Jin Sima

522 citations
27 papers · 317 · h-index 10

Impact in

Papers in

Jin Sima

26 papers receiving 314 citations

Peers

Jin Sima
Comparison fields: 5 of 20
  • Computational Theory and Mathematics 92
  • Computer Networks and Communications 116
  • Artificial Intelligence 148
  • Molecular Biology 264
  • Electrical and Electronic Engineering 31
Replace Tuan Thanh Nguyen with:
Tuan Thanh Nguyen Singapore
Wentu Song Singapore
S. M. Hossein Tabatabaei Yazdi United States
Kedar Tatwawadi United States
Vladimir N. Potapov Russia
David Simplot France
Katsunobu Imai Japan
Chong Shangguan China
Hiroshi Umeo Japan
Vitaly Skachek Estonia
Jin Sima relative to Tuan Thanh Nguyen Singapore Tuan Thanh Nguyen's profile →
Citations per field
00.5×1.5×
Tuan Thanh Nguyen · 1×
Citations per year

Countries citing papers authored by Jin Sima

Since Specialization
Citations

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

Fields of papers citing papers by Jin Sima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Jin Sima, 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 Jin Sima Line = papers co-authored together Jin Sima links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202046
2 202046
3 201937
4 201936
5 202026
6 202022
7 202117
8 201912
9 202012
10 202111
11 20238
12 20217
13 20195
14 20185
15 20144
16 20233
17 20243
18 20173
19 20252
20 20222

About Jin Sima

Jin Sima is a scholar working on Molecular Biology, Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 27 papers that have together received 317 indexed citations. Recurring topics across this work include DNA and Biological Computing (20 papers), Advanced biosensing and bioanalysis techniques (13 papers), Algorithms and Data Compression (12 papers), Error Correcting Code Techniques (4 papers), Cooperative Communication and Network Coding (3 papers), Advanced Data Storage Technologies (3 papers), Cellular Automata and Applications (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computational Theory and Mathematics (92 citations), Computer Networks and Communications (116 citations), Artificial Intelligence (148 citations), Molecular Biology (264 citations) and Electrical and Electronic Engineering (31 citations). Jin Sima has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Jehoshua Bruck, Ryan Gabrys, Netanel Raviv, Farzad Farnoud, Wei Chen, Olgica Milenković, Ilan Shomorony, Moshe Schwartz, Krishna R. Narayanan and Anxiao Jiang. Their work appears in journals such as IEEE Transactions on Information Theory, Entropy and 2022 IEEE International Symposium on Information Theory (ISIT).

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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