Dan Liao

3.1k citations
91 papers · 2.4k · h-index 25

Impact in

Papers in

Dan Liao

88 papers receiving 2.3k citations

Peers

Dan Liao
Comparison fields: 5 of 107
  • Computer Networks and Communications 1.2k
  • Information Systems 730
  • Building and Construction 389
  • Artificial Intelligence 523
  • Computer Science Applications 75
Replace Fan Liang with:
Fan Liang United States
Suat Özdemi̇r Türkiye
Rafidah Md Noor Malaysia
Leonardo Mostarda Italy
Yun Li China
Abid Khan Pakistan
Hasan Ali Khattak Pakistan
Ashiq Anjum United Kingdom
Amir Taherkordi Norway
Degan Zhang China
Dan Liao relative to Fan Liang United States Fan Liang's profile →
Citations per field
00.5×5.6×
Fan Liang · 1×
Citations per year

Countries citing papers authored by Dan Liao

Since Specialization
Citations

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

Fields of papers citing papers by Dan Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009282
2 2018193
3 2018189
4 2015171
5 2018163
6 2016116
7 201585
8 201678
9 200972
10 201965
11 202064
12 201661
13 201855
14 201449
15 201844
16 201939
17 201738
18 202237
19 201837
20 201934

About Dan Liao

Dan Liao is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, Artificial Intelligence and Sociology and Political Science, having authored 91 papers that have together received 2.4k indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (37 papers), Advanced Optical Network Technologies (23 papers), Cloud Computing and Resource Management (19 papers), Caching and Content Delivery (18 papers), Privacy-Preserving Technologies in Data (17 papers), IoT and Edge/Fog Computing (13 papers), Vehicular Ad Hoc Networks (VANETs) (11 papers) and Privacy, Security, and Data Protection (9 papers). The work is most often cited by research in Computer Networks and Communications (1.2k citations), Information Systems (730 citations), Building and Construction (389 citations), Artificial Intelligence (523 citations) and Computer Science Applications (75 citations). Dan Liao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Gang Sun, Hongfang Yu, Victor Chang, Changzhi Yang, Jinghua Yu, Liwei Tian, Dongcheng Zhao, Mohsen Guizani, Xiaojiang Du and Yayu Li. Their work appears in journals such as Future Generation Computer Systems, IEEE Access, Journal of Network and Computer Applications, Information Sciences and Computer Networks.

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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