Han Cai

624 total citations · 1 hit paper
26 papers, 290 citations indexed

About

Han Cai is a scholar working on Sociology and Political Science, Artificial Intelligence and Physiology. According to data from OpenAlex, Han Cai has authored 26 papers receiving a total of 290 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Sociology and Political Science, 6 papers in Artificial Intelligence and 4 papers in Physiology. Recurrent topics in Han Cai's work include Digital Marketing and Social Media (3 papers), Ovarian function and disorders (2 papers) and Circadian rhythm and melatonin (2 papers). Han Cai is often cited by papers focused on Digital Marketing and Social Media (3 papers), Ovarian function and disorders (2 papers) and Circadian rhythm and melatonin (2 papers). Han Cai collaborates with scholars based in China, South Korea and United States. Han Cai's co-authors include Song Han, Chuang Gan, Abbas Mardani, Brett H. Hokr, Marlan O. Scully, Kai Wang, Alexei V. Sokolov, Ziyun Di, Vladislav V. Yakovlev and Hui Du and has published in prestigious journals such as Nature, Nature Communications and Annual Review of Immunology.

In The Last Decade

Han Cai

25 papers receiving 279 citations

Hit Papers

EfficientViT: Lightweight Multi-Scale Attention for High-... 2023 2026 2024 2025 2023 25 50 75 100

Peers

Han Cai
Comparison fields: 5 of 113
  • Computer Vision and Pattern Recognition 61
  • Artificial Intelligence 31
  • Immunology 25
  • Analytical Chemistry 22
  • Sociology and Political Science 21
Jiahong Zhang China
Kajsa Møllersen Norway
Shailendra Kumar Singh India
Nuh Alpaslan Türkiye
Ali Hussain South Korea
Tony Griffiths United Kingdom
Shannon Quinn United States
Zeyang Zhang China
Mohammad Shuaib Mir Saudi Arabia
Jiahong Zhang China View profile →
Citations per field, relative to Han Cai
Han Cai · 1×
Citations per year, relative to Han Cai
Han Cai · 1×

Countries citing papers authored by Han Cai

Since Specialization
Citations

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

Fields of papers citing papers by Han Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Han Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Han Cai. A scholar is included among the top collaborators of Han Cai 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 Cai. Han Cai 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
# Work Indexed citations
1 0
2 1
3 2
4 8
5 2
6 17
7 1
8 7
9 14
10 1
11 16
12 3
13 10
14 8
15 15
16 10
17
Reinforcement Learning for Architecture Search by Network Transformation
12
18 3
19
Modeling for Reputation Computing in C2C Communities
7
20 5

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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