Dan Phung

498 total citations
12 papers, 321 citations indexed

About

Dan Phung is a scholar working on Information Systems, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Dan Phung has authored 12 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Information Systems, 4 papers in Computer Networks and Communications and 3 papers in Hardware and Architecture. Recurrent topics in Dan Phung's work include Neural dynamics and brain function (2 papers), Personal Information Management and User Behavior (2 papers) and Software System Performance and Reliability (2 papers). Dan Phung is often cited by papers focused on Neural dynamics and brain function (2 papers), Personal Information Management and User Behavior (2 papers) and Software System Performance and Reliability (2 papers). Dan Phung collaborates with scholars based in United States and Italy. Dan Phung's co-authors include Gail E. Kaiser, Yixin Diao, S. Parekh, Rean Griffith, Akaysha C. Tang, Barak A. Pearlmutter, Jason Nieh, Oren Laadan, Bethany C. Reeb and Joseph L. Hellerstein and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, Neural Computation and ACM SIGOPS Operating Systems Review.

In The Last Decade

Dan Phung

12 papers receiving 294 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dan Phung United States	8	163	124	86	83	78	12	321
Katsuro Inoue Japan	10	51 0.3×	173 1.4×	46 0.5×	51 0.6×	27 0.3×	51	274
Licia Sbattella Italy	9	159 1.0×	77 0.6×	104 1.2×	155 1.9×	36 0.5×	42	297
Matthew J. Renzelmann United States	9	368 2.3×	234 1.9×	103 1.2×	191 2.3×	66 0.8×	12	616
Mihai Capotă Netherlands	9	177 1.1×	113 0.9×	23 0.3×	94 1.1×	41 0.5×	23	316
David S. Kosbie United States	5	92 0.6×	114 0.9×	20 0.2×	148 1.8×	19 0.2×	14	449
Andrew Mickish United States	4	97 0.6×	120 1.0×	16 0.2×	163 2.0×	23 0.3×	6	474
Richard Koman	6	113 0.7×	97 0.8×	32 0.4×	96 1.2×	6 0.1×	11	304
Etsuya Shibayama Japan	8	219 1.3×	55 0.4×	17 0.2×	132 1.6×	19 0.2×	30	385
Christophe Scholliers Belgium	8	106 0.7×	67 0.5×	9 0.1×	66 0.8×	21 0.3×	31	223
R. Stockton Gaines United States	8	70 0.4×	255 2.1×	205 2.4×	58 0.7×	17 0.2×	18	355

Countries citing papers authored by Dan Phung

Since Specialization

Citations

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

Fields of papers citing papers by Dan Phung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Phung

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Phung. A scholar is included among the top collaborators of Dan Phung 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 Dan Phung. Dan Phung 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:

12 of 12 papers shown

1.

Murphy, Christian, Dan Phung, & Gail E. Kaiser. (2008). A distance learning approach to teaching eXtreme programming. Columbia Academic Commons (Columbia University). 199–203. 15 indexed citations

2.

Murphy, Christian, Dan Phung, & Gail E. Kaiser. (2008). A distance learning approach to teaching eXtreme programming. ACM SIGCSE Bulletin. 40(3). 199–203. 10 indexed citations

3.

Laadan, Oren, et al.. (2007). DejaView. ACM SIGOPS Operating Systems Review. 41(6). 279–292. 6 indexed citations

4.

Laadan, Oren, et al.. (2007). DejaView. 279–292. 40 indexed citations

5.

Valetto, Giuseppe, Gail E. Kaiser, & Dan Phung. (2005). A Uniform Programming Abstraction for Effecting Autonomic Adaptations onto Software Systems. Columbia Academic Commons (Columbia University). 2. 286–297. 5 indexed citations

6.

Diao, Yixin, et al.. (2005). A control theory foundation for self-managing computing systems. IEEE Journal on Selected Areas in Communications. 23(12). 2213–2222. 65 indexed citations

7.

Laadan, Oren, Dan Phung, & Jason Nieh. (2005). Transparent Checkpoint-Restart of Distributed Applications on Commodity Clusters. 1–13. 25 indexed citations

8.

Diao, Yixin, Joseph L. Hellerstein, S. Parekh, et al.. (2005). Self-Managing Systems: A Control Theory Foundation. 23. 441–448. 66 indexed citations

9.

Phung, Dan, Giuseppe Valetto, Gail E. Kaiser, & Suhit Gupta. (2004). Optimizing Quality for Collaborative Video Viewing. Columbia Academic Commons (Columbia University). 1 indexed citations

10.

Tang, Akaysha C., et al.. (2002). Independent Components of Magnetoencephalography: Localization. Neural Computation. 14(8). 1827–1858. 79 indexed citations

11.

Tang, Akaysha C., et al.. (2000). Independent Components of Magnetoencephalography, Part I: Localization. 2 indexed citations

12.

Tang, Akaysha C., et al.. (2000). Localization of Independent Components from Magnetoencephalography. Maynooth University ePrints and eTheses Archive (Maynooth University). 7 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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