Clement Lee
Impact in
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
-
- Innovative Human-Technology Interaction
Papers in
-
- Complex Network Analysis Techniques 5
- Opinion Dynamics and Social Influence 4
-
- Innovative Human-Technology Interaction 2
- Co-authors
- Darren J. Wilkinson (3 shared papers)Michelle Venables (1 shared paper)Fumiaki Imamura (1 shared paper)Patrick L. Olivier (1 shared paper)Søren Brage (1 shared paper)Emma L. Simpson (1 shared paper)Nita G. Forouhi (1 shared paper)Emma Foster (1 shared paper)
- Journals
- Journal of the American Statistical Association (1 paper)Scientific Reports (1 paper)Journal of Computational and Graphical Statistics (1 paper)Statistics and Computing (1 paper)Journal of Nutritional Science (1 paper)
- Partner nations
- United KingdomAustralia
In The Last Decade
Clement Lee
9 papers receiving 283 citations
Peers
Comparison fields: 5 of 90
- Statistical and Nonlinear Physics 83
- Human-Computer Interaction 19
- Public Health, Environmental and Occupational Health 58
- Artificial Intelligence 52
- Statistics and Probability 12
Countries citing papers authored by Clement Lee
This map shows the geographic impact of Clement Lee'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 Clement Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clement Lee more than expected).
Fields of papers citing papers by Clement Lee
This network shows the impact of papers produced by Clement Lee. 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 Clement Lee. The network helps show where Clement Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Clement Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A review of stochastic block models and extensions for graph clustering | 2019 | 123 |
| 2 | 2019 | 105 | |
| 3 | 2018 | 22 | |
| 4 | 2019 | 13 | |
| 5 | 2021 | 7 | |
| 6 | 2019 | 6 | |
| 7 | 2018 | 5 | |
| 8 | 2017 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 0 |
About Clement Lee
Clement Lee is a scholar working on Statistical and Nonlinear Physics, Human-Computer Interaction, Artificial Intelligence, Transportation and Statistics and Probability, having authored 10 papers that have together received 284 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Bayesian Methods and Mixture Models (4 papers), Opinion Dynamics and Social Influence (4 papers), Innovative Human-Technology Interaction (2 papers), Petroleum Processing and Analysis (1 paper), Green IT and Sustainability (1 paper), Hydrocarbon exploration and reservoir analysis (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (83 citations), Human-Computer Interaction (19 citations), Public Health, Environmental and Occupational Health (58 citations), Artificial Intelligence (52 citations) and Statistics and Probability (12 citations). Clement Lee has collaborated with scholars based in United Kingdom and Australia. Frequent co-authors include Darren J. Wilkinson, Michelle Venables, Fumiaki Imamura, Patrick L. Olivier, Søren Brage, Emma L. Simpson, Nita G. Forouhi, Emma Foster, Timur Osadchiy and Stefanie E. Hollidge. Their work appears in journals such as Journal of the American Statistical Association, Scientific Reports, Journal of Computational and Graphical Statistics, Statistics and Computing and Journal of Nutritional Science.
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.