Seongyoon Kim

505 total citations
21 papers, 372 citations indexed

About

Seongyoon Kim is a scholar working on Electrical and Electronic Engineering, Automotive Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Seongyoon Kim has authored 21 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 10 papers in Automotive Engineering and 4 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Seongyoon Kim's work include Advanced Battery Technologies Research (10 papers), Advancements in Battery Materials (7 papers) and Advanced Battery Materials and Technologies (3 papers). Seongyoon Kim is often cited by papers focused on Advanced Battery Technologies Research (10 papers), Advancements in Battery Materials (7 papers) and Advanced Battery Materials and Technologies (3 papers). Seongyoon Kim collaborates with scholars based in South Korea, United States and China. Seongyoon Kim's co-authors include Jung‐Il Choi, Yun Young Choi, Ki Jae Kim, Soowhan Kim, Min‐Ho Lee, Sang‐Hee Lee, Hyunsoon Cho, Seung Hwan Ko, Sukjoon Hong and Jaeho Shin and has published in prestigious journals such as ACS Nano, Journal of Power Sources and Applied Energy.

In The Last Decade

Seongyoon Kim

19 papers receiving 365 citations

Peers

Seongyoon Kim

EEE

CSE

SRRQ

Seongyun Park South Korea

Inho Cho South Korea

Yao Chang China

Zhengguo Li China

Christian Ellersdorfer Austria

Bhanu Sood United States

Sangdo Park South Korea

Suyong Chae South Korea

Maosheng Li China

Seongyun Park South Korea

Seongyoon Kim

253 ×1.0

226 ×0.9

EEE

53 ×0.8

CSE

33 ×0.6

SRRQ

11 ×0.4

Citations per year, relative to Seongyoon Kim Seongyoon Kim (= 1×) peers Seongyun Park

Countries citing papers authored by Seongyoon Kim

Since Specialization

Citations

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

Fields of papers citing papers by Seongyoon Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seongyoon Kim

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

All Works

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20 of 20 papers shown

Kim, Seongyoon & Jung‐Il Choi. (2024). Bayesian impedance deconvolution using timescale distribution for lithium-ion battery state estimation. Journal of Energy Storage. 100. 113503–113503. 1 indexed citations

Lee, Min‐Ho, et al.. (2024). Bilevel-optimized continual learning for predicting capacity degradation of lithium-ion batteries. Journal of Energy Storage. 86. 111187–111187. 4 indexed citations

Kim, Seongyoon, et al.. (2024). Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records. JCO Clinical Cancer Informatics. 8(8). e2300192–e2300192. 1 indexed citations

Kim, Seongyoon, et al.. (2024). Capacity fade-aware parameter identification of zero-dimensional model for vanadium redox flow batteries. Applied Energy. 380. 124989–124989. 1 indexed citations

Kim, Seongyoon, et al.. (2023). Bayesian parameter identification in electrochemical model for lithium-ion batteries. Journal of Energy Storage. 71. 108129–108129. 19 indexed citations

Kim, Seongyoon, et al.. (2023). Model-free reconstruction of capacity degradation trajectory of lithium-ion batteries using early cycle data. eTransportation. 17. 100243–100243. 33 indexed citations

Yang, Mingyu, et al.. (2023). Deep-learning-based reduced-order modeling to optimize recuperative burner operating conditions. Applied Thermal Engineering. 236. 121669–121669. 5 indexed citations

Kim, Seongyoon, et al.. (2023). Electrochemical Model-Based State-Space Approach for Real-Time Parameter Estimation of Lithium-Ion Batteries. ECS Meeting Abstracts. MA2023-02(65). 3052–3052.

Sun, Xiang, Seongyoon Kim, & Jung‐Il Choi. (2022). Recurrent neural network-induced Gaussian process. Neurocomputing. 509. 75–84. 3 indexed citations

10.

Kim, Seongyoon, Yun Young Choi, Ki Jae Kim, & Jung‐Il Choi. (2021). Forecasting state-of-health of lithium-ion batteries using variational long short-term memory with transfer learning. Journal of Energy Storage. 41. 102893–102893. 103 indexed citations

11.

Kim, Seongyoon, Yun Young Choi, & Jung‐Il Choi. (2021). Impedance-based capacity estimation for lithium-ion batteries using generative adversarial network. Applied Energy. 308. 118317–118317. 56 indexed citations

12.

Choi, Yun Young, et al.. (2021). Parameter identification and identifiability analysis of lithium‐ion batteries. Energy Science & Engineering. 10(2). 488–506. 10 indexed citations

13.

Shin, Jaeho, Seong‐Min Jeong, Jin‐Mo Kim, et al.. (2021). Dynamic Pore Modulation of Stretchable Electrospun Nanofiber Filter for Adaptive Machine Learned Respiratory Protection. ACS Nano. 15(10). 15730–15740. 39 indexed citations

14.

Choi, Yun Young, et al.. (2020). Multiple parameter identification using genetic algorithm in vanadium redox flow batteries. Journal of Power Sources. 450. 227684–227684. 40 indexed citations

15.

Kim, Seongyoon, Sang‐Hee Lee, Jung‐Il Choi, & Hyunsoon Cho. (2020). Binary genetic algorithm for optimal joinpoint detection: Application to cancer trend analysis. Statistics in Medicine. 40(3). 799–822. 28 indexed citations

16.

Ko, Dai Ho, et al.. (2011). Focal plane damage analysis by the space radiation environment in Aura satellite orbit. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 638(1). 183–186.

17.

Kim, Seongyoon, et al.. (2009). An SoC integrating an H.264 encoder with an ISP. 1936–1936. 5 indexed citations

18.

Kim, Seongyoon, et al.. (2008). Experience of Subjective Symptoms in Euthymic Patients with Bipolar Disorder. Journal of Korean Medical Science. 23(1). 18–18. 8 indexed citations

19.

Kim, Seongyoon, et al.. (2008). A synchronous DRAM controller for an H.264/AVC encoder. II–113. 3 indexed citations

20.

Suh, Cheolwon, et al.. (2006). Korean Translation and Validation of the Functional Assessment of Cancer Therapy-Lung (FACT-L) Version 4. Quality of Life Research. 15(1). 161–166. 12 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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