Dae Sin Kim

1.0k total citations
80 papers, 674 citations indexed

About

Dae Sin Kim is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Dae Sin Kim has authored 80 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Electrical and Electronic Engineering, 17 papers in Materials Chemistry and 16 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Dae Sin Kim's work include Semiconductor materials and devices (32 papers), Advancements in Semiconductor Devices and Circuit Design (23 papers) and Integrated Circuits and Semiconductor Failure Analysis (11 papers). Dae Sin Kim is often cited by papers focused on Semiconductor materials and devices (32 papers), Advancements in Semiconductor Devices and Circuit Design (23 papers) and Integrated Circuits and Semiconductor Failure Analysis (11 papers). Dae Sin Kim collaborates with scholars based in South Korea, United States and France. Dae Sin Kim's co-authors include D. S. Citrin, Changwook Jeong, Inkook Jang, Won‐Joon Son, Mun‐Bo Shim, Inkoo Kim, Hyeonho Choi, Soon Ok Jeon, Young-Gu Kim and Jisu Ryu and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Applied Physics Letters.

In The Last Decade

Dae Sin Kim

64 papers receiving 655 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dae Sin Kim South Korea	13	528	211	126	53	51	80	674
Zhiguo Qian United States	14	808 1.5×	92 0.4×	369 2.9×	81 1.5×	19 0.4×	45	1.0k
Jianfeng Zhai China	16	949 1.8×	90 0.4×	83 0.7×	80 1.5×	7 0.1×	75	1.3k
Chunrong Peng China	17	579 1.1×	87 0.4×	236 1.9×	13 0.2×	90 1.8×	76	779
Toshiyuki Shibuya Japan	9	284 0.5×	137 0.6×	71 0.6×	45 0.8×	9 0.2×	26	606
Shinnosuke Hattori Japan	12	267 0.5×	89 0.4×	131 1.0×	18 0.3×	43 0.8×	41	468
Alexander Y. Nikiforov Russia	16	545 1.0×	99 0.5×	149 1.2×	92 1.7×	4 0.1×	90	820
R. Johanni Germany	6	135 0.3×	253 1.2×	179 1.4×	44 0.8×	3 0.1×	9	953
You Wang China	16	620 1.2×	85 0.4×	277 2.2×	151 2.8×	8 0.2×	66	856
James Sexton United States	10	68 0.1×	127 0.6×	32 0.3×	83 1.6×	9 0.2×	26	677

Countries citing papers authored by Dae Sin Kim

Since Specialization

Citations

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

Fields of papers citing papers by Dae Sin Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dae Sin Kim

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Park, Min‐Chul, Sangyeon Kim, Yeji Kim, et al.. (2025). Realistic and Scalable TCAD for Yield-Aware Full-Chip DTCO. 1–3.

Cho, Eunseog, Won‐Joon Son, Seungmin Lee, et al.. (2025). Unraveling the adhesion characteristics of ruthenium as an advanced metal interconnect material using machine learning potential. Journal of Materials Chemistry C. 13(15). 7772–7784.

Kim, Dae Sin, et al.. (2025). Deriving optimal atomic layer deposition process conditions using machine learning. Journal of Industrial Information Integration. 47. 100879–100879. 2 indexed citations

Jin, Seonghoon, Kyungmin Lee, Woosung Choi, et al.. (2024). A New Anisotropic Driving Force Model for SiC Device Simulations. IEEE Transactions on Electron Devices. 71(3). 2024–2029. 2 indexed citations

Lee, Juho, et al.. (2024). Origin of High Specific Contact Resistivity in TiN-InGaZnO Junctions. IEEE Electron Device Letters. 45(9). 1665–1668. 5 indexed citations

Nakamura, Satoshi, et al.. (2024). Hardware efficient decomposition of the Laplace operator and its application to the Helmholtz and the Poisson equation on quantum computer. Quantum Information Processing. 23(7). 2 indexed citations

Lee, Minhwan, et al.. (2024). Microscopic Structure and Dynamic Study in Amorphous InGaZnO Focusing on Oxygen-Centered Complex. The Journal of Physical Chemistry C. 128(30). 12642–12648. 2 indexed citations

Cho, Eunseog, Ara Jo, Tae‐Gon Kim, et al.. (2024). Exploring the optical characteristics influenced by size and surface defects in AgInS2 quantum dots: A theoretical study with a simple ligand model. Applied Surface Science. 686. 162142–162142. 1 indexed citations

Kim, Inkoo, Daun Jeong, Won‐Joon Son, et al.. (2023). Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs. npj Computational Materials. 9(1). 6 indexed citations

10.

Kim, Young-Gu, et al.. (2023). TCAD Device Simulation With Graph Neural Network. IEEE Electron Device Letters. 44(8). 1368–1371. 12 indexed citations

11.

Schmidt, Alexander, Hyo‐Shin Ahn, Inkook Jang, et al.. (2023). Full Chip Stress Model for Flash BEOL Crack Failure Risk Analysis. 29–32. 1 indexed citations

12.

Park, Ji Young, Hyun‐Ji Song, Won‐Joon Son, et al.. (2023). EUV-induced activation mechanism of photoacid generators: key factors affecting EUV sensitivity. 27–27. 1 indexed citations

13.

Müller, Peter C., Richard Dronskowski, Woon Ih Choi, et al.. (2023). On the atomistic origin of the polymorphism and the dielectric physical properties of beryllium oxide. Journal of Computational Chemistry. 44(10). 1052–1063. 2 indexed citations

14.

Choi, Woon Ih, et al.. (2023). Switchable Chemical‐Bond Reorganization for the Stable Charge Trapping in Amorphous Silicon Nitride. Advanced Materials. 36(9). e2308054–e2308054. 7 indexed citations

15.

Choi, Woon Ih, Aamir Shafique, Hye Jung Kim, et al.. (2023). Structural-Stability Study of AntiperovskiteNa3OClforNa-Rich Solid Electrolyte. Physical Review Applied. 19(3). 7 indexed citations

16.

Kang, Hosuk, Soo‐Ghang Ihn, Inkoo Kim, et al.. (2022). Designing Stable Deep‐Blue Thermally Activated Delayed Fluorescence Emitters through Controlling the Intrinsic Stability of Triplet Excitons (Advanced Optical Materials 12/2022). Advanced Optical Materials. 10(12).

17.

Kim, In-Soo, So Jeong Park, Mun‐Bo Shim, et al.. (2022). Simulator acceleration and inverse design of fin field-effect transistors using machine learning. Scientific Reports. 12(1). 1140–1140. 15 indexed citations

18.

Pham, Anh-Tuan, et al.. (2021). Critical Backscattering Length in Nanotransistors. IEEE Electron Device Letters. 43(2). 180–183. 4 indexed citations

19.

Sakuma, Rei, et al.. (2018). First-principles reaction-path finding in gas discharge plasmas with QCEIMS. Bulletin of the American Physical Society. 1 indexed citations

20.

Kim, Dae Sin, Young-Gu Kim, Jaeho Kim, et al.. (2012). Comprehensive modeling of NAND flash memory reliability: Endurance and data retention. MY.5.1–MY.5.4. 28 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.

Explore authors with similar magnitude of impact