Sheng Zha

43 total papers · 678 total citations
9 papers, 246 citations indexed

About

Sheng Zha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Sheng Zha has authored 9 papers receiving a total of 246 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Sheng Zha's work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Multimodal Machine Learning Applications (3 papers). Sheng Zha is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Multimodal Machine Learning Applications (3 papers). Sheng Zha collaborates with scholars based in United States and Germany. Sheng Zha's co-authors include He He, Haohan Wang, Leonard Lausen, George Karypis, Mu Li, Hang Zhang, Chenguang Wang, Xingjian Shi, Tong He and He He and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

In The Last Decade

Sheng Zha

7 papers receiving 238 citations

Author Peers

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

Author						Papers	Cites
Sheng Zha	165	90	12	11	11	9	246
David Münch	114 0.7×	87 1.0×	6 0.5×	10 0.9×	10 0.9×	10	286
Shang-Tse Chen	140 0.8×	85 0.9×	17 1.4×	10 0.9×	35 3.2×	18	213
Nitin Kumar Chauhan	101 0.6×	35 0.4×	10 0.8×	7 0.6×	13 1.2×	9	262
Tianyu Xu	169 1.0×	84 0.9×	25 2.1×	15 1.4×	7 0.6×	15	286
Joshua V. Dillon	146 0.9×	77 0.9×	18 1.5×	4 0.4×	20 1.8×	9	206
Patrick Letrémy	115 0.7×	55 0.6×	11 0.9×	5 0.5×	21 1.9×	9	202
A. Lamas	150 0.9×	151 1.7×	10 0.8×	5 0.5×	12 1.1×	10	302
Yuanhang Su	90 0.5×	90 1.0×	22 1.8×	13 1.2×	14 1.3×	10	268
Shashank Mujumdar	108 0.7×	33 0.4×	32 2.7×	10 0.9×	12 1.1×	11	239
Nilaksh Das	150 0.9×	101 1.1×	12 1.0×	4 0.4×	31 2.8×	11	279

Countries citing papers authored by Sheng Zha

Since Specialization

Citations

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

Fields of papers citing papers by Sheng Zha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Zha

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