Chenglu Jin

59 papers receiving 924 citations

Peers

Chenglu Jin
Comparison fields: 5 of 67
  • Hardware and Architecture 300
  • General Energy 23
  • Economics and Econometrics 424
  • Finance 134
  • Accounting 82
Replace Baohua Yang with:
Baohua Yang China
Ranjan Dasgupta India
James C. T. Mao United States
Harald Vranken Netherlands
Edward M.H. Lin Taiwan
P Zanetti Italy
Mian Dai United States
Jacob Zahavi Israel
André Schweizer Germany
Shihao Gu United States
Chenglu Jin relative to Baohua Yang China Baohua Yang's profile →
Citations per field
00.5×10×15×22.3×
Baohua Yang · 1×
Citations per year

Countries citing papers authored by Chenglu Jin

Since Specialization
Citations

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

Fields of papers citing papers by Chenglu Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019113
2 202298
3 201457
4 202251
5 202147
6 202341
7 201939
8 202433
9 202232
10 201730
11 202430
12 201927
13 201726
14 201925
15 202120
16 201719
17 202218
18 201918
19 201816
20 201713

About Chenglu Jin

Chenglu Jin is a scholar working on Economics and Econometrics, Artificial Intelligence, Finance, Hardware and Architecture and Information Systems, having authored 62 papers that have together received 950 indexed citations. Recurring topics across this work include Physical Unclonable Functions (PUFs) and Hardware Security (17 papers), Market Dynamics and Volatility (13 papers), Financial Markets and Investment Strategies (11 papers), Integrated Circuits and Semiconductor Failure Analysis (10 papers), Cryptographic Implementations and Security (10 papers), Energy, Environment, Economic Growth (8 papers), Cryptography and Data Security (6 papers) and Advanced Memory and Neural Computing (6 papers). The work is most often cited by research in Hardware and Architecture (300 citations), General Energy (23 citations), Economics and Econometrics (424 citations), Finance (134 citations) and Accounting (82 citations). Chenglu Jin has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Xiaohang Ren, Rongda Chen, Marten van Dijk, Phuong Ha Nguyen, Ulrich Rührmair, Kaleel Mahmood, Durga Prasad Sahoo, Weiwei Bao, Xiaofei Guo and Ramesh Karri. Their work appears in journals such as International Review of Financial Analysis, Finance research letters, International Review of Economics & Finance, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Dependable and Secure Computing.

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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