Congrui Huang

22 total papers · 2.1k total citations
8 papers, 863 citations indexed

About

Congrui Huang is a scholar working on Artificial Intelligence, Signal Processing and Economics and Econometrics. According to data from OpenAlex, Congrui Huang has authored 8 papers receiving a total of 863 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Signal Processing and 2 papers in Economics and Econometrics. Recurrent topics in Congrui Huang's work include Time Series Analysis and Forecasting (4 papers), Advanced Text Analysis Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Congrui Huang is often cited by papers focused on Time Series Analysis and Forecasting (4 papers), Advanced Text Analysis Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Congrui Huang collaborates with scholars based in China, United States and United Kingdom. Congrui Huang's co-authors include Yujing Wang, Juanyong Duan, Yunhai Tong, Bixiong Xu, Tianmeng Yang, Zhihan Yue, Jie Tong, Jing Bai, Defu Cao and Qi Zhang and has published in prestigious journals such as Empirical Methods in Natural Language Processing, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Congrui Huang

7 papers receiving 833 citations

Hit Papers

Multivariate Time-Series ... 2020 2026 2022 2024 2020 2022 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Congrui Huang 585 391 232 111 71 8 863
Bixiong Xu 507 0.9× 380 1.0× 233 1.0× 111 1.0× 67 0.9× 4 742
Alexander Lavin 599 1.0× 280 0.7× 300 1.3× 110 1.0× 28 0.4× 14 1.0k
Chaoli Zhang 352 0.6× 257 0.7× 124 0.5× 95 0.9× 122 1.7× 17 849
Samaneh Aminikhanghahi 319 0.5× 209 0.5× 144 0.6× 97 0.9× 61 0.9× 14 996
Tung Kieu 414 0.7× 385 1.0× 182 0.8× 69 0.6× 106 1.5× 18 792
S. Chu 307 0.5× 427 1.1× 99 0.4× 64 0.6× 59 0.8× 7 739
Chenhao Niu 716 1.2× 450 1.2× 486 2.1× 140 1.3× 21 0.3× 7 839
Ming Jin 510 0.9× 154 0.4× 129 0.6× 66 0.6× 57 0.8× 33 812
Boris V. Cherkassky 163 0.3× 212 0.5× 302 1.3× 68 0.6× 43 0.6× 9 949
Abdullah Alamri 452 0.8× 129 0.3× 141 0.6× 72 0.6× 37 0.5× 10 779

Countries citing papers authored by Congrui Huang

Since Specialization
Citations

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

Fields of papers citing papers by Congrui Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Congrui Huang

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

All Works

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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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