John T. Daly

724 total citations
14 papers, 418 citations indexed

About

John T. Daly is a scholar working on Computer Networks and Communications, Information Systems and Electrical and Electronic Engineering. According to data from OpenAlex, John T. Daly has authored 14 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Networks and Communications, 3 papers in Information Systems and 3 papers in Electrical and Electronic Engineering. Recurrent topics in John T. Daly's work include Distributed systems and fault tolerance (9 papers), Cloud Computing and Resource Management (3 papers) and Software Reliability and Analysis Research (2 papers). John T. Daly is often cited by papers focused on Distributed systems and fault tolerance (9 papers), Cloud Computing and Resource Management (3 papers) and Software Reliability and Analysis Research (2 papers). John T. Daly collaborates with scholars based in United States. John T. Daly's co-authors include Nathan DeBardeleben, William M. Jones, Helen B. Daly, Sarah Michalak, Patricia J. Teller, J. E. Meyer, Seetharami Seelam, Andrew G. Moore, Ron A. Oldfield and Rolf Riesen and has published in prestigious journals such as Journal of Experimental Psychology General, Transactions of the American Mathematical Society and Future Generation Computer Systems.

In The Last Decade

John T. Daly

13 papers receiving 389 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John T. Daly United States 7 360 187 153 91 13 14 418
Berkin Özıṣıkyılmaz United States 11 257 0.7× 253 1.4× 83 0.5× 101 1.1× 6 0.5× 11 382
Gábor Dózsa Hungary 9 269 0.7× 228 1.2× 58 0.4× 17 0.2× 3 0.2× 22 301
Tammo Spalink United States 7 461 1.3× 114 0.6× 110 0.7× 29 0.3× 4 0.3× 17 495
Tim Levin United States 10 151 0.4× 79 0.4× 122 0.8× 49 0.5× 4 0.3× 27 262
Maged Michael United States 5 406 1.1× 261 1.4× 71 0.5× 26 0.3× 10 0.8× 6 440
Damian Dechev United States 9 217 0.6× 137 0.7× 50 0.3× 27 0.3× 5 0.4× 68 268
Wei-Yu Chen United States 10 319 0.9× 295 1.6× 90 0.6× 34 0.4× 3 0.2× 18 458
Giuliana Santos Veronese Portugal 7 393 1.1× 33 0.2× 227 1.5× 53 0.6× 12 0.9× 14 446
Luke Yen United States 11 823 2.3× 703 3.8× 32 0.2× 83 0.9× 8 0.6× 17 839
Matthias Wiesmann Switzerland 6 359 1.0× 48 0.3× 118 0.8× 13 0.1× 3 0.2× 17 374

Countries citing papers authored by John T. Daly

Since Specialization
Citations

This map shows the geographic impact of John T. Daly'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 John T. Daly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Daly more than expected).

Fields of papers citing papers by John T. Daly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John T. Daly. 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 John T. Daly. The network helps show where John T. Daly may publish in the future.

Co-authorship network of co-authors of John T. Daly

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

All Works

14 of 14 papers shown
1.
Daly, John T., et al.. (2024). Solving Boltzmann optimization problems with deep learning. 1(1).
2.
Moore, Andrew G., et al.. (2023). Design of General Purpose Minimal-Auxiliary Ising Machines. 17. 1–10. 2 indexed citations
3.
4.
Jones, William M., John T. Daly, & Nathan DeBardeleben. (2012). Application monitoring and checkpointing in HPC. 262–267. 15 indexed citations
5.
Jones, William M., John T. Daly, & Nathan DeBardeleben. (2010). Impact of sub-optimal checkpoint intervals on application efficiency in computational clusters. 276–279. 21 indexed citations
6.
Daly, John T., et al.. (2009). Propitious Checkpoint Intervals to Improve System Performance. scholarworks - UTEP (The University of Texas at El Paso). 1 indexed citations
7.
Jones, William M., John T. Daly, & Nathan DeBardeleben. (2008). Application Resilience: Making Progress in Spite of Failure. 34. 789–794. 9 indexed citations
8.
Daly, John T., et al.. (2008). Opportunistic Checkpoint Intervals to Improve System Performance. scholarworks - UTEP (The University of Texas at El Paso). 3 indexed citations
9.
10.
11.
Daly, John T.. (2004). A higher order estimate of the optimum checkpoint interval for restart dumps. Future Generation Computer Systems. 22(3). 303–312. 321 indexed citations
12.
Daly, Helen B. & John T. Daly. (1982). A mathematical model of reward and aversive nonreward: Its application in over 30 appetitive learning situations.. Journal of Experimental Psychology General. 111(4). 441–480. 19 indexed citations
13.
Daly, John T., et al.. (1976). A Banach Algebra of Functions With Bounded nth Differences. Transactions of the American Mathematical Society. 223. 279–279. 1 indexed citations
14.
Daly, John T.. (1971). On Liouville F-Algebras. Studia Mathematica. 40(1). 1–16. 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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