John Burge

680 total citations
14 papers, 266 citations indexed

About

John Burge is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, John Burge has authored 14 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Signal Processing and 2 papers in Computer Networks and Communications. Recurrent topics in John Burge's work include Bayesian Modeling and Causal Inference (3 papers), Machine Learning in Healthcare (2 papers) and Seismology and Earthquake Studies (2 papers). John Burge is often cited by papers focused on Bayesian Modeling and Causal Inference (3 papers), Machine Learning in Healthcare (2 papers) and Seismology and Earthquake Studies (2 papers). John Burge collaborates with scholars based in United States, Canada and Iran. John Burge's co-authors include Terran Lane, Frederick Hayes‐Roth, Carl A. Sunshine, Cathleen Stasz, Stephanie Forrest, Anil Somayaji, Shibin Qiu, Vincent P. Clark, Godfrey D. Pearlson and Vince D. Calhoun and has published in prestigious journals such as NeuroImage, Human Brain Mapping and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).

In The Last Decade

John Burge

11 papers receiving 246 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Burge United States	8	113	84	67	45	32	14	266
Diego Peteiro-Barral Spain	8	150 1.3×	55 0.7×	25 0.4×	21 0.5×	26 0.8×	15	296
Abhijit S. Pandya United States	8	103 0.9×	31 0.4×	42 0.6×	20 0.4×	33 1.0×	62	322
Tuomo Sipola Finland	9	104 0.9×	79 0.9×	45 0.7×	44 1.0×	8 0.3×	24	251
Xintao Ding China	12	81 0.7×	37 0.4×	59 0.9×	31 0.7×	44 1.4×	35	339
Deepti Gupta United States	11	163 1.4×	186 2.2×	29 0.4×	157 3.5×	15 0.5×	40	446
Vandana Bhattacharjee India	10	84 0.7×	40 0.5×	44 0.7×	28 0.6×	18 0.6×	37	349
G S Pradeep Ghantasala India	10	126 1.1×	70 0.8×	45 0.7×	8 0.2×	25 0.8×	63	322
Mitra Mirzarezaee Iran	10	73 0.6×	19 0.2×	70 1.0×	11 0.2×	16 0.5×	36	280
Yu Wen China	7	168 1.5×	169 2.0×	22 0.3×	79 1.8×	15 0.5×	12	326
Ito Wasito Indonesia	9	123 1.1×	13 0.2×	36 0.5×	33 0.7×	18 0.6×	47	328

Countries citing papers authored by John Burge

Since Specialization

Citations

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

Fields of papers citing papers by John Burge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Burge

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

All Works

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14 of 14 papers shown

1.

Burge, John, et al.. (2023). Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior. Fire Technology. 59(6). 3327–3354. 12 indexed citations

2.

Burge, John, et al.. (2008). Hybrid ICA–Bayesian network approach reveals distinct effective connectivity differences in schizophrenia. NeuroImage. 42(4). 1560–1568. 46 indexed citations

3.

Burge, John, et al.. (2007). Discrete dynamic Bayesian network analysis of fMRI data. Human Brain Mapping. 30(1). 122–137. 43 indexed citations

4.

Lane, Terran & John Burge. (2007). Learning bayesian networks from hierarchically related data with a neuroimaging application.

5.

Somayaji, Anil, et al.. (2006). Learning DFA representations of HTTP for protecting web applications. Computer Networks. 51(5). 1239–1255. 53 indexed citations

6.

Burge, John & Frederick Hayes‐Roth. (2005). A novel pattern learning and classification procedure applied to the learning of vowels. 1. 154–157. 1 indexed citations

7.

Burge, John & Terran Lane. (2005). Learning class-discriminative dynamic Bayesian networks. 97–104. 9 indexed citations

8.

Şendur, Polat, et al.. (2004). DEVELOPMENT & VALIDATION OF A GENERIC 3-D VEHICLE MODEL & GUI FOR STUDYING THE HANDLING PERFORMANCE. 1 indexed citations

9.

Packer, James E. & John Burge. (2003). Templum Divi Traiani Parthici et Plotinae: a debate with R. Meneghini. Journal of Roman Archaeology. 16. 108–136. 2 indexed citations

10.

Burge, John, et al.. (2002). V-Lab-a virtual laboratory for autonomous agents-SLA-based learning controllers. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 32(6). 791–803. 20 indexed citations

11.

Burge, John, et al.. (2001). Virtual Environment for Transportation Data Management System. Transportation Research Record Journal of the Transportation Research Board. 1764(1). 164–175.

12.

Hayes‐Roth, Frederick, et al.. (1988). Network Structures for Distributed Situation Assessment. Elsevier eBooks. 71–89. 7 indexed citations

13.

Hayes‐Roth, Frederick, et al.. (1981). Network Structures for Distributed Situation Assessment. IEEE Transactions on Systems Man and Cybernetics. 11(1). 5–23. 69 indexed citations

14.

Klahr, Philip, et al.. (1978). Machine methods for acquiring, learning, and applying knowledge. RAND Corporation eBooks. 3 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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