Kin Fun Li

79 papers receiving 648 citations

Peers

Kin Fun Li
Comparison fields: 5 of 99
  • Computer Science Applications 70
  • Human-Computer Interaction 60
  • Hardware and Architecture 67
  • Information Systems 175
  • Computer Vision and Pattern Recognition 156
Replace John Garofalakis with:
John Garofalakis Greece
Elena Verdú Spain
Hossein Falaki United States
Dale C. Rowe United States
Jason Ng United Arab Emirates
Maria Ebling United States
Sami Rollins United States
Kuan‐Ta Chen Taiwan
Rossana M. C. Andrade Brazil
Chandra Narayanaswami United States
Kin Fun Li relative to John Garofalakis Greece John Garofalakis's profile →
Citations per field
00.5×2.7×
John Garofalakis · 1×
Citations per year

Countries citing papers authored by Kin Fun Li

Since Specialization
Citations

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

Fields of papers citing papers by Kin Fun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kin Fun Li. 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 Kin Fun Li. The network helps show where Kin Fun Li may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201255
2 200847
3 201938
4 201137
5 201330
6 201529
7 201129
8 202024
9 200821
10 202119
11 202019
12 201319
13 200715
14 201514
15 202314
16 201813
17 201113
18 201613
19 202212
20 201012

About Kin Fun Li

Kin Fun Li is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems, Artificial Intelligence and Hardware and Architecture, having authored 90 papers that have together received 709 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (11 papers), Video Analysis and Summarization (9 papers), Recommender Systems and Techniques (9 papers), Algorithms and Data Compression (7 papers), Embedded Systems Design Techniques (6 papers), Parallel Computing and Optimization Techniques (6 papers), Distributed systems and fault tolerance (6 papers) and Network Packet Processing and Optimization (5 papers). The work is most often cited by research in Computer Science Applications (70 citations), Human-Computer Interaction (60 citations), Hardware and Architecture (67 citations), Information Systems (175 citations) and Computer Vision and Pattern Recognition (156 citations). Kin Fun Li has collaborated with scholars based in Canada, Japan and China. Frequent co-authors include Darshika G. Perera, Fayez Gebali, Stephen W. Neville, David W. Capson, Stephen Lau, Zhang Li, Wojciech Uchman, J. Kotowicz, Nigel J. Livingston and Foad Hamidi. Their work appears in journals such as International Journal of Embedded Systems, Knowledge-Based Systems, IEEE Access, Journal of Ambient Intelligence and Humanized Computing and Electronics.

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.

Explore authors with similar magnitude of impact