Aimin Yang

2.8k citations
119 papers · 2.0k · 1 hit paper · h-index 24

Impact in

Papers in

Aimin Yang

107 papers receiving 1.9k citations

Aimin Yang's Hit Papers

A survey on big data-enabled innovative online education systems during the COVID-19 pandemic 2022 · 84 citations
840+1+2Years since publication255075

Peers

Aimin Yang
Comparison fields: 5 of 168
  • Health Informatics 29
  • Artificial Intelligence 520
  • Computer Networks and Communications 314
  • Signal Processing 139
  • Business and International Management 25
Replace Sachin Sharma with:
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Bhekisipho Twala South Africa
Sudan Jha India
Caiming Zhang China
Kuruva Lakshmanna India
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Aimin Yang relative to Sachin Sharma India Sachin Sharma's profile →
Citations per field
00.5×3.9×
Sachin Sharma · 1×
Citations per year

Countries citing papers authored by Aimin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Aimin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aimin Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aimin Yang Line = papers co-authored together Aimin Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 119 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019179
2 2023104
3 202298
4 201997
5 201992
6 202091
7
A survey on big data-enabled innovative online education systems during the COVID-19 pandemic
Hit paper breakdown →
202284
8 201967
9 201965
10 201762
11 200560
12 201859
13 201856
14 201836
15 201434
16 202233
17 201933
18 202332
19 202032
20 201931

About Aimin Yang

Aimin Yang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanical Engineering, Information Systems and Computer Networks and Communications, having authored 119 papers that have together received 2.0k indexed citations. Recurring topics across this work include Iron and Steelmaking Processes (15 papers), Mineral Processing and Grinding (8 papers), Metallurgical Processes and Thermodynamics (7 papers), Face and Expression Recognition (6 papers), Network Security and Intrusion Detection (6 papers), Physical Activity and Education Research (6 papers), Fuzzy Logic and Control Systems (5 papers) and Machine Learning and ELM (5 papers). The work is most often cited by research in Health Informatics (29 citations), Artificial Intelligence (520 citations), Computer Networks and Communications (314 citations), Signal Processing (139 citations) and Business and International Management (25 citations). Aimin Yang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Chunying Zhang, Huixiang Liu, Yang Han, Jie Li, Zezhong Ma, Liya Wang, Gunasekaran Manogaran, Hanliang Fu, Ming Cao and Song Jiang. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal, Future Generation Computer Systems, Alexandria Engineering Journal and Science and Technology of Advanced Materials.

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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