Wai-man Lam

730 citations
21 papers · 391 · h-index 10

Impact in

Papers in

Wai-man Lam

19 papers receiving 355 citations

Peers

Wai-man Lam
Comparison fields: 5 of 57
  • Computer Networks and Communications 134
  • Signal Processing 56
  • Artificial Intelligence 129
  • Computer Vision and Pattern Recognition 78
  • Statistics and Probability 28
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Lucia D’Acunto Netherlands
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Rishabh Kaushal India
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Citations per field
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Citations per year

Countries citing papers authored by Wai-man Lam

Since Specialization
Citations

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

Fields of papers citing papers by Wai-man Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Wai-man 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 Wai-man Lam Line = papers co-authored together Wai-man Lam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993124
2 199568
3 201543
4 201024
5 200517
6 201316
7 199616
8 201815
9 200715
10
Public Policymaking in Hong Kong: Civic Engagement and State-Society Relations in a Semi-Democracy
201311
11 20129
12 20037
13
China's United Front Work in Civil Society: The Case of Hong Kong +
20136
14
Contemporary Hong Kong Politics: Governance in the Post-1997 Era
20076
15
Migrants and democratization: The political economy of Chinese immigrants in Hong Kong
20165
16 20064
17
Understanding the Political Culture of Hong Kong: The Paradox of Activism and Depoliticization: The Paradox of Activism and Depoliticization
20042
18 20141
19 20121
20 20241

About Wai-man Lam

Wai-man Lam is a scholar working on Sociology and Political Science, Political Science and International Relations, Artificial Intelligence, Demography and Computer Networks and Communications, having authored 21 papers that have together received 391 indexed citations. Recurring topics across this work include Hong Kong and Taiwan Politics (11 papers), Social Policy and Reform Studies (3 papers), Diaspora, migration, transnational identity (2 papers), Migration, Refugees, and Integration (2 papers), Socioeconomic Development in Asia (2 papers), Cellular Automata and Applications (1 paper), Video Coding and Compression Technologies (1 paper) and Electoral Systems and Political Participation (1 paper). The work is most often cited by research in Computer Networks and Communications (134 citations), Signal Processing (56 citations), Artificial Intelligence (129 citations), Computer Vision and Pattern Recognition (78 citations) and Statistics and Probability (28 citations). Wai-man Lam has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Amy R. Reibman, Sanjeev R. Kulkarni, Ngok Ma, Stan Hok‐Wui Wong, Ian Holliday, Wai Fung Lam, Elaine Chan, Wilson Wong and Émilie Tran. Their work appears in journals such as PS Political Science & Politics, IEEE Transactions on Image Processing, International Journal of Public Administration, IEEE Transactions on Communications and Social Indicators Research.

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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