al.. (2011). PAPR Reduction Techniques Analysis of Non-Contiguous OFDM in Cognitive Radio Systems. Journal of the Institute of Electronics Engineers of Korea. 48(9). 27–34. 1 indexed citations
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18.
Kim, Sungjun & Sungbin Im. (2003). The Effects of PRF and Slot Interval on the Data Throughput of PPM-Based Ultra Wide-Band Systems in Multi-Path Channels.. International Conference on Wireless Networks. 18–23. 1 indexed citations
19.
20.
Im, Sungbin & Myung-Jin Bae. (1996). Nonlinear Modeling Of Speech Signals Using A Sparse Volterra Model. 2. 760–763. 2 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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