Sungjun Cho

925 total citations
32 papers, 694 citations indexed

About

Sungjun Cho is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Artificial Intelligence. According to data from OpenAlex, Sungjun Cho has authored 32 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 9 papers in Materials Chemistry and 8 papers in Artificial Intelligence. Recurrent topics in Sungjun Cho's work include Perovskite Materials and Applications (5 papers), Chalcogenide Semiconductor Thin Films (4 papers) and Advanced Neural Network Applications (4 papers). Sungjun Cho is often cited by papers focused on Perovskite Materials and Applications (5 papers), Chalcogenide Semiconductor Thin Films (4 papers) and Advanced Neural Network Applications (4 papers). Sungjun Cho collaborates with scholars based in South Korea, United States and Belgium. Sungjun Cho's co-authors include Wooyoung Shim, Gun Young Jung, Gwangmook Kim, Hyeonghun Kim, Woochul Kim, Jiyoon Park, Youngjae Kim, Youngsok Kim, Taeyoon Lee and Dae‐Eun Kim and has published in prestigious journals such as Advanced Materials, Nature Communications and Nature Nanotechnology.

In The Last Decade

Sungjun Cho

29 papers receiving 680 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sungjun Cho South Korea 14 338 312 173 151 123 32 694
Chenghao Deng China 19 323 1.0× 518 1.7× 270 1.6× 225 1.5× 81 0.7× 50 940
Yu Xiao China 13 402 1.2× 466 1.5× 124 0.7× 135 0.9× 114 0.9× 49 765
Qiang Zou China 14 229 0.7× 569 1.8× 84 0.5× 167 1.1× 227 1.8× 46 728
Yunqi Cao United States 15 376 1.1× 366 1.2× 124 0.7× 199 1.3× 82 0.7× 61 748
Daisuke Yamamoto Japan 10 388 1.1× 752 2.4× 134 0.8× 200 1.3× 190 1.5× 19 927
Natasha A. D. Yamamoto Brazil 15 607 1.8× 752 2.4× 100 0.6× 331 2.2× 250 2.0× 25 1.3k
Taemin Lee South Korea 11 274 0.8× 644 2.1× 55 0.3× 245 1.6× 286 2.3× 35 831
Satoko Honda Japan 14 286 0.8× 642 2.1× 62 0.4× 164 1.1× 194 1.6× 21 776
Qingying Ren China 11 351 1.0× 170 0.5× 107 0.6× 68 0.5× 37 0.3× 55 594

Countries citing papers authored by Sungjun Cho

Since Specialization
Citations

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

Fields of papers citing papers by Sungjun Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungjun Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Sungjun Cho. A scholar is included among the top collaborators of Sungjun 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 Sungjun Cho. Sungjun 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.
Kim, Byeongsu, Sang Yeon Lee, Hyunseok Ko, et al.. (2024). Ultrahigh-gain colloidal quantum dot infrared avalanche photodetectors. Nature Nanotechnology. 20(2). 237–245. 15 indexed citations
2.
3.
Cha, Sungmin, et al.. (2024). Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11186–11194. 10 indexed citations
4.
Cho, Sungjun, et al.. (2024). Learning Equi-Angular Representations for Online Continual Learning. 23933–23942. 3 indexed citations
5.
Cho, Sungjun, et al.. (2023). Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8334–8342. 5 indexed citations
6.
Kim, Byeongsu, Changjo Kim, Minho Lee, et al.. (2023). Unlocking the Potential of Colloidal Quantum Dot/Organic Hybrid Solar Cells: Band Tunable Interfacial Layer Approach. ACS Applied Materials & Interfaces. 15(33). 39408–39416. 4 indexed citations
7.
Cui, Jiaming, et al.. (2023). Using spectral characterization to identify healthcare-associated infection (HAI) patients for clinical contact precaution. Scientific Reports. 13(1). 16197–16197. 2 indexed citations
8.
Cha, Sungmin, et al.. (2023). Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. 20127–20136. 12 indexed citations
9.
Kim, Jun Hwan, et al.. (2023). Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2308–2317. 4 indexed citations
10.
Cho, Sungjun, et al.. (2021). Omni-directional wind-driven triboelectric nanogenerator with cross-shaped dielectric film. Nano Convergence. 8(1). 25–25. 21 indexed citations
11.
Sim, Sangwan, Doeon Lee, Jekwan Lee, et al.. (2020). Role of weak interlayer coupling in ultrafast exciton-exciton annihilation in two-dimensional rhenium dichalcogenides. Physical review. B.. 101(17). 26 indexed citations
12.
Cho, Sungjun, et al.. (2020). Real-Time Object Detection System with Multi-Path Neural Networks. 174–187. 43 indexed citations
13.
Cho, Sungjun, et al.. (2020). Triboelectric nanogenerator based on intercalated Al layer within fluttering dielectric film. Nano Energy. 77. 105184–105184. 16 indexed citations
14.
Cho, Sungjun, Wonsang Jung, Gun Young Jung, & KwangSup Eom. (2020). High-performance boron-doped silicon micron-rod anode fabricated using a mass-producible lithography method for a lithium ion battery. Journal of Power Sources. 454. 227931–227931. 35 indexed citations
15.
Sim, Sangwan, Doeon Lee, Tae‐Young Kim, et al.. (2018). Ultrafast quantum beats of anisotropic excitons in atomically thin ReS2. Nature Communications. 9(1). 351–351. 54 indexed citations
16.
Lee, Jaehong, Gwangmook Kim, Youngjae Kim, et al.. (2017). Paper Electronics: Rough‐Surface‐Enabled Capacitive Pressure Sensors with 3D Touch Capability (Small 43/2017). Small. 13(43). 1 indexed citations
17.
Lee, Doeon, Sangwan Sim, Sungjun Cho, Wooyoung Shim, & Hyunyong Choi. (2017). Ultrafast anisotropic dynamics of non-degenerated excitons in atomically-thin ReS2. Conference on Lasers and Electro-Optics. 86. FTh1F.3–FTh1F.3. 1 indexed citations
18.
Kumaresan, Yogeenth, Hyeonghun Kim, Yusin Pak, et al.. (2017). Ultra-High Sensitivity to Low Hydrogen Gas Concentration With Pd-Decorated IGZO Film. IEEE Electron Device Letters. 38(12). 1735–1738. 16 indexed citations
19.
Cho, Sungjun, Gwangmook Kim, Sooun Lee, Jin‐Woo Park, & Wooyoung Shim. (2017). Molecular‐Printed Thermochromic with Fast Color Switching. Advanced Optical Materials. 5(23). 30 indexed citations
20.
Lee, Hyunsoo, Sungjun Cho, Moonseo Park, Sungjoo Hwang, & Hyunsoo Kim. (2012). A Study of the Work Efficiency in the High Altitude according to Climatic Elements. Korean Journal of Construction Engineering and Management. 13(3). 67–77. 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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