Philip Pham

1.2k total citations
8 papers, 304 citations indexed

About

Philip Pham is a scholar working on Artificial Intelligence, Computer Networks and Communications and Oceanography. According to data from OpenAlex, Philip Pham has authored 8 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Oceanography. Recurrent topics in Philip Pham's work include Topic Modeling (3 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Philip Pham is often cited by papers focused on Topic Modeling (3 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Philip Pham collaborates with scholars based in United States, Switzerland and Netherlands. Philip Pham's co-authors include Robin Pemantle, Diana C. Mutz, Joshua Ainslie, Chris Alberti, Vaclav Cvicek, Qifan Wang, Yang Li, Santiago Ontañón, Anirudh Ravula and Sumit Sanghai and has published in prestigious journals such as The American Statistician, International Journal for Numerical Methods in Biomedical Engineering and Neural Information Processing Systems.

In The Last Decade

Philip Pham

8 papers receiving 295 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philip Pham United States	6	162	55	52	32	26	8	304
William Cohen United States	8	230 1.4×	27 0.5×	73 1.4×	31 1.0×	15 0.6×	22	440
Anne Lauscher Germany	12	384 2.4×	54 1.0×	28 0.5×	16 0.5×	11 0.4×	41	499
Samuel Carton United States	11	225 1.4×	16 0.3×	64 1.2×	24 0.8×	5 0.2×	15	351
Maheen Farooqi Canada	3	211 1.3×	24 0.4×	39 0.8×	8 0.3×	9 0.3×	5	323
Przemyslaw A. Grabowicz Germany	8	63 0.4×	22 0.4×	100 1.9×	5 0.2×	11 0.4×	19	339
Alexandra Schofield United States	8	155 1.0×	24 0.4×	69 1.3×	9 0.3×	2 0.1×	13	310
Bob Nelson United States	8	79 0.5×	46 0.8×	27 0.5×	4 0.1×	10 0.4×	20	251
Anna Rogers United States	11	299 1.8×	67 1.2×	25 0.5×	4 0.1×	5 0.2×	23	370
Christopher Rytting United States	4	187 1.2×	15 0.3×	86 1.7×	15 0.5×	10 0.4×	4	382

Countries citing papers authored by Philip Pham

Since Specialization

Citations

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

Fields of papers citing papers by Philip Pham

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Pham

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Tay, Yi, Mostafa Dehghani, Samira Abnar, et al.. (2021). Long Range Arena : A Benchmark for Efficient Transformers. 15 indexed citations

2.

Juan, Da-Cheng, Chun-Sung Ferng, Allan Heydon, et al.. (2021). Neural Structured Learning: Training Neural Networks with Structured Signals. 1150–1153. 8 indexed citations

3.

Zemlyanskiy, Yury, Joshua Ainslie, Michiel de Jong, et al.. (2021). ReadTwice: Reading Very Large Documents with Memories. 5189–5195. 7 indexed citations

4.

Ainslie, Joshua, Santiago Ontañón, Chris Alberti, et al.. (2020). ETC: Encoding Long and Structured Inputs in Transformers. 268–284. 148 indexed citations

5.

Ahmadian, Sara, Alessandro Epasto, Mohammad Mahdian, et al.. (2020). Fair Hierarchical Clustering. Neural Information Processing Systems. 33. 21050–21060. 1 indexed citations

6.

Juan, Da-Cheng, et al.. (2020). Neural Structured Learning. 3501–3502. 1 indexed citations

7.

Mutz, Diana C., Robin Pemantle, & Philip Pham. (2017). The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data. The American Statistician. 73(1). 32–42. 116 indexed citations

8.

Layton, Anita T., et al.. (2011). Signal transduction in a compliant short loop of Henle. International Journal for Numerical Methods in Biomedical Engineering. 28(3). 369–383. 8 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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