Cong Shi

2.4k citations
87 papers · 1.8k · 1 hit paper · h-index 20

Impact in

Papers in

Cong Shi

80 papers receiving 1.8k citations

Cong Shi's Hit Papers

Serendipity 2012 · 295 citations
2950+4+9Years since publication50100150200250

Peers

Cong Shi
Comparison fields: 5 of 113
  • Computer Networks and Communications 824
  • Signal Processing 321
  • Computer Vision and Pattern Recognition 389
  • Information Systems 372
  • Human-Computer Interaction 88
Replace João M. P. Cardoso with:
João M. P. Cardoso Portugal
Zhanyong Tang China
Yiwen Wang China
Pedro C. Diniz United States
Gregor Schiele Germany
Shan Chang China
Ashfaq Khokhar United States
Yao Liu United States
Ashvin Goel Canada
Cong Shi relative to João M. P. Cardoso Portugal João M. P. Cardoso's profile →
Citations per field
00.5×2×3.3×
João M. P. Cardoso · 1×
Citations per year

Countries citing papers authored by Cong Shi

Since Specialization
Citations

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

Fields of papers citing papers by Cong Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Serendipity
Hit paper breakdown →
2012295
2 2017230
3 2014145
4 201482
5 201269
6 202062
7 202162
8 201862
9 201759
10 202056
11 201146
12 202146
13 201142
14 202234
15 202133
16 201924
17 202124
18 202324
19 202123
20 201123

About Cong Shi

Cong Shi is a scholar working on Signal Processing, Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering, having authored 87 papers that have together received 1.8k indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (12 papers), Speech and Audio Processing (11 papers), CCD and CMOS Imaging Sensors (11 papers), Adversarial Robustness in Machine Learning (10 papers), Caching and Content Delivery (10 papers), User Authentication and Security Systems (7 papers), Peer-to-Peer Network Technologies (7 papers) and Speech Recognition and Synthesis (7 papers). The work is most often cited by research in Computer Networks and Communications (824 citations), Signal Processing (321 citations), Computer Vision and Pattern Recognition (389 citations), Information Systems (372 citations) and Human-Computer Interaction (88 citations). Cong Shi has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Yingying Jennifer Chen, Mostafa Ammar, Ellen Witte Zegura, Jian Liu, Hongbo Liu, Vasileios Lakafosis, Mayur Naik, Zhuohang Li, Yi Xie and Bo Yuan. Their work appears in journals such as Science China Information Sciences, IEEE Transactions on Mobile Computing, Electronics Letters, IEEE Security & Privacy and Japanese Journal of Applied Physics.

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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