Hai Pham

37 total papers · 856 total citations
13 papers, 458 citations indexed

About

Hai Pham is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Hai Pham has authored 13 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Signal Processing. Recurrent topics in Hai Pham's work include Face recognition and analysis (7 papers), Multimodal Machine Learning Applications (4 papers) and Speech and Audio Processing (3 papers). Hai Pham is often cited by papers focused on Face recognition and analysis (7 papers), Multimodal Machine Learning Applications (4 papers) and Speech and Audio Processing (3 papers). Hai Pham collaborates with scholars based in United States, Singapore and United Kingdom. Hai Pham's co-authors include Paul Pu Liang, Thomas Manzini, Barnabás Póczos, Louis–Philippe Morency, Vladimir Pavlović, Samuel Cheung, Yuting Wang, Ricardo Guerrero, Jiatong Li and Tat‐Jen Cham and has published in prestigious journals such as IEEE Transactions on Affective Computing, Journal of Visual Communication and Image Representation and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Hai Pham

12 papers receiving 444 citations

Hit Papers

Found in Translation: Lea... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Hai Pham 279 224 135 124 40 13 458
S. Narayanan 269 1.0× 107 0.5× 186 1.4× 105 0.8× 39 1.0× 27 451
Yuli Xue 229 0.8× 180 0.8× 141 1.0× 197 1.6× 16 0.4× 24 483
Zhimeng Zhang 134 0.5× 393 1.8× 122 0.9× 72 0.6× 58 1.4× 33 542
Najmeh Sadoughi 255 0.9× 105 0.5× 165 1.2× 204 1.6× 38 0.9× 14 428
Olivier Deroo 375 1.3× 67 0.3× 259 1.9× 110 0.9× 22 0.6× 19 515
Suzhen Wang 65 0.2× 294 1.3× 108 0.8× 65 0.5× 57 1.4× 26 416
Thomas Polzin 294 1.1× 136 0.6× 202 1.5× 285 2.3× 10 0.3× 13 542
Zenghai Chen 102 0.4× 244 1.1× 42 0.3× 191 1.5× 60 1.5× 20 469
Licai Sun 256 0.9× 133 0.6× 110 0.8× 237 1.9× 10 0.3× 21 457
Mohamed R. Amer 231 0.8× 264 1.2× 60 0.4× 37 0.3× 14 0.3× 24 425

Countries citing papers authored by Hai Pham

Since Specialization
Citations

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

Fields of papers citing papers by Hai Pham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Pham. 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 Hai Pham. The network helps show where Hai Pham may publish in the future.

Co-authorship network of co-authors of Hai Pham

This figure shows the co-authorship network connecting the top 25 collaborators of Hai Pham. A scholar is included among the top collaborators of Hai Pham based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hai Pham. Hai Pham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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