Lam Pham

503 total citations
49 papers, 201 citations indexed

About

Lam Pham is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Lam Pham has authored 49 papers receiving a total of 201 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Signal Processing, 13 papers in Computer Vision and Pattern Recognition and 12 papers in Artificial Intelligence. Recurrent topics in Lam Pham's work include Music and Audio Processing (21 papers), Speech and Audio Processing (15 papers) and Music Technology and Sound Studies (7 papers). Lam Pham is often cited by papers focused on Music and Audio Processing (21 papers), Speech and Audio Processing (15 papers) and Music Technology and Sound Studies (7 papers). Lam Pham collaborates with scholars based in Austria, Vietnam and United Kingdom. Lam Pham's co-authors include Dat Ngo, Ian McLoughlin, Huy Phan, Alexander Schindler, Thanh Duc Ngo, Anh Gia-Tuan Nguyen, Ramaswamy Palaniappan, Khoa Tran, Michael Rotter and Jin Y. Ooi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Lightwave Technology and Transactions of the American Mathematical Society.

In The Last Decade

Lam Pham

41 papers receiving 191 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lam Pham Austria 7 88 40 39 34 26 49 201
Yuan Xie China 9 90 1.0× 24 0.6× 6 0.2× 22 0.6× 59 2.3× 37 290
Roberta Avanzato Italy 9 41 0.5× 31 0.8× 38 1.0× 31 0.9× 33 1.3× 37 292
Qing Song China 10 13 0.1× 56 1.4× 13 0.3× 197 5.8× 23 0.9× 28 341
Franko Hržić Croatia 8 14 0.2× 62 1.6× 14 0.4× 51 1.5× 10 0.4× 26 271
Cláudio Rosito Jung Brazil 8 13 0.1× 76 1.9× 7 0.2× 258 7.6× 25 1.0× 13 342
Jung Ho Lee South Korea 9 52 0.6× 57 1.4× 5 0.1× 30 0.9× 190 7.3× 31 309
Pavan Kumar Anasosalu Vasu United States 5 10 0.1× 54 1.4× 4 0.1× 129 3.8× 23 0.9× 6 250
M. Radha India 3 10 0.1× 45 1.1× 4 0.1× 180 5.3× 10 0.4× 4 284

Countries citing papers authored by Lam Pham

Since Specialization
Citations

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

Fields of papers citing papers by Lam Pham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lam Pham

This figure shows the co-authorship network connecting the top 25 collaborators of Lam Pham. A scholar is included among the top collaborators of Lam 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 Lam Pham. Lam Pham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Pham, Lam, Dat Q. Tran, Tin Nguyen, et al.. (2025). A comprehensive survey with critical analysis for deepfake speech detection. Computer Science Review. 57. 100757–100757. 3 indexed citations
4.
Pham, Lam, et al.. (2024). Neural Network with Optical Frequency-Coded ReLU. Zenodo (CERN European Organization for Nuclear Research). M4C.2–M4C.2. 2 indexed citations
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Pham, Lam, et al.. (2024). Photonic Neuron With on Frequency-Domain ReLU Activation Function. Journal of Lightwave Technology. 42(22). 7919–7928. 1 indexed citations
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Pham, Lam, et al.. (2024). Landslide Detection and Segmentation Using Remote Sensing Images and Deep Neural Networks. 9582–9586. 2 indexed citations
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Pham, Lam, et al.. (2024). LSTM-based Deep Neural Network With A Focus on Sentence Representation for Sequential Sentence Classification in Medical Scientific Abstracts. SHILAP Revista de lepidopterología. 39. 219–224. 1 indexed citations
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Pham, Lam, et al.. (2023). Lightweight deep neural networks for acoustic scene classification and an effective visualization for presenting sound scene contexts. Applied Acoustics. 211. 109489–109489. 5 indexed citations
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Pham, Lam, et al.. (2023). A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification. 177–184. 2 indexed citations
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Pham, Lam, et al.. (2022). Bottom of the length spectrum of arithmetic orbifolds. Transactions of the American Mathematical Society. 376(7). 4745–4764. 1 indexed citations
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Ngo, Dat, et al.. (2022). Sound Context Classification based on Joint Learning Model and Multi-Spectrogram Features. International Journal of Computing. 258–270. 5 indexed citations
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Pham, Lam, et al.. (2022). An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification. 23–28. 5 indexed citations
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Pham, Lam, et al.. (2021). An Audio-Based Deep Learning Framework For BBC Television Programme Classification. 2021 29th European Signal Processing Conference (EUSIPCO). 56–60. 1 indexed citations
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Pham, Lam. (2020). Predicting Respiratory Anomalies and Diseases Using Deep Learning Models. arXiv (Cornell University). 3 indexed citations
19.
Pham, Lam, Ian McLoughlin, Huy Phan, Ramaswamy Palaniappan, & Yue Lang. (2019). Bag-of-Features Models Based on C-DNN Network for Acoustic Scene Classification. Kent Academic Repository (University of Kent). 3 indexed citations
20.
Pham, Lam. (2007). Actions on Structures: Regulations and Standards. Electronic Journal of Structural Engineering. 4–8. 1 indexed citations

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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2026