Ming-Chang Yang

86 papers receiving 727 citations

Peers

Ming-Chang Yang
Comparison fields: 5 of 72
  • Hardware and Architecture 282
  • Computer Networks and Communications 542
  • Computational Theory and Mathematics 87
  • Information Systems 94
  • Computer Vision and Pattern Recognition 54
Replace Siamak Mohammadi with:
Siamak Mohammadi Iran
Liang Shi China
Rino Micheloni Italy
Abdel‐Hameed A. Badawy United States
Ki‐Young Choi South Korea
Yongjun Park South Korea
James P. Black Canada
Farshad Safaei Iran
H. Q. Le United States
Takashi Nanya Japan
Ming-Chang Yang relative to Siamak Mohammadi Iran Siamak Mohammadi's profile →
Citations per field
00.5×1.5×2.3×
Siamak Mohammadi · 1×
Citations per year

Countries citing papers authored by Ming-Chang Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Chang Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming-Chang 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 Ming-Chang Yang Line = papers co-authored together Ming-Chang Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201465
2 201352
3 201733
4 202029
5
Evaluating host aware SMR drives
201629
6 202129
7 202224
8 201320
9 201720
10 201819
11 201319
12 202019
13 201815
14 201915
15 202015
16 201515
17 202014
18 201314
19 201614
20 202113

About Ming-Chang Yang

Ming-Chang Yang is a scholar working on Computer Networks and Communications, Hardware and Architecture, Information Systems, Electrical and Electronic Engineering and Computational Theory and Mathematics, having authored 93 papers that have together received 738 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (71 papers), Parallel Computing and Optimization Techniques (49 papers), Caching and Content Delivery (42 papers), Cellular Automata and Applications (13 papers), Advanced Memory and Neural Computing (9 papers), Cloud Computing and Resource Management (7 papers), Magnetic properties of thin films (7 papers) and Cloud Data Security Solutions (7 papers). The work is most often cited by research in Hardware and Architecture (282 citations), Computer Networks and Communications (542 citations), Computational Theory and Mathematics (87 citations), Information Systems (94 citations) and Computer Vision and Pattern Recognition (54 citations). Ming-Chang Yang has collaborated with scholars based in Taiwan, Hong Kong and China. Frequent co-authors include Yuan-Hao Chang, Tei‐Wei Kuo, Po‐Chun Huang, Chun-Feng Wu, David H. C. Du, Yu-Ming Chang, Tseng‐Yi Chen, Shuo-Han Chen, Wei‐Kuan Shih and Ren‐Hung Hwang. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ACM Transactions on Embedded Computing Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and IEEE Electron Device Letters.

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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