Hua Ma

55 total papers · 470 total citations
33 papers, 319 citations indexed

About

Hua Ma is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Hua Ma has authored 33 papers receiving a total of 319 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Information Systems, 14 papers in Artificial Intelligence and 12 papers in Computer Networks and Communications. Recurrent topics in Hua Ma's work include Cloud Computing and Resource Management (9 papers), IoT and Edge/Fog Computing (7 papers) and Caching and Content Delivery (6 papers). Hua Ma is often cited by papers focused on Cloud Computing and Resource Management (9 papers), IoT and Edge/Fog Computing (7 papers) and Caching and Content Delivery (6 papers). Hua Ma collaborates with scholars based in China, Canada and United States. Hua Ma's co-authors include Zhigang Hu, Haibin Zhu, Keqin Li, Wensheng Tang, Hong‐yu Zhang, Pingping Dong, Yang Liu, Libo Zhang, Jingze Li and Hongyu Zhang and has published in prestigious journals such as Knowledge-Based Systems, Frontiers in Human Neuroscience and Future Generation Computer Systems.

In The Last Decade

Hua Ma

28 papers receiving 311 citations

Author Peers

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

Author Last Decade Papers Cites
Hua Ma 161 146 96 88 28 33 319
Ghaith M. Jaradat 91 0.6× 58 0.4× 65 0.7× 105 1.2× 13 0.5× 35 360
Khaironi Yatim Sharif 172 1.1× 88 0.6× 41 0.4× 49 0.6× 48 1.7× 37 351
Paul J. Deitel 137 0.9× 82 0.6× 20 0.2× 86 1.0× 47 1.7× 41 359
Miguel J. Hornos 45 0.3× 54 0.4× 97 1.0× 100 1.1× 11 0.4× 42 343
Daniel Tovarňák 130 0.8× 140 1.0× 16 0.2× 60 0.7× 23 0.8× 25 250
K. Vivekanandan 164 1.0× 63 0.4× 39 0.4× 139 1.6× 25 0.9× 55 326
Víctor Sánchez-Anguix 49 0.3× 54 0.4× 73 0.8× 119 1.4× 30 1.1× 26 276
Wei Du 156 1.0× 151 1.0× 23 0.2× 95 1.1× 31 1.1× 27 343
I‐Ching Hsu 182 1.1× 102 0.7× 26 0.3× 165 1.9× 20 0.7× 36 306
Cássia Trojahn dos Santos 162 1.0× 39 0.3× 70 0.7× 296 3.4× 13 0.5× 42 361

Countries citing papers authored by Hua Ma

Since Specialization
Citations

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

Fields of papers citing papers by Hua Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hua Ma

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