Myeonghwi Kim

1.0k total citations · 2 hit papers
7 papers, 637 citations indexed

About

Myeonghwi Kim is a scholar working on Artificial Intelligence, Epidemiology and Computational Theory and Mathematics. According to data from OpenAlex, Myeonghwi Kim has authored 7 papers receiving a total of 637 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Epidemiology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Myeonghwi Kim's work include Data-Driven Disease Surveillance (2 papers), Adaptive Dynamic Programming Control (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). Myeonghwi Kim is often cited by papers focused on Data-Driven Disease Surveillance (2 papers), Adaptive Dynamic Programming Control (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). Myeonghwi Kim collaborates with scholars based in South Korea, United States and Czechia. Myeonghwi Kim's co-authors include Beakcheol Jang, Jong Wook Kim, Gaspard Harerimana, Inhwan Kim, Hugh L. Montgomery, Paul Abbott, Wolfgang P. Schleich, Helmut Maier and J. W. Neuberger and has published in prestigious journals such as IEEE Access, Sensors and Applied Sciences.

In The Last Decade

Myeonghwi Kim

7 papers receiving 612 citations

Hit Papers

Q-Learning Algorithms: A Comprehensive Classification and... 2019 2026 2021 2023 2019 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Q-Learning Algorithms: A Comprehensive Classification and Applications
    2019 358 citations Beakcheol Jang, Myeonghwi Kim et al. IEEE Access profile →
  2. Bi-LSTM Model to Increase Accuracy in Text Classification: Combining Word2vec CNN and Attention Mechanism
    2020 267 citations Beakcheol Jang, Myeonghwi Kim et al. Applied Sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Myeonghwi Kim South Korea 4 263 122 118 78 72 7 637
Gaspard Harerimana South Korea 6 341 1.3× 127 1.0× 129 1.1× 89 1.1× 78 1.1× 7 776
Zhuangdi Zhu United States 8 269 1.0× 158 1.3× 112 0.9× 62 0.8× 108 1.5× 17 647
Konstantinos Zervoudakis Greece 7 289 1.1× 160 1.3× 68 0.6× 37 0.5× 65 0.9× 15 685
Long Lin China 4 176 0.7× 254 2.1× 115 1.0× 78 1.0× 101 1.4× 9 550
Muhammad Faheem Mushtaq Pakistan 17 353 1.3× 119 1.0× 140 1.2× 149 1.9× 75 1.0× 45 774
Zhidan Liu China 14 178 0.7× 119 1.0× 107 0.9× 57 0.7× 75 1.0× 38 573
Mingliang Hou China 14 196 0.7× 103 0.8× 149 1.3× 71 0.9× 83 1.2× 47 606
Martijn van Otterlo Netherlands 11 499 1.9× 93 0.8× 118 1.0× 64 0.8× 137 1.9× 34 899
Swarna Priya Ramu India 6 205 0.8× 123 1.0× 176 1.5× 115 1.5× 45 0.6× 12 590
Yue Tan China 8 439 1.7× 171 1.4× 187 1.6× 140 1.8× 58 0.8× 19 763

Countries citing papers authored by Myeonghwi Kim

Since Specialization
Citations

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

Fields of papers citing papers by Myeonghwi Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Myeonghwi Kim

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

All Works

7 of 7 papers shown
1.
Jang, Beakcheol, Myeonghwi Kim, Inhwan Kim, & Jong Wook Kim. (2021). EagleEye: A Worldwide Disease-Related Topic Extraction System Using a Deep Learning Based Ranking Algorithm and Internet-Sourced Data. Sensors. 21(14). 4665–4665. 4 indexed citations
2.
Jang, Beakcheol, et al.. (2020). Bi-LSTM Model to Increase Accuracy in Text Classification: Combining Word2vec CNN and Attention Mechanism. Applied Sciences. 10(17). 5841–5841. 267 indexed citations breakdown →
3.
Kim, Myeonghwi & Beakcheol Jang. (2020). PERFORMANCE EVALUATION OF DEEP LEARNING MODELS. JP Journal of Heat and Mass Transfer. 83–90. 1 indexed citations
4.
Jang, Beakcheol, Myeonghwi Kim, Gaspard Harerimana, & Jong Wook Kim. (2019). Q-Learning Algorithms: A Comprehensive Classification and Applications. IEEE Access. 7. 133653–133667. 358 indexed citations breakdown →
5.
Schleich, Wolfgang P., Myeonghwi Kim, Paul Abbott, et al.. (2018). Equivalent formulations of the Riemann hypothesis based on lines of constant phase. Physica Scripta. 93(6). 65201–65201. 4 indexed citations
6.
Kim, Myeonghwi, et al.. (2018). Worldwide emerging disease-related information extraction system from news data. 331–332. 2 indexed citations
7.
Kim, Myeonghwi, J. W. Neuberger, & Wolfgang P. Schleich. (2017). A perfect memory makes the continuous Newton method look ahead. Physica Scripta. 92(8). 85201–85201. 1 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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