Liang Gou

2.1k total citations · 1 hit paper
43 papers, 1.2k citations indexed

About

Liang Gou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Liang Gou has authored 43 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 22 papers in Computer Vision and Pattern Recognition and 13 papers in Statistical and Nonlinear Physics. Recurrent topics in Liang Gou's work include Complex Network Analysis Techniques (13 papers), Data Visualization and Analytics (10 papers) and Advanced Neural Network Applications (7 papers). Liang Gou is often cited by papers focused on Complex Network Analysis Techniques (13 papers), Data Visualization and Analytics (10 papers) and Advanced Neural Network Applications (7 papers). Liang Gou collaborates with scholars based in United States, Germany and India. Liang Gou's co-authors include Xiaolong Zhang, Yanhong Wu, Aravind Sankar, Wei Zhang, Hao Yang, Han‐Wei Shen, Junpeng Wang, Hung‐Hsuan Chen, C. Lee Giles and Michelle X. Zhou and has published in prestigious journals such as International Journal of Computer Vision, IEEE Transactions on Visualization and Computer Graphics and IEEE Computer Graphics and Applications.

In The Last Decade

Liang Gou

40 papers receiving 1.2k citations

Hit Papers

DySAT 2020 2026 2022 2024 2020 100 200 300
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.

  1. DySAT
    2020 305 citations Aravind Sankar, Yanhong Wu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liang Gou United States 18 709 435 294 242 115 43 1.2k
Eunyee Koh United States 19 762 1.1× 396 0.9× 363 1.2× 233 1.0× 77 0.7× 76 1.2k
Sungchul Kim United States 19 943 1.3× 304 0.7× 360 1.2× 237 1.0× 83 0.7× 93 1.4k
Erheng Zhong Hong Kong 18 587 0.8× 293 0.7× 137 0.5× 372 1.5× 71 0.6× 28 1.1k
Yukio Ohsawa Japan 16 851 1.2× 293 0.7× 183 0.6× 255 1.1× 94 0.8× 179 1.2k
Kan Li China 19 429 0.6× 197 0.5× 242 0.8× 270 1.1× 119 1.0× 99 984
Wenwen Dou United States 20 470 0.7× 801 1.8× 183 0.6× 127 0.5× 160 1.4× 70 1.4k
Bert Huang United States 18 766 1.1× 228 0.5× 140 0.5× 176 0.7× 75 0.7× 50 1.3k
Gita Sukthankar United States 18 602 0.8× 264 0.6× 136 0.5× 114 0.5× 80 0.7× 113 1.1k
Richong Zhang China 22 1.2k 1.7× 236 0.5× 139 0.5× 434 1.8× 118 1.0× 118 1.7k
Carl Yang United States 21 1.1k 1.5× 240 0.6× 260 0.9× 435 1.8× 52 0.5× 130 1.6k

Countries citing papers authored by Liang Gou

Since Specialization
Citations

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

Fields of papers citing papers by Liang Gou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Gou

This figure shows the co-authorship network connecting the top 25 collaborators of Liang Gou. A scholar is included among the top collaborators of Liang Gou 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 Liang Gou. Liang Gou 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.
Gou, Liang, et al.. (2025). AttributionScanner: A Visual Analytics System for Model Validation With Metadata-Free Slice Finding. IEEE Transactions on Visualization and Computer Graphics. 31(10). 7436–7447. 1 indexed citations
2.
Wang, Xiaoqi, et al.. (2025). VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels. IEEE Transactions on Visualization and Computer Graphics. 31(10). 6991–7003. 3 indexed citations
3.
Zhang, Xiaoyu, et al.. (2024). Slicing, Chatting, and Refining: A Concept-Based Approach for Machine Learning Model Validation with ConceptSlicer. Repository for Publications and Research Data (ETH Zurich). 274–287. 1 indexed citations
4.
Li, Xin, et al.. (2024). USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation. 4187–4196. 4 indexed citations
5.
Doan, Thang, et al.. (2024). Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 1555–1563. 4 indexed citations
6.
Gou, Liang, et al.. (2023). CLIP-S4: Language-Guided Self-Supervised Semantic Segmentation. 11207–11216. 25 indexed citations
7.
Gou, Liang, Shaohua Zhang, Yuanyuan Yue, et al.. (2022). Direct shear-wave seismic survey in Sanhu area, Qaidam Basin, west China. The Leading Edge. 41(1). 47–53. 4 indexed citations
8.
Gou, Liang, et al.. (2022). Self-supervised Semantic Segmentation Grounded in Visual Concepts. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 949–955. 5 indexed citations
9.
Gou, Liang, et al.. (2021). Where Can We Help? A Visual Analytics Approach to Diagnosing and Improving Semantic Segmentation of Movable Objects. IEEE Transactions on Visualization and Computer Graphics. 28(1). 1040–1050. 33 indexed citations
10.
Gou, Liang, et al.. (2021). Label-Free Robustness Estimation of Object Detection CNNs for Autonomous Driving Applications. International Journal of Computer Vision. 129(4). 1185–1201. 14 indexed citations
11.
Sankar, Aravind, Yanhong Wu, Liang Gou, Wei Zhang, & Hao Yang. (2020). DySAT Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks. 519–527. 26 indexed citations
12.
Sankar, Aravind, Yanhong Wu, Liang Gou, Wei Zhang, & Hao Yang. (2020). DySAT. 519–527. 305 indexed citations breakdown →
13.
Wang, Junpeng, et al.. (2019). DeepVID: Deep Visual Interpretation and Diagnosis for Image Classifiers via Knowledge Distillation. IEEE Transactions on Visualization and Computer Graphics. 25(6). 2168–2180. 83 indexed citations
14.
Wang, Junpeng, Liang Gou, Han‐Wei Shen, & Hao Yang. (2018). DQNViz: A Visual Analytics Approach to Understand Deep Q-Networks. IEEE Transactions on Visualization and Computer Graphics. 25(1). 288–298. 102 indexed citations
15.
Wang, Junpeng, Liang Gou, Hao Yang, & Han‐Wei Shen. (2018). <italic>GANViz</italic>: A Visual Analytics Approach to Understand the Adversarial Game. IEEE Transactions on Visualization and Computer Graphics. 24(6). 1905–1917. 61 indexed citations
16.
Zhao, Jian, Liang Gou, Fei Wang, & Michelle X. Zhou. (2014). PEARL: An interactive visual analytic tool for understanding personal emotion style derived from social media. 203–212. 47 indexed citations
17.
Gou, Liang, Michelle X. Zhou, & Huahai Yang. (2014). KnowMe and ShareMe. 955–964. 78 indexed citations
18.
19.
Gou, Liang & Xiaolong Zhang. (2011). TreeNetViz: Revealing Patterns of Networks over Tree Structures. IEEE Transactions on Visualization and Computer Graphics. 17(12). 2449–2458. 21 indexed citations
20.
Gou, Liang, Hung‐Hsuan Chen, Jung-Hyun Kim, Xiaolong Zhang, & C. Lee Giles. (2010). SNDocRank. 367–376. 14 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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