Han Mao Kiah

114 papers receiving 1.1k citations

Peers

Han Mao Kiah
Comparison fields: 5 of 37
  • Molecular Biology 610
  • Artificial Intelligence 591
  • Computer Networks and Communications 379
  • Computational Theory and Mathematics 371
  • Electrical and Electronic Engineering 259
Replace Antonia Wachter-Zeh with:
Antonia Wachter-Zeh Germany
Ryan Gabrys United States
Xiao Guo-zhen China
Bella Bose United States
B. Bose United States
Ming-Deh A. Huang United States
Hessam Mahdavifar United States
Klaus Sutner United States
Guu-Chang Yang Taiwan
Martti Penttonen Finland
Han Mao Kiah relative to Antonia Wachter-Zeh Germany Antonia Wachter-Zeh's profile →
Citations per field
00.5×4.6×
Antonia Wachter-Zeh · 1×
Citations per year

Countries citing papers authored by Han Mao Kiah

Since Specialization
Citations

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

Fields of papers citing papers by Han Mao Kiah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Han Mao Kiah. 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 Han Mao Kiah. The network helps show where Han Mao Kiah may publish in the future.

Co-authorship network of co-authors of Han Mao Kiah

This figure shows the co-authorship network connecting the top 25 collaborators of Han Mao Kiah. A scholar is included among the top collaborators of Han Mao Kiah 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 Han Mao Kiah. Han Mao Kiah 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 0
2 0
3 1
4 1
5 1
6 0
7 1
8 2
9 0
10 11
11 6
12 1
13
Optimal Reconstruction Codes for Deletion Channels
2
14 9
15 44
16 45
17 10
18
Pure Asymmetric Quantum MDS Codes from CSS Construction: A Complete Characterization
14
19
Pure Asymmetric Quantum MDS Codes from CSS Construction
1
20 34

About Han Mao Kiah

Han Mao Kiah is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Artificial Intelligence, having authored 120 papers that have together received 1.1k indexed citations. Recurring topics across this work include DNA and Biological Computing (48 papers), Advanced Data Storage Technologies (38 papers) and Coding theory and cryptography (33 papers). The work is most often cited by research in Computational Theory and Mathematics (371 citations), Artificial Intelligence (591 citations) and Computer Networks and Communications (379 citations). Han Mao Kiah has collaborated with scholars based in Singapore, United States and Israel. Frequent co-authors include Yeow Meng Chee, Olgica Milenković, Eitan Yaakobi, Tuan Thanh Nguyen, Ryan Gabrys, Alexander Vardy, San Ling, Gregory J. Puleo, Kui Cai and Ka Hin Leung. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Communications and IEEE/ACM Transactions on Networking.

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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