Sangwoo Mo

976 total citations
9 papers, 203 citations indexed

About

Sangwoo Mo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Sangwoo Mo has authored 9 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Sangwoo Mo's work include Electrical and Bioimpedance Tomography (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Advanced Sensor and Energy Harvesting Materials (2 papers). Sangwoo Mo is often cited by papers focused on Electrical and Bioimpedance Tomography (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Advanced Sensor and Energy Harvesting Materials (2 papers). Sangwoo Mo collaborates with scholars based in South Korea, United States and Canada. Sangwoo Mo's co-authors include Jinwoo Shin, Kyungseo Park, Hyunkyu Park, Jung Kim, Jaeho Lee, Sejun Park, Minsu Cho, Jongheon Jeong, Jihoon Tack and Hyosang Lee and has published in prestigious journals such as IEEE Transactions on Robotics, Open Access System for Information Sharing (Pohang University of Science and Technology) and arXiv (Cornell University).

In The Last Decade

Sangwoo Mo

9 papers receiving 198 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sangwoo Mo South Korea	6	76	75	53	49	36	9	203
Mehdi Ammi France	9	62 0.8×	96 1.3×	15 0.3×	36 0.7×	15 0.4×	25	272
Ruidong Zhang United States	9	86 1.1×	37 0.5×	20 0.4×	35 0.7×	39 1.1×	27	239
Manuel Eggimann Switzerland	10	50 0.7×	57 0.8×	148 2.8×	37 0.8×	22 0.6×	16	273
Thi Ngoc Tho Nguyen Singapore	8	42 0.6×	31 0.4×	27 0.5×	56 1.1×	22 0.6×	18	248
Martin Lefebvre Belgium	9	21 0.3×	44 0.6×	196 3.7×	45 0.9×	11 0.3×	26	248
David Weikersdorfer Germany	7	92 1.2×	25 0.3×	103 1.9×	16 0.3×	34 0.9×	8	235
Kyeongbo Kong South Korea	8	126 1.7×	35 0.5×	27 0.5×	57 1.2×	54 1.5×	27	252
Chiang Liang Kok Singapore	9	10 0.1×	81 1.1×	109 2.1×	43 0.9×	21 0.6×	55	242
Xianwei Jiang China	9	61 0.8×	77 1.0×	18 0.3×	63 1.3×	27 0.8×	21	282
Shuchang Xu China	7	94 1.2×	68 0.9×	13 0.2×	17 0.3×	78 2.2×	43	256

Countries citing papers authored by Sangwoo Mo

Since Specialization

Citations

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

Fields of papers citing papers by Sangwoo Mo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sangwoo Mo

This figure shows the co-authorship network connecting the top 25 collaborators of Sangwoo Mo. A scholar is included among the top collaborators of Sangwoo Mo 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 Sangwoo Mo. Sangwoo Mo 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:

9 of 9 papers shown

1.

Kim, Younghyun, Sangwoo Mo, Minkyu Kim, et al.. (2024). Discovering and Mitigating Visual Biases Through Keyword Explanation. 11082–11092. 1 indexed citations

2.

Mo, Sangwoo, et al.. (2021). MASKER: Masked Keyword Regularization for Reliable Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 35(15). 13578–13586. 16 indexed citations

3.

Park, Hyunkyu, Kyungseo Park, Sangwoo Mo, & Jung Kim. (2021). Deep Neural Network Based Electrical Impedance Tomographic Sensing Methodology for Large-Area Robotic Tactile Sensing. IEEE Transactions on Robotics. 37(5). 1570–1583. 69 indexed citations

4.

Tack, Jihoon, Sangwoo Mo, Jongheon Jeong, & Jinwoo Shin. (2020). CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances. arXiv (Cornell University). 33. 11839–11852. 19 indexed citations

5.

Lee, Jaeho, et al.. (2020). Layer-adaptive sparsity for the Magnitude-based Pruning. arXiv (Cornell University). 44 indexed citations

6.

Park, Sejun, Jaeho Lee, Sangwoo Mo, & Jinwoo Shin. (2020). Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning. arXiv (Cornell University). 5 indexed citations

7.

Mo, Sangwoo, et al.. (2019). Mining GOLD Samples for Conditional GANs. arXiv (Cornell University). 32. 6167–6178. 1 indexed citations

8.

Park, Hyunkyu, Hyosang Lee, Kyungseo Park, Sangwoo Mo, & Jung Kim. (2019). Deep Neural Network Approach in Electrical Impedance Tomography-based Real-time Soft Tactile Sensor. 7447–7452. 22 indexed citations

9.

Mo, Sangwoo, Minsu Cho, & Jinwoo Shin. (2018). InstaGAN: Instance-aware Image-to-Image Translation. Open Access System for Information Sharing (Pohang University of Science and Technology). 26 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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