Jeong‐Hyeon Cho

1.0k total citations · 1 hit paper
30 papers, 675 citations indexed

About

Jeong‐Hyeon Cho is a scholar working on Aquatic Science, Electrical and Electronic Engineering and Immunology. According to data from OpenAlex, Jeong‐Hyeon Cho has authored 30 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Aquatic Science, 11 papers in Electrical and Electronic Engineering and 6 papers in Immunology. Recurrent topics in Jeong‐Hyeon Cho's work include Aquaculture Nutrition and Growth (12 papers), Aquaculture disease management and microbiota (6 papers) and Reproductive biology and impacts on aquatic species (5 papers). Jeong‐Hyeon Cho is often cited by papers focused on Aquaculture Nutrition and Growth (12 papers), Aquaculture disease management and microbiota (6 papers) and Reproductive biology and impacts on aquatic species (5 papers). Jeong‐Hyeon Cho collaborates with scholars based in South Korea, United States and Japan. Jeong‐Hyeon Cho's co-authors include Joungho Kim, Eakhwan Song, Joohee Kim, Jonghyun Cho, Heegon Kim, Seung-Taek Yang, Junho Lee, Kwang-Yoo Byun, Min-Suk Suh and Kunwoo Park and has published in prestigious journals such as Aquaculture, IEEE Microwave and Wireless Components Letters and Frontiers in Marine Science.

In The Last Decade

Jeong‐Hyeon Cho

24 papers receiving 652 citations

Hit Papers

High-Frequency Scalable Electrical Model and Analysis of ... 2011 2026 2016 2021 2011 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. High-Frequency Scalable Electrical Model and Analysis of a Through Silicon Via (TSV)
    2011 373 citations Eakhwan Song, Jeong‐Hyeon Cho 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
Jeong‐Hyeon Cho South Korea 11 477 112 108 42 42 30 675
Qichang Chen China 13 164 0.3× 52 0.5× 16 0.1× 22 0.5× 6 0.1× 34 461
Michele Petracca United States 15 506 1.1× 282 2.5× 212 2.0× 26 0.6× 32 699
Eren Kursun United States 16 458 1.0× 163 1.5× 274 2.5× 13 0.3× 39 592
Eric Karl United States 19 843 1.8× 130 1.2× 287 2.7× 8 0.2× 41 935
An V. Tran Australia 15 670 1.4× 19 0.2× 9 0.1× 13 0.3× 128 3.0× 110 785
Krishnamachar Prasad New Zealand 10 186 0.4× 74 0.7× 26 0.2× 28 0.7× 38 370
Mohit Gupta Belgium 14 559 1.2× 39 0.3× 85 0.8× 121 2.9× 45 645
Yuyang Wang China 11 244 0.5× 46 0.4× 11 0.1× 46 1.1× 72 368
Po-Chun Chang Taiwan 12 206 0.4× 167 1.5× 79 0.7× 25 0.6× 23 470
Kaushik Mazumdar India 9 205 0.4× 72 0.6× 27 0.3× 22 0.5× 42 279

Countries citing papers authored by Jeong‐Hyeon Cho

Since Specialization
Citations

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

Fields of papers citing papers by Jeong‐Hyeon Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeong‐Hyeon Cho. 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 Jeong‐Hyeon Cho. The network helps show where Jeong‐Hyeon Cho may publish in the future.

Co-authorship network of co-authors of Jeong‐Hyeon Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Jeong‐Hyeon Cho. A scholar is included among the top collaborators of Jeong‐Hyeon Cho 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 Jeong‐Hyeon Cho. Jeong‐Hyeon Cho 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.
Xiong, Wenjie, Liu Ke, Yeongon Cho, et al.. (2025). Accelerating Confidential Recommendation Model Inference With Near-Memory Processing. IEEE Transactions on Dependable and Secure Computing. 22(4). 3580–3586.
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Park, Sangsoo, Jin Chul Jung, Jong-Geon Lee, et al.. (2024). An LPDDR-based CXL-PNM Platform for TCO-efficient Inference of Transformer-based Large Language Models. 970–982. 17 indexed citations
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Park, Jin‐Woo, et al.. (2023). The reproductive potential of Pacific bluefin tuna (Thunnus orientalis) farmed in sea cages in South Korea. Journal of the World Aquaculture Society. 54(6). 1497–1512. 1 indexed citations
7.
Cho, Jeong‐Hyeon, Jin Woo Park, Yong‐Woon Ryu, Kang‐Woong Kim, & Sang‐Woo Hur. (2023). Morphology, Histology, and Histochemistry of the Digestive Tract of the Marbled Flounder Pseudopleuronectes yokohamae. Animals. 13(5). 936–936. 13 indexed citations
8.
Kim, Hyun Seok, et al.. (2023). SMT: Software-Defined Memory Tiering for Heterogeneous Computing Systems With CXL Memory Expander. IEEE Micro. 43(2). 20–29. 16 indexed citations
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Cho, Jeong‐Hyeon, Jin Woo Park, Bong‐Joo Lee, Kang‐Woong Kim, & Sang‐Woo Hur. (2022). Low extrusion pressure and small feed particle size improve the growth performance and digestive physiology of rockfish (Sebastes schlegeli). Aquaculture. 566. 739199–739199. 3 indexed citations
11.
Lee, Donghun, et al.. (2022). Improving In-Memory Database Operations with Acceleration DIMM (AxDIMM). 1–9. 18 indexed citations
12.
Kim, Kyung‐Sun, et al.. (2022). A Novel Simulation Methodology Reflecting System Power Scenario using a Markov-Chain-based Stochastic Random Power Model. 2022 IEEE 72nd Electronic Components and Technology Conference (ECTC). 929–936. 1 indexed citations
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Ke, Liu, Xuan Zhang, Jong-Geon Lee, et al.. (2021). Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM. IEEE Micro. 42(1). 116–127. 79 indexed citations
15.
Kang, Shin-haeng, Sukhan Lee, Hyeonsu Kim, et al.. (2021). Aquabolt-XL: Samsung HBM2-PIM with in-memory processing for ML accelerators and beyond. 1–26. 33 indexed citations
16.
Cho, Jeong‐Hyeon, Seunghyung Lee, Bong‐Joo Lee, et al.. (2021). A preliminary study of dietary protein requirement of juvenile marbled flounder (Pseudopleuronectes yokohamae). Animal nutrition. 7(2). 548–555. 6 indexed citations
17.
Cho, Jeong‐Hyeon, Bong‐Joo Lee, Sang‐Woo Hur, et al.. (2019). Effects of Extrusion Pressure and Feed Ingredient Particle Size on Growth Performance in Olive Flounder Paralichthys olivaceus. Korean Journal of Fisheries and Aquatic Sciences. 52(3). 247–255. 3 indexed citations
18.
Cho, Jeong‐Hyeon, et al.. (2017). The Impact of Patient Education with a Smartphone Application on the Quality of Bowel Preparation for Screening Colonoscopy. Clinical Endoscopy. 50(5). 479–485. 29 indexed citations
19.
Cho, Jeong‐Hyeon, et al.. (2009). A Precise Analytical Estimation Method of Data-dependent Jitter for High Speed Serial Links with the Consideration of Finite Slew Rate of Input Signal. 215–218. 2 indexed citations
20.
Song, Eakhwan, Jeong‐Hyeon Cho, Woojin Lee, Minchul Shin, & Joungho Kim. (2008). A Wide-Band Passive Equalizer Design on PCB Based on Near-End Crosstalk and Reflections for 12.5 Gbps Serial Data Transmission. IEEE Microwave and Wireless Components Letters. 18(12). 794–796. 13 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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