Hua Ma

448 citations
20 papers · 290 indexed · h-index 9
Topics
Adversarial Robustness in Machine Learning (9 papers)Advanced Neural Network Applications (6 papers)Physical Unclonable Functions (PUFs) and Hardware Security (5 papers)

In The Last Decade

Hua Ma

19 papers receiving 282 citations

Peers

Hua Ma
Comparison fields: 5 of 48
  • Hardware and Architecture 158
  • Electrical and Electronic Engineering 141
  • Artificial Intelligence 96
  • Cellular and Molecular Neuroscience 89
  • Computer Networks and Communications 44
Replace Ahmed Khairy Mahmoud with:
Ahmed Khairy Mahmoud Egypt
Michael Schaffner Switzerland
Rong Xu China
M. Anguita Spain
Alexandros Nikolaos Ziogas Switzerland
Zhan Yu China
Yves Mathieu France
Vikash Kumar India
Reza Rahimi United States
Robert A. Iannucci United States
Hua Ma relative to Ahmed Khairy Mahmoud Egypt Ahmed Khairy Mahmoud's profile →
Citations per field
00.5×3.7×
Ahmed Khairy Mahmoud · 1×
Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 5
4 3
5 4
6 4
7 6
8 9
9 6
10 12
11 8
12 1
13 32
14 6
15 10
16 61
17 33
18 63
19 19
20
A Traitor Tracing Scheme Based on the RSA System.
7

About Hua Ma

Hua Ma is a scholar working on Hardware and Architecture, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 290 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (9 papers), Advanced Neural Network Applications (6 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (5 papers). The work is most often cited by research in Hardware and Architecture (158 citations), Cellular and Molecular Neuroscience (89 citations) and Signal Processing (41 citations). Hua Ma has collaborated with scholars based in China, Australia and South Korea. Frequent co-authors include Said F. Al-Sarawi, Derek Abbott, Damith C. Ranasinghe, Yansong Gao, Yansong Gao, Omid Kavehei, Gefei Li, Anmin Fu, Jingtao Wang and Cheng Chen. Their work appears in journals such as Expert Systems with Applications, Remote Sensing and IEEE Transactions on Information Forensics and Security.

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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