Michael Wilde

4.5k total citations · 1 hit paper
66 papers, 2.8k citations indexed

About

Michael Wilde is a scholar working on Computer Networks and Communications, Information Systems and Management and Information Systems. According to data from OpenAlex, Michael Wilde has authored 66 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Networks and Communications, 32 papers in Information Systems and Management and 18 papers in Information Systems. Recurrent topics in Michael Wilde's work include Distributed and Parallel Computing Systems (53 papers), Advanced Data Storage Technologies (33 papers) and Scientific Computing and Data Management (32 papers). Michael Wilde is often cited by papers focused on Distributed and Parallel Computing Systems (53 papers), Advanced Data Storage Technologies (33 papers) and Scientific Computing and Data Management (32 papers). Michael Wilde collaborates with scholars based in United States, Brazil and Canada. Michael Wilde's co-authors include Ian Foster, Yong Zhao, Justin M. Wozniak, Ben Clifford, Daniel S. Katz, Mihael Hategan, Sarah Kenny, Jeffrey R. Spies, Michael C. Neale and Timothy C. Bates and has published in prestigious journals such as Protein Science, Psychometrika and Environmental Modelling & Software.

In The Last Decade

Michael Wilde

66 papers receiving 2.6k citations

Hit Papers

OpenMx: An Open Source Extended Structural Equation Model... 2011 2026 2016 2021 2011 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Wilde United States 21 1.5k 1.2k 836 311 289 66 2.8k
D. Stott Parker United States 20 775 0.5× 70 0.1× 490 0.6× 102 0.3× 139 0.5× 83 2.1k
Vanessa Sochat United States 10 257 0.2× 278 0.2× 203 0.2× 105 0.3× 33 0.1× 32 1.6k
Paul Millar United Kingdom 15 633 0.4× 94 0.1× 238 0.3× 87 0.3× 251 0.9× 68 1.6k
Jin Chen China 23 211 0.1× 72 0.1× 74 0.1× 27 0.1× 95 0.3× 107 1.9k
Tara Madhyastha United States 24 347 0.2× 20 0.0× 117 0.1× 171 0.5× 183 0.6× 71 1.8k
Matthew Kay United States 26 73 0.0× 154 0.1× 158 0.2× 366 1.2× 69 0.2× 103 2.6k
Norma P. Simon Australia 27 98 0.1× 76 0.1× 735 0.9× 36 0.1× 32 0.1× 211 2.8k
Chia‐Chen Chang Taiwan 25 217 0.1× 39 0.0× 216 0.3× 87 0.3× 17 0.1× 98 2.1k
Michael Johnson Australia 14 199 0.1× 53 0.0× 70 0.1× 124 0.4× 11 0.0× 98 1.3k
Erik Linstead United States 24 165 0.1× 62 0.1× 746 0.9× 21 0.1× 4 0.0× 82 1.9k

Countries citing papers authored by Michael Wilde

Since Specialization
Citations

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

Fields of papers citing papers by Michael Wilde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Wilde

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Wilde. A scholar is included among the top collaborators of Michael Wilde 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 Michael Wilde. Michael Wilde 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
1.
Wilde, Michael, Muhammad Saad Yousuf, Jeffrey G. Jarvik, et al.. (2025). IGHG4 Expression in C2 Human Dorsal Root Ganglion Potentially Links B Cells to Spreading Chronic Neck Pain. Journal of Pain. 29. 105010–105010. 1 indexed citations
2.
Wilde, Michael, Ian Foster, Marta Mattoso, et al.. (2018). BioWorkbench: a high-performance framework for managing and analyzing bioinformatics experiments. PeerJ. 6. e5551–e5551. 8 indexed citations
3.
Zapol, Peter, Dmitry Karpeyev, Ketan Maheshwari, et al.. (2015). Coupled molecular-dynamics and first-principle transport calculations of metal/oxide/metal heterostructures. Bulletin of the American Physical Society. 2015. 1 indexed citations
4.
Armstrong, Timothy G., Justin M. Wozniak, Michael Wilde, & Ian Foster. (2014). Compiler Techniques for Massively Scalable Implicit Task Parallelism. 299–310. 32 indexed citations
5.
Wozniak, Justin M., Michael Wilde, & Ian Foster. (2014). Language Features for Scalable Distributed-Memory Dataflow Computing. 50–53. 7 indexed citations
6.
Montella, Raffaele, Alison Brizius, Joshua Elliott, et al.. (2014). FACE-IT: A Science Gateway for Food Security Research. CINECA IRIS Institutial research information system (Parthenope University of Naples). 42–46. 21 indexed citations
7.
Wozniak, Justin M., Tom Peterka, Timothy G. Armstrong, et al.. (2013). Dataflow coordination of data-parallel tasks via MPI 3.0. 1–6. 11 indexed citations
8.
Wozniak, Justin M., Timothy G. Armstrong, Ketan Maheshwari, et al.. (2013). Turbine: A Distributed-memory Dataflow Engine for High Performance Many-task Applications. Fundamenta Informaticae. 128(3). 337–366. 27 indexed citations
9.
Elliott, Joshua, David Kelly, Neil Best, et al.. (2013). The parallel system for integrating impact models and sectors (pSIMS). 1–8. 16 indexed citations
10.
Wozniak, Justin M., Michael Wilde, & Daniel S. Katz. (2013). JETS: Language and System Support for Many-Parallel-Task Workflows. Journal of Grid Computing. 11(3). 341–360. 1 indexed citations
11.
Wozniak, Justin M., Timothy G. Armstrong, Ketan Maheshwari, et al.. (2012). Turbine. 1–12. 17 indexed citations
12.
Zhang, Zhao, Daniel S. Katz, Matei Ripeanu, Michael Wilde, & Ian Foster. (2011). AME. 137–146. 11 indexed citations
13.
Boker, Steven M., Michael C. Neale, Hermine H. Maes, et al.. (2011). OpenMx: An Open Source Extended Structural Equation Modeling Framework. Psychometrika. 76(2). 306–317. 890 indexed citations breakdown →
14.
Hocky, Glen M., et al.. (2010). Protein structure prediction enhanced with evolutionary diversity: SPEED. Protein Science. 19(3). 520–534. 23 indexed citations
15.
Sulakhe, Dinanath, et al.. (2008). Interoperability of GADU in Using Heterogeneous Grid Resources for Bioinformatics Applications. IEEE Transactions on Information Technology in Biomedicine. 12(2). 241–246. 7 indexed citations
16.
Raicu, Ioan, Yong Zhao, Cătălin Dumitrescu, Ian Foster, & Michael Wilde. (2007). Falkon: A Proposal for Project Globus Incubation. 1 indexed citations
17.
Sulakhe, Dinanath, Álex Rodríguez, Mark D’Souza, et al.. (2005). Gnare: Automated System For High-Throughput Genome Analysis With Grid Computational Backend. Journal of Clinical Monitoring and Computing. 19(4-5). 361–369. 13 indexed citations
18.
Zhao, Yong, Michael Wilde, Ian Foster, et al.. (2005). Virtual data Grid middleware services for data‐intensive science. Concurrency and Computation Practice and Experience. 18(6). 595–608. 14 indexed citations
19.
Foster, Ian, et al.. (2003). The Virtual Data Grid: A New Model and Architecture for Data-Intensive Collaboration.. Conference on Innovative Data Systems Research. 75 indexed citations
20.
Annis, James, et al.. (2002). Applying Chimera Virtual Data Concepts to Cluster Finding in the Sloan Sky Survey. Conference on High Performance Computing (Supercomputing). 1–14. 53 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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