Can Cui

493 citations
29 papers · 323 · h-index 11

Impact in

Papers in

Can Cui

25 papers receiving 315 citations

Peers

Can Cui
Comparison fields: 5 of 70
  • Atomic and Molecular Physics, and Optics 122
  • Electrical and Electronic Engineering 194
  • Artificial Intelligence 86
  • Condensed Matter Physics 22
  • Electronic, Optical and Magnetic Materials 27
Replace Tianhan Wang with:
Tianhan Wang China
Sheng Feng China
Holger Büch Australia
Bismarck Costa Lima Brazil
Isabelle Zaquine France
Samiran Ganguly United States
Sebastian Luber Germany
Daryoush Shiri Sweden
Juwon Seo South Korea
Can Cui relative to Tianhan Wang China Tianhan Wang's profile →
Citations per field
00.5×11.8×
Tianhan Wang · 1×
Citations per year

Countries citing papers authored by Can Cui

Since Specialization
Citations

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

Fields of papers citing papers by Can Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202147
2 202244
3 202141
4 202130
5 202022
6 202116
7 202316
8 202015
9 202314
10 202014
11 202211
12 201510
13 20229
14 20227
15 20197
16
Early Marketplace Enrollees Were Older and Used More Medication Than Later Enrollees
20154
17 20243
18 20183
19
What is the Rationale for an Insurance Coverage Mandate? Evidence from Workers’ Compensation Insurance
20192
20 20242

About Can Cui

Can Cui is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Economics and Econometrics and Biomedical Engineering, having authored 29 papers that have together received 323 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (12 papers), Neural Networks and Reservoir Computing (8 papers), Ferroelectric and Negative Capacitance Devices (8 papers), Magnetic properties of thin films (6 papers), Healthcare Policy and Management (3 papers), Insurance and Financial Risk Management (2 papers), Healthcare Systems and Reforms (2 papers) and Acoustic Wave Resonator Technologies (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (122 citations), Electrical and Electronic Engineering (194 citations), Artificial Intelligence (86 citations), Condensed Matter Physics (22 citations) and Electronic, Optical and Magnetic Materials (27 citations). Can Cui has collaborated with scholars based in United States, China and Spain. Frequent co-authors include Jean Anne C. Incorvia, Christopher H. Bennett, Matthew Marinella, Joseph S. Friedman, T. Patrick Xiao, Samuel Liu, Xuan Hu, Felipe García‐Sánchez, Thomas M. Leonard and Lin Xue. Their work appears in journals such as Applied Physics Letters, Health Affairs, Gait & Posture, IEEE Transactions on Professional Communication and Physics of Fluids.

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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