Soojin Cho

4.2k total citations · 2 hit papers
103 papers, 3.2k citations indexed

About

Soojin Cho is a scholar working on Civil and Structural Engineering, Discrete Mathematics and Combinatorics and Electrical and Electronic Engineering. According to data from OpenAlex, Soojin Cho has authored 103 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Civil and Structural Engineering, 19 papers in Discrete Mathematics and Combinatorics and 15 papers in Electrical and Electronic Engineering. Recurrent topics in Soojin Cho's work include Structural Health Monitoring Techniques (41 papers), Infrastructure Maintenance and Monitoring (28 papers) and Advanced Combinatorial Mathematics (17 papers). Soojin Cho is often cited by papers focused on Structural Health Monitoring Techniques (41 papers), Infrastructure Maintenance and Monitoring (28 papers) and Advanced Combinatorial Mathematics (17 papers). Soojin Cho collaborates with scholars based in South Korea, United States and Japan. Soojin Cho's co-authors include Byunghyun Kim, Sung‐Han Sim, Chung‐Bang Yun, Billie F. Spencer, Hyung‐Jo Jung, Hyunjun Kim, Junhwa Lee, Hongki Jo, B. F. Spencer and Eunjong Ahn and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cement and Concrete Research and Expert Systems with Applications.

In The Last Decade

Soojin Cho

92 papers receiving 3.1k citations

Hit Papers

align trajectories

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.

Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

2018 244 citations Byunghyun Kim, Soojin Cho Sensors profile →
Image‐based concrete crack assessment using mask and region‐based convolutional neural network

2019 230 citations Byunghyun Kim, Soojin Cho Structural Control and Health Monitoring profile →

Peers

Soojin Cho

CSE

ME

EEE

CN

GEOLO

Eugene J. OBrien Ireland

Alfonso García-Cerezo Spain

Juan P. Amézquita-Sánchez Mexico

Miha Boltežar Slovenia

Ye Xia China

Maria Q. Feng United States

Tiziana D’Orazio Italy

Martin Valtierra‐Rodriguez Mexico

Jaime Valls Miró Australia

Neal Wadhwa United States

Eugene J. OBrien Ireland

Soojin Cho

6.4k ×2.6

CSE

3.5k ×6.6

ME

404 ×1.0

EEE

80 ×0.2

CN

94 ×0.3

GEOLO

Citations per year, relative to Soojin Cho Soojin Cho (= 1×) peers Eugene J. OBrien

Countries citing papers authored by Soojin Cho

Since Specialization

Citations

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

Fields of papers citing papers by Soojin Cho

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soojin Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Soojin Cho. A scholar is included among the top collaborators of Soojin 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 Soojin Cho. Soojin Cho 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

1.

Lee, Gyumin, et al.. (2025). Zero-shot framework for automated inspection of bridge expansion joints using road scan images. Automation in Construction. 179. 106444–106444.

2.

Bae, Sung‐Ho, et al.. (2025). Training Deep Learning Segmentation Models Using Super-Resolution Crack Images for Detection of Thin Concrete Cracks. Journal of Computing in Civil Engineering. 39(4). 2 indexed citations

3.

Sim, Sung‐Han, et al.. (2024). Long-term displacement measurement system for bridge bearing capable of camera reposition. Measurement. 235. 114921–114921. 4 indexed citations

4.

Cho, Soojin, et al.. (2023). Bases of the equivariant cohomologies of regular semisimple Hessenberg varieties. Advances in Mathematics. 423. 109018–109018.

5.

Kim, Byunghyun, et al.. (2022). Comparative Study of Lightweight Deep Semantic Segmentation Models for Concrete Damage Detection. Applied Sciences. 12(24). 12786–12786. 8 indexed citations

6.

Kim, Byunghyun & Soojin Cho. (2020). Automated Multiple Concrete Damage Detection Using Instance Segmentation Deep Learning Model. Applied Sciences. 10(22). 8008–8008. 66 indexed citations

7.

Kim, Byunghyun & Soojin Cho. (2019). Hyperspectral Super-Resolution Technique Using Histogram Matching and Endmember Optimization. Applied Sciences. 9(20). 4444–4444. 1 indexed citations

8.

Kim, Byunghyun & Soojin Cho. (2019). Image‐based concrete crack assessment using mask and region‐based convolutional neural network. Structural Control and Health Monitoring. e2381–e2381. 230 indexed citations breakdown →

9.

Cho, Soojin, et al.. (2019). A Comparative Study on Performance of Deep Learning Models for Vision-based Concrete Crack Detection according to Model Types. Journal of the Korean Society of Safety. 34(6). 50–57. 1 indexed citations

10.

Cho, Soojin, Suyoung Choi, & Shizuo Kaji. (2019). GEOMETRIC REPRESENTATIONS OF FINITE GROUPS ON REAL TORIC SPACES. Journal of the Korean Mathematical Society. 56(5). 1265–1283.

11.

Kim, Byunghyun & Soojin Cho. (2018). Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique. Sensors. 18(10). 3452–3452. 244 indexed citations breakdown →

12.

Cho, Soojin, Junhwa Lee, & Sung‐Han Sim. (2018). Comparative study on displacement measurement sensors for high-speed railroad bridge. Smart Structures and Systems. 21(5). 637–652. 8 indexed citations

13.

Cho, Soojin, et al.. (2016). Reference-Free Displacement Estimation of Bridges Using Kalman Filter-Based Multimetric Data Fusion. Journal of Sensors. 2016. 1–9. 34 indexed citations

14.

Cho, Soojin, Sung‐Han Sim, Jong‐Woong Park, & Junhwa Lee. (2014). Extension of indirect displacement estimation method using acceleration and strain to various types of beam structures. Smart Structures and Systems. 14(4). 699–718. 13 indexed citations

15.

Cho, Soojin. (2012). A new Littlewood-Richardson rule for Schur 𝑃-functions. Transactions of the American Mathematical Society. 365(2). 939–972. 6 indexed citations

16.

Cho, Soojin, et al.. (2010). Reduction formulae of Littlewood–Richardson coefficients. Advances in Applied Mathematics. 46(1-4). 125–143. 2 indexed citations

17.

Booth, James R., Soojin Cho, Douglas D. Burman, & Tali Bitan. (2007). Neural correlates of mapping from phonology to orthography in children performing an auditory spelling task. Developmental Science. 10(4). 441–451. 59 indexed citations

18.

Cho, Soojin, et al.. (2007). A combinatorial proof of the reduction formula for Littlewood–Richardson coefficients. Journal of Combinatorial Theory Series A. 114(7). 1199–1219. 6 indexed citations

19.

Cho, Soojin. (2004). Major Index for Standard Young Tableaux.. Ars Combinatoria. 71.

20.

Cho, Soojin. (1998). Minimal null designs of subspace lattice over finite fields. Linear Algebra and its Applications. 282(1-3). 199–220. 5 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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