Vernon Austel

495 total citations
11 papers, 256 citations indexed

About

Vernon Austel is a scholar working on Artificial Intelligence, Hardware and Architecture and Computer Networks and Communications. According to data from OpenAlex, Vernon Austel has authored 11 papers receiving a total of 256 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Hardware and Architecture and 3 papers in Computer Networks and Communications. Recurrent topics in Vernon Austel's work include Neural Networks and Applications (4 papers), Parallel Computing and Optimization Techniques (3 papers) and Speech Recognition and Synthesis (3 papers). Vernon Austel is often cited by papers focused on Neural Networks and Applications (4 papers), Parallel Computing and Optimization Techniques (3 papers) and Speech Recognition and Synthesis (3 papers). Vernon Austel collaborates with scholars based in United States, Austria and United Kingdom. Vernon Austel's co-authors include John A. Gunnels, Sean W. Smith, I‐Hsin Chung, Brian Kingsbury, Bhuvana Ramabhadran, Tara N. Sainath, Paul A. Karger, Erik W. Draeger, Bronis R. de Supinski and James C. Sexton and has published in prestigious journals such as Nature Communications, IEEE Transactions on Parallel and Distributed Systems and ACM Transactions on Mathematical Software.

In The Last Decade

Vernon Austel

11 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vernon Austel United States	9	91	74	70	37	37	11	256
Jack Purdum United States	4	50 0.5×	127 1.7×	118 1.7×	63 1.7×	32 0.9×	9	324
H. Schröder Germany	11	69 0.8×	71 1.0×	60 0.9×	117 3.2×	58 1.6×	60	323
Arthur Trew United Kingdom	10	51 0.6×	96 1.3×	39 0.6×	15 0.4×	11 0.3×	39	294
Che–Rung Lee Taiwan	10	47 0.5×	131 1.8×	75 1.1×	60 1.6×	32 0.9×	54	298
Yong Sun China	12	123 1.4×	107 1.4×	58 0.8×	11 0.3×	15 0.4×	43	402
Hasitha Muthumala Waidyasooriya Japan	10	135 1.5×	86 1.2×	126 1.8×	38 1.0×	13 0.4×	42	303
José M. Badía Spain	8	27 0.3×	31 0.4×	31 0.4×	27 0.7×	42 1.1×	40	175
K. Torki France	10	74 0.8×	67 0.9×	29 0.4×	81 2.2×	17 0.5×	40	270
Marat Dukhan United States	7	125 1.4×	67 0.9×	82 1.2×	147 4.0×	8 0.2×	8	266

Countries citing papers authored by Vernon Austel

Since Specialization

Citations

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

Fields of papers citing papers by Vernon Austel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vernon Austel

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

11 of 11 papers shown

1.

Abdelaziz, Ibrahim, Asim Munawar, Vernon Austel, et al.. (2024). API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs. 12859–12870. 3 indexed citations

2.

Dash, Sanjeeb, Vernon Austel, Tyler R. Josephson, et al.. (2023). Combining data and theory for derivable scientific discovery with AI-Descartes. Nature Communications. 14(1). 1777–1777. 39 indexed citations

3.

Zee, Field G., Tyler Smith, Bryan Marker, et al.. (2016). The BLIS Framework. ACM Transactions on Mathematical Software. 42(2). 1–19. 51 indexed citations

4.

Chung, I‐Hsin, Tara N. Sainath, Bhuvana Ramabhadran, et al.. (2016). Parallel Deep Neural Network Training for Big Data on Blue Gene/Q. IEEE Transactions on Parallel and Distributed Systems. 28(6). 1703–1714. 28 indexed citations

5.

Chung, I‐Hsin, Tara N. Sainath, Bhuvana Ramabhadran, et al.. (2014). Parallel Deep Neural Network Training for Big Data on Blue Gene/Q. 745–753. 19 indexed citations

6.

Sainath, Tara N., I‐Hsin Chung, Bhuvana Ramabhadran, et al.. (2014). Parallel deep neural network training for LVCSR tasks using blue gene/Q. 1048–1052. 6 indexed citations

7.

Gygi, François, Christoph W. Ueberhuber, Erik W. Draeger, et al.. (2006). Gordon Bell finalists I---Large-scale electronic structure calculations of high-Z metals on the BlueGene/L platform. 45–45. 50 indexed citations

8.

Akiba, Hiroshi, Manish Gupta, John A. Gunnels, et al.. (2006). Gordon Bell finalists I---Large scale drop impact analysis of mobile phone using ADVC on Blue Gene/L. 46–46. 23 indexed citations

9.

Schellhorn, Gerhard, et al.. (2002). Verified formal security models for multiapplicative smart cards1. Journal of Computer Security. 10(4). 339–367. 8 indexed citations

10.

Karger, Paul A., et al.. (2000). A New Mandatory Security Policy Combining Secrecy and Integrity. 11 indexed citations

11.

Smith, Sean W. & Vernon Austel. (1998). Trusting trusted hardware: towards a formal model for programmable secure coprocessors. 8–8. 18 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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