Kam-Yiu Lam

2.0k citations
147 papers · 1.2k · h-index 20

Impact in

Papers in

Kam-Yiu Lam

140 papers receiving 1.1k citations

Peers

Kam-Yiu Lam
Comparison fields: 5 of 93
  • Hardware and Architecture 420
  • Computer Networks and Communications 924
  • Signal Processing 143
  • Computational Theory and Mathematics 145
  • Computer Vision and Pattern Recognition 185
Replace Kyoung‐Don Kang with:
Kyoung‐Don Kang United States
Chi‐Sheng Shih Taiwan
Mauro Marinoni Italy
Tae‐Sun Chung South Korea
Semeen Rehman Germany
Susmita Sur‐Kolay India
Ajay D. Kshemkalyani United States
Ugo Buy United States
Claude Castelluccia France
David Powell France
Kam-Yiu Lam relative to Kyoung‐Don Kang United States Kyoung‐Don Kang's profile →
Citations per field
00.5×2.7×
Kyoung‐Don Kang · 1×
Citations per year

Countries citing papers authored by Kam-Yiu Lam

Since Specialization
Citations

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

Fields of papers citing papers by Kam-Yiu Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kam-Yiu Lam. 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 Kam-Yiu Lam. The network helps show where Kam-Yiu Lam may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 147 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201956
2 200045
3 200643
4 201441
5 201938
6 200838
7 200036
8 201529
9 200525
10 199924
11 201323
12
Promising Approach to Distributed Query Processing.
198221
13 199921
14 200521
15 200321
16 201220
17 201520
18 201220
19 199919
20 200119

About Kam-Yiu Lam

Kam-Yiu Lam is a scholar working on Computer Networks and Communications, Hardware and Architecture, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computational Theory and Mathematics, having authored 147 papers that have together received 1.2k indexed citations. Recurring topics across this work include Distributed systems and fault tolerance (75 papers), Real-Time Systems Scheduling (52 papers), Distributed and Parallel Computing Systems (22 papers), Petri Nets in System Modeling (16 papers), Data Management and Algorithms (14 papers), Parallel Computing and Optimization Techniques (14 papers), Context-Aware Activity Recognition Systems (13 papers) and Advanced Data Storage Technologies (13 papers). The work is most often cited by research in Hardware and Architecture (420 citations), Computer Networks and Communications (924 citations), Signal Processing (143 citations), Computational Theory and Mathematics (145 citations) and Computer Vision and Pattern Recognition (185 citations). Kam-Yiu Lam has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Song Han, Edward Chan, Ming Xiong, Tei‐Wei Kuo, Victor C. S. Lee, Qingchun Chen, Ben Kao, Joseph Kee‐Yin Ng, Deji Chen and Reynold Cheng. Their work appears in journals such as Journal of Systems and Software, Information Systems, Real-Time Systems, IEEE Transactions on Computers and Journal of Systems Architecture.

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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