Tam Le
Impact in
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- Recycling and Waste Management Techniques
- Municipal Solid Waste Management
- Pollution top 5%
- Microplastics and Plastic Pollution
- Pharmaceutical and Antibiotic Environmental Impacts
Papers in
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- Microplastics and Plastic Pollution 5
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- Generative Adversarial Networks and Image Synthesis 1
- Human Pose and Action Recognition 1
- Co-authors
- Emilie Strady (4 shared papers)Thuy-Chung Kieu-Le (2 shared papers)Julien Némery (2 shared papers)Josette Garnier (1 shared paper)Phuoc‐Dan Nguyen (5 shared papers)Thanh‐Son Dao (1 shared paper)An Nguyen (1 shared paper)Christine Baduel (2 shared papers)
In The Last Decade
Tam Le
15 papers receiving 366 citations
Peers
Comparison fields: 5 of 71
- Industrial and Manufacturing Engineering 191
- Pollution 231
- Oceanography 30
- Biomaterials 31
- Environmental Chemistry 20
Countries citing papers authored by Tam Le
This map shows the geographic impact of Tam Le'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 Tam Le with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tam Le more than expected).
Fields of papers citing papers by Tam Le
This network shows the impact of papers produced by Tam Le. 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 Tam Le. The network helps show where Tam Le may publish in the future.
Co-authors
The 25 scholars most cited alongside Tam Le, 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 | 2021 | 112 | |
| 2 | 2023 | 74 | |
| 3 | 2022 | 48 | |
| 4 | 2023 | 47 | |
| 5 | 2021 | 33 | |
| 6 | 2018 | 25 | |
| 7 | 2021 | 12 | |
| 8 | 2020 | 10 | |
| 9 | 2014 | 5 | |
| 10 | Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations | 2015 | 4 |
| 11 | 2024 | 2 | |
| 12 | Fast Tree Variants of Gromov-Wasserstein | 2019 | 1 |
| 13 | Riemannian Manifold Kernel for Persistence Diagrams | 2018 | 1 |
| 14 | 2025 | 1 | |
| 15 | Tree-Sliced Approximation of Wasserstein Distances. | 2019 | 1 |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About Tam Le
Tam Le is a scholar working on Pollution, Computer Vision and Pattern Recognition, Artificial Intelligence, Industrial and Manufacturing Engineering and Computational Theory and Mathematics, having authored 18 papers that have together received 376 indexed citations. Recurring topics across this work include Microplastics and Plastic Pollution (5 papers), Recycling and Waste Management Techniques (3 papers), Water Quality and Pollution Assessment (2 papers), Topological and Geometric Data Analysis (2 papers), Membrane Separation Technologies (1 paper), Markov Chains and Monte Carlo Methods (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (191 citations), Pollution (231 citations), Oceanography (30 citations), Biomaterials (31 citations) and Environmental Chemistry (20 citations). Tam Le has collaborated with scholars based in Vietnam, France and Japan. Frequent co-authors include Emilie Strady, Thuy-Chung Kieu-Le, Julien Némery, Josette Garnier, Phuoc‐Dan Nguyen, Thanh‐Son Dao, An Nguyen, Christine Baduel, Nicolas Gratiot and Nhat Ho. Their work appears in journals such as Case Studies in Chemical and Environmental Engineering, Environmental Pollution, Journal of Optimization Theory and Applications, Marine Pollution Bulletin and Chemosphere.
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.