Christopher T. Symons

634 total citations
23 papers, 345 citations indexed

About

Christopher T. Symons is a scholar working on Artificial Intelligence, Computer Networks and Communications and Molecular Biology. According to data from OpenAlex, Christopher T. Symons has authored 23 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Computer Networks and Communications and 3 papers in Molecular Biology. Recurrent topics in Christopher T. Symons's work include Electron and X-Ray Spectroscopy Techniques (3 papers), Advanced Graph Theory Research (3 papers) and Machine Learning in Materials Science (2 papers). Christopher T. Symons is often cited by papers focused on Electron and X-Ray Spectroscopy Techniques (3 papers), Advanced Graph Theory Research (3 papers) and Machine Learning in Materials Science (2 papers). Christopher T. Symons collaborates with scholars based in United States, Sweden and Lebanon. Christopher T. Symons's co-authors include Michael A. Langston, Faisal N. Abu-Khzam, R. Lorraine Collins, Justin M. Beaver, Michael R. Fellows, Ranga Raju Vatsavai, Stephen Jesse, Alex Belianinov, Chad A. Steed and Richard Archibald and has published in prestigious journals such as SHILAP Revista de lepidopterología, Algorithmica and Microscopy and Microanalysis.

In The Last Decade

Christopher T. Symons

21 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher T. Symons United States 11 84 82 79 61 52 23 345
Tsutomu Kawabata Japan 12 41 0.5× 82 1.0× 69 0.9× 179 2.9× 15 0.3× 60 463
Peter Ronhovde United States 6 29 0.3× 89 1.1× 52 0.7× 56 0.9× 17 0.3× 11 410
Amos Waterland United States 9 15 0.2× 52 0.6× 212 2.7× 66 1.1× 17 0.3× 17 350
R.S. Indeck United States 11 58 0.7× 99 1.2× 123 1.6× 24 0.4× 147 2.8× 43 384
Wei-Cheng Hsu Taiwan 8 98 1.2× 109 1.3× 124 1.6× 28 0.5× 20 0.4× 22 380
Chi-Huan Tung United States 10 34 0.4× 59 0.7× 119 1.5× 96 1.6× 20 0.4× 38 327
A. Yu. Romanov Russia 11 23 0.3× 31 0.4× 130 1.6× 23 0.4× 33 0.6× 77 337
Norman W. Johnson United States 10 73 0.9× 68 0.8× 15 0.2× 111 1.8× 10 0.2× 16 552

Countries citing papers authored by Christopher T. Symons

Since Specialization
Citations

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

Fields of papers citing papers by Christopher T. Symons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher T. Symons

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher T. Symons. A scholar is included among the top collaborators of Christopher T. Symons 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 Christopher T. Symons. Christopher T. Symons 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.
Bucher, Amy, et al.. (2024). How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review. SHILAP Revista de lepidopterología. 2(3). 375–404. 10 indexed citations
2.
Symons, Christopher T., et al.. (2022). Persona-Based Conversational AI: State of the Art and Challenges. 993–1001. 5 indexed citations
3.
Jesse, Stephen, Miaofang Chi, Albina Y. Borisevich, et al.. (2016). Using Multivariate Analysis of Scanning-Rochigram Data to Reveal Material Functionality. Microscopy and Microanalysis. 22(S3). 292–293. 1 indexed citations
4.
Idrobo, Juan Carlos, Ján Rusz, Michael A. McGuire, et al.. (2016). Mapping Magnetic Ordering With Aberrated Electron Probes in STEM. Microscopy and Microanalysis. 22(S3). 1676–1677. 1 indexed citations
5.
Lingerfelt, Eric J., Alex Belianinov, Eirik Endeve, et al.. (2016). BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. Procedia Computer Science. 80. 2276–2280. 13 indexed citations
6.
Idrobo, Juan Carlos, Ján Rusz, Michael A. McGuire, et al.. (2016). Detecting magnetic ordering with atomic size electron probes. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2(1). 34 indexed citations
7.
Belianinov, Alex, Rama K. Vasudevan, Evgheni Strelcov, et al.. (2015). Big data and deep data in scanning and electron microscopies: deriving functionality from multidimensional data sets. PubMed. 1(1). 6–6. 86 indexed citations
8.
Patton, Robert M., et al.. (2012). A Text Analysis Approach to Motivate Knowledge Sharing via Microsoft SharePoint. 1. 3670–3678. 3 indexed citations
9.
Symons, Christopher T. & Justin M. Beaver. (2012). Nonparametric semi-supervised learning for network intrusion detection. 49–58. 17 indexed citations
10.
Vatsavai, Ranga Raju, Christopher T. Symons, Varun Chandola, & Goo Jun. (2011). GX-Means: A model-based divide and merge algorithm for geospatial image clustering. Procedia Computer Science. 4. 186–195. 10 indexed citations
11.
Symons, Christopher T., et al.. (2011). Multi-View Budgeted Learning under Label and Feature Constraints Using Label-Guided Graph-Based Regularization. 1 indexed citations
12.
Steed, Chad A., et al.. (2011). Guided text analysis using adaptive visual analytics. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8294. 829408–829408. 4 indexed citations
13.
Pullum, Laura & Christopher T. Symons. (2011). Failure Analysis of a Complex Learning Framework Incorporating Multi-modal and Semi-supervised Learning. 1. 308–313. 1 indexed citations
14.
15.
Pullum, Laura, et al.. (2010). Architecture-level dependability analysis of a medical decision support system. 83–88. 2 indexed citations
16.
Symons, Christopher T., Nagiza F. Samatova, Byung Park, et al.. (2006). Multi-Criterion Active Learning in Conditional Random Fields. 12 indexed citations
17.
Abu-Khzam, Faisal N., et al.. (2006). Scalable Parallel Algorithms for FPT Problems. Algorithmica. 45(3). 269–284. 44 indexed citations
18.
Samatova, Nagiza F., Christopher T. Symons, David Buttler, et al.. (2005). Information Extraction from Unstructured Text for the Biodefense Knowledge Center. University of North Texas Digital Library (University of North Texas).
19.
Baldwin, Nicole, R. Lorraine Collins, Michael A. Langston, et al.. (2004). High performance computational tools for motif discovery. 122. 192–199. 15 indexed citations
20.
Abu-Khzam, Faisal N., et al.. (2004). Kernelization Algorithms for the Vertex Cover Problem: Theory and Experiments.. 62–69. 69 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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