Can Cui

508 citations
30 papers · 337 · h-index 11

Impact in

Papers in

Can Cui

27 papers receiving 329 citations

Peers

Can Cui
Comparison fields: 5 of 68
  • Atomic and Molecular Physics, and Optics 122
  • Electrical and Electronic Engineering 196
  • Artificial Intelligence 86
  • Condensed Matter Physics 22
  • Electronic, Optical and Magnetic Materials 28
Replace Ann Ackaert with:
Ann Ackaert Belgium
Holger Büch Australia
Samiran Ganguly United States
Sebastian Luber Germany
Bradley Hauer Canada
Shreyas Muralidhar Sweden
Daryoush Shiri Sweden
Ana Gómez Oliva Spain
Tianhan Wang China
Arpan Deyasi India
Can Cui relative to Ann Ackaert Belgium Ann Ackaert's profile →
Citations per field
00.5×20×40×63×
Ann Ackaert · 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 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202149
2 202245
3 202141
4 202130
5 202022
6 202117
7 202316
8 202016
9 202014
10 202314
11 202212
12 201510
13 20229
14 20199
15 20227
16
Early Marketplace Enrollees Were Older and Used More Medication Than Later Enrollees
20154
17
What is the Rationale for an Insurance Coverage Mandate? Evidence from Workers’ Compensation Insurance
20193
18 20243
19 20253
20 20183

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 30 papers that have together received 337 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (12 papers), Ferroelectric and Negative Capacitance Devices (8 papers), Neural Networks and Reservoir Computing (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 Innovative Energy Harvesting Technologies (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (122 citations), Electrical and Electronic Engineering (196 citations), Artificial Intelligence (86 citations), Condensed Matter Physics (22 citations) and Electronic, Optical and Magnetic Materials (28 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, Thomas M. Leonard, Felipe García‐Sánchez and Lin Xue. Their work appears in journals such as Applied Physics Letters, Sensors, Nano Letters, Physics of Fluids and Advanced Electronic Materials.

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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