Younggy Kim

3.5k total citations · 1 hit paper
64 papers, 2.8k citations indexed

About

Younggy Kim is a scholar working on Environmental Engineering, Biomedical Engineering and Water Science and Technology. According to data from OpenAlex, Younggy Kim has authored 64 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Environmental Engineering, 26 papers in Biomedical Engineering and 25 papers in Water Science and Technology. Recurrent topics in Younggy Kim's work include Microbial Fuel Cells and Bioremediation (33 papers), Membrane-based Ion Separation Techniques (25 papers) and Membrane Separation Technologies (21 papers). Younggy Kim is often cited by papers focused on Microbial Fuel Cells and Bioremediation (33 papers), Membrane-based Ion Separation Techniques (25 papers) and Membrane Separation Technologies (21 papers). Younggy Kim collaborates with scholars based in Canada, United States and Egypt. Younggy Kim's co-authors include Bruce E. Logan, Desmond F. Lawler, W. Shane Walker, Roland D. Cusick, Marta C. Hatzell, Pay Drechsel, Amit Pramanik, Blanca Jiménez, Manzoor Qadir and Hui Guo and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Younggy Kim

62 papers receiving 2.8k citations

Hit Papers

Global and regional potential of wastewater as a water, n... 2020 2026 2022 2024 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. Global and regional potential of wastewater as a water, nutrient and energy source
    2020 345 citations Younggy Kim et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Younggy Kim Canada 28 1.5k 1.3k 1.2k 1.0k 503 64 2.8k
Roland D. Cusick United States 28 1.4k 0.9× 1.1k 0.8× 920 0.8× 1.2k 1.1× 571 1.1× 66 3.1k
Philipp Kuntke Netherlands 27 1.2k 0.8× 1.0k 0.8× 720 0.6× 545 0.5× 273 0.5× 49 2.6k
Haoran Li China 28 1.7k 1.1× 1.0k 0.8× 762 0.7× 1.5k 1.5× 892 1.8× 124 3.5k
Lean Zhou China 32 1.2k 0.8× 440 0.3× 749 0.6× 939 0.9× 263 0.5× 80 2.6k
Guangli Liu China 40 2.8k 1.9× 1.2k 0.9× 1.0k 0.9× 1.8k 1.8× 910 1.8× 151 4.7k
Xiaoxin Cao China 22 1.9k 1.3× 895 0.7× 841 0.7× 1.2k 1.2× 635 1.3× 40 2.5k
Jia Yan China 32 589 0.4× 456 0.3× 819 0.7× 590 0.6× 233 0.5× 114 2.9k
Pablo Ledezma Australia 22 1.1k 0.7× 467 0.4× 271 0.2× 564 0.5× 399 0.8× 50 1.6k
Ka Yu Cheng Australia 32 916 0.6× 776 0.6× 405 0.4× 681 0.7× 256 0.5× 92 2.5k

Countries citing papers authored by Younggy Kim

Since Specialization
Citations

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

Fields of papers citing papers by Younggy Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Younggy Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Younggy Kim. A scholar is included among the top collaborators of Younggy 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 Younggy Kim. Younggy Kim 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
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Guo, Hui, et al.. (2025). Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning. Journal of Environmental Management. 379. 124803–124803. 4 indexed citations
3.
Kim, Younggy, et al.. (2024). Carbon preference by Cupriavidus necator for growth and accumulation phases: Heterotrophic vs. autotrophic metabolisms. Journal of Power Sources. 626. 235797–235797. 2 indexed citations
4.
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Hong, Tianqi, Mao Peng, Younggy Kim, Herb E. Schellhorn, & Qiyin Fang. (2024). Automated cell profiling in imaging flow cytometry with annotation-efficient learning. Optics & Laser Technology. 181. 111992–111992.
6.
Pavlović, Vladimir B., et al.. (2024). Enhancing ammonia recovery through pH polarization in bipolar membrane electrodialysis. Environmental Science Advances. 3(9). 1309–1316. 2 indexed citations
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Yu, Jaecheul, et al.. (2022). Model study on real-time aeration based on nitrite for effective operation of single-stage anammox. Environmental Research. 212(Pt E). 113554–113554. 10 indexed citations
9.
Guo, Hui & Younggy Kim. (2021). Membrane Scaling in Electrodialysis Fed with High-Strength Wastewater. Environmental Engineering Science. 38(9). 832–840. 11 indexed citations
10.
Kim, Younggy, et al.. (2021). Isolation of Pb(II)-reducing bacteria and demonstration of biological Pb(II) reduction to metallic Pb. Journal of Hazardous Materials. 423(Pt A). 126975–126975. 10 indexed citations
11.
Goel, Rajeev, et al.. (2021). Modeling the anaerobic digestion of wastewater sludge under sulfate‐rich conditions. Water Environment Research. 93(10). 2084–2096. 5 indexed citations
12.
Guo, Hui & Younggy Kim. (2019). Stacked multi-electrode design of microbial electrolysis cells for rapid and low-sludge treatment of municipal wastewater. Biotechnology for Biofuels. 12(1). 23–23. 23 indexed citations
13.
Kim, Younggy, et al.. (2017). Increasing phosphorus recovery from dewatering centrate in microbial electrolysis cells. Biotechnology for Biofuels. 10(1). 70–70. 29 indexed citations
14.
Huang, Wendy & Younggy Kim. (2016). Electrochemical techniques for evaluating short-chain fatty acid utilization by bioanodes. Environmental Science and Pollution Research. 24(3). 2620–2626. 8 indexed citations
15.
Kim, Younggy, et al.. (2016). Cadmium (II) removal mechanisms in microbial electrolysis cells. Journal of Hazardous Materials. 311. 134–141. 83 indexed citations
16.
Kim, Younggy, et al.. (2016). The yield and decay coefficients of exoelectrogenic bacteria in bioelectrochemical systems. Water Research. 94. 233–239. 44 indexed citations
17.
Kim, Younggy, et al.. (2014). Energy efficient reconcentration of diluted human urine using ion exchange membranes in bioelectrochemical systems. Water Research. 64. 61–72. 72 indexed citations
18.
Kim, Younggy, W. Shane Walker, & Desmond F. Lawler. (2012). Competitive separation of di- vs. mono-valent cations in electrodialysis: Effects of the boundary layer properties. Water Research. 46(7). 2042–2056. 97 indexed citations
19.
Kim, Younggy & Bruce E. Logan. (2012). Microbial desalination cells for energy production and desalination. Desalination. 308. 122–130. 223 indexed citations
20.
Kim, Younggy & Bruce E. Logan. (2011). Series Assembly of Microbial Desalination Cells Containing Stacked Electrodialysis Cells for Partial or Complete Seawater Desalination. Environmental Science & Technology. 45(13). 5840–5845. 154 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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