Hang Yang

63 total papers · 416 total citations
39 papers, 239 citations indexed

About

Hang Yang is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Hang Yang has authored 39 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 14 papers in Signal Processing and 10 papers in Computer Networks and Communications. Recurrent topics in Hang Yang's work include Data Stream Mining Techniques (25 papers), Anomaly Detection Techniques and Applications (18 papers) and Machine Learning and Data Classification (12 papers). Hang Yang is often cited by papers focused on Data Stream Mining Techniques (25 papers), Anomaly Detection Techniques and Applications (18 papers) and Machine Learning and Data Classification (12 papers). Hang Yang collaborates with scholars based in Macao, China and Japan. Hang Yang's co-authors include Simon Fong, Raymond K. Wong, Yvonne Ho, Guangmin Sun, Huajun Chen, Aidong Xu, Jinan Fiaidhi, Sabah Mohammed, Peng Li and Yan Zhuang and has published in prestigious journals such as Journal of Systems and Software, Information Systems Frontiers and Mathematical Problems in Engineering.

In The Last Decade

Hang Yang

36 papers receiving 218 citations

Author Peers

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

Author						Papers	Cites
Hang Yang	146	62	61	55	24	39	239
Renato José Sassi	108 0.7×	73 1.2×	81 1.3×	72 1.3×	14 0.6×	40	284
Djamel Eddine Saïdouni	142 1.0×	39 0.6×	68 1.1×	102 1.9×	33 1.4×	60	316
Ralf Bruns	87 0.6×	36 0.6×	53 0.9×	102 1.9×	26 1.1×	33	304
Songqiao Han	201 1.4×	40 0.6×	28 0.5×	85 1.5×	12 0.5×	25	323
Aman Jatain	100 0.7×	29 0.5×	91 1.5×	42 0.8×	13 0.5×	45	272
T. V. Suresh Kumar	100 0.7×	53 0.9×	106 1.7×	147 2.7×	14 0.6×	40	271
Sujala D. Shetty	109 0.7×	24 0.4×	90 1.5×	57 1.0×	32 1.3×	32	269
Ali Syed	74 0.5×	53 0.9×	86 1.4×	60 1.1×	23 1.0×	28	220
Laïla Benhlima	109 0.7×	22 0.4×	73 1.2×	68 1.2×	32 1.3×	37	321
V. Govindasamy	90 0.6×	51 0.8×	79 1.3×	110 2.0×	10 0.4×	41	284

Countries citing papers authored by Hang Yang

Since Specialization

Citations

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

Fields of papers citing papers by Hang Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hang Yang

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