Dafa Li

702 citations
45 papers · 507 · h-index 13

Impact in

Papers in

Dafa Li

40 papers receiving 493 citations

Peers

Dafa Li
Comparison fields: 5 of 51
  • Artificial Intelligence 345
  • Atomic and Molecular Physics, and Optics 293
  • Computational Mathematics 4
  • Automotive Engineering 37
  • Computer Vision and Pattern Recognition 56
Replace Debasis Sarkar with:
Debasis Sarkar India
D. de Falco Italy
Matthias M. Müller Germany
Sanjoy Mandal India
Oliver Sander Germany
Ruixing Long United States
Domaniç Lavery United Kingdom
Neil G. Dickson Canada
Alexander Hentschel Germany
Dafa Li relative to Debasis Sarkar India Debasis Sarkar's profile →
Citations per field
00.5×4.1×
Debasis Sarkar · 1×
Citations per year

Countries citing papers authored by Dafa Li

Since Specialization
Citations

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

Fields of papers citing papers by Dafa Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017127
2 201238
3 202429
4 200729
5 200725
6 202023
7 200621
8 200919
9 201218
10 202116
11 202214
12 200114
13 200313
14 200912
15 200611
16 20259
17 20068
18 20098
19 20106
20 20216

About Dafa Li

Dafa Li is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Mechanical Engineering, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 45 papers that have together received 507 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (27 papers), Quantum Computing Algorithms and Architecture (24 papers), Quantum Mechanics and Applications (21 papers), Optical measurement and interference techniques (3 papers), Modular Robots and Swarm Intelligence (3 papers), Electric and Hybrid Vehicle Technologies (3 papers), Hydraulic and Pneumatic Systems (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). The work is most often cited by research in Artificial Intelligence (345 citations), Atomic and Molecular Physics, and Optics (293 citations), Computational Mathematics (4 citations), Automotive Engineering (37 citations) and Computer Vision and Pattern Recognition (56 citations). Dafa Li has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Xiangrong Li, Hongtao Huang, Xinxin Li, Huanlong Liu, Jiawei Wang, Xiangrong Li, Xiang Qian, Chaobo Zhang, Weihua Gui and Xiaojun Liang. Their work appears in journals such as Physical Review A, Quantum Information Processing, Quantum Information and Computation, Physics Letters A and Biosystems.

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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