An Chan

533 citations
14 papers · 410 · h-index 11

Impact in

Papers in

An Chan

14 papers receiving 389 citations

Peers

An Chan
Comparison fields: 5 of 33
  • Computer Networks and Communications 223
  • Computer Vision and Pattern Recognition 178
  • Signal Processing 65
  • Electrical and Electronic Engineering 238
  • Artificial Intelligence 66
Replace Robert Kinicki with:
Robert Kinicki United States
Gaetano Carlucci Italy
Ashkan Nikravesh United States
Mário Almeida United Kingdom
Katherine Guo United States
K.J. Ray Liu United States
Sanjeev Mehrotra United States
Shu Lin United States
Fulu Li United States
Johan Garcia Sweden
An Chan relative to Robert Kinicki United States Robert Kinicki's profile →
Citations per field
00.5×4.7×
Robert Kinicki · 1×
Citations per year

Countries citing papers authored by An Chan

Since Specialization
Citations

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

Fields of papers citing papers by An Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside An Chan, 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 An Chan Line = papers co-authored together An Chan links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2010191
2 201050
3 201032
4 201224
5 201320
6 201118
7 200814
8 200912
9 200811
10 201510
11 201110
12 20067
13 20087
14 20134

About An Chan

An Chan is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Sociology and Political Science and Signal Processing, having authored 14 papers that have together received 410 indexed citations. Recurring topics across this work include Wireless Networks and Protocols (8 papers), Mobile Ad Hoc Networks (7 papers), Image and Video Quality Assessment (5 papers), Multimedia Communication and Technology (4 papers), Video Coding and Compression Technologies (3 papers), Advanced Wireless Network Optimization (3 papers), Advanced MIMO Systems Optimization (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Computer Networks and Communications (223 citations), Computer Vision and Pattern Recognition (178 citations), Signal Processing (65 citations), Electrical and Electronic Engineering (238 citations) and Artificial Intelligence (66 citations). An Chan has collaborated with scholars based in United States, Hong Kong and India. Frequent co-authors include Prasant Mohapatra, Daniel Wu, Kai Zeng, Amit Pande, Sujata Banerjee, Sung-Ju Lee, Soung Chang Liew, Kai Zeng, Xiaolin Cheng and Soung‐Yue Liew. Their work appears in journals such as IEEE Transactions on Mobile Computing, Multimedia Tools and Applications, IEEE Communications Magazine and Pervasive and Mobile 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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