Robert Fung

753 total citations
11 papers, 231 citations indexed

About

Robert Fung is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing. According to data from OpenAlex, Robert Fung has authored 11 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Management Science and Operations Research and 4 papers in Signal Processing. Recurrent topics in Robert Fung's work include Bayesian Modeling and Causal Inference (9 papers), Data Quality and Management (4 papers) and Data Management and Algorithms (4 papers). Robert Fung is often cited by papers focused on Bayesian Modeling and Causal Inference (9 papers), Data Quality and Management (4 papers) and Data Management and Algorithms (4 papers). Robert Fung collaborates with scholars based in United States. Robert Fung's co-authors include Stuart L. Crawford, Kuo‐Chu Chang, Steven R. Bratt, James Z. Wang, Cris Kobryn, Jeffrey W. Given, Thomas C. Bache, Richard M. Tong, Noah S. Friedland and Robert B. Washburn and has published in prestigious journals such as Communications of the ACM, Bulletin of the Seismological Society of America and Statistics and Computing.

In The Last Decade

Robert Fung

11 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robert Fung United States	8	182	49	46	43	37	11	231
Kai Sheng Tai United States	4	94 0.5×	26 0.5×	9 0.2×	51 1.2×	6 0.2×	5	123
Liang Yuan China	8	63 0.3×	13 0.3×	44 1.0×	10 0.2×	5 0.1×	30	225
Kenneth J. Laskey United States	8	93 0.5×	24 0.5×	45 1.0×		20 0.5×	13	194
Dustin Kempton United States	10	110 0.6×	98 2.0×	37 0.8×	2 0.0×	27 0.7×	24	255
Thomas Bernecker Germany	6	62 0.3×	207 4.2×	154 3.3×	5 0.1×	19 0.5×	18	280
Nistor Grozavu France	9	191 1.0×	18 0.4×	32 0.7×	9 0.2×	9 0.2×	33	225
Paulo Gonçalvés France	9	211 1.2×	45 0.9×	24 0.5×	3 0.1×	29 0.8×	20	290
Nader Shakibay Senobari United States	7	196 1.1×	205 4.2×	15 0.3×	52 1.2×	6 0.2×	14	296
Michael A. Schuh United States	8	99 0.5×	84 1.7×	37 0.8×	1 0.0×	23 0.6×	21	234

Countries citing papers authored by Robert Fung

Since Specialization

Citations

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

Fields of papers citing papers by Robert Fung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Fung

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

All Works

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11 of 11 papers shown

1.

Chang, Kuo‐Chu & Robert Fung. (2013). Refinement and Coarsening of Bayesian Networks. arXiv (Cornell University). 435–446. 4 indexed citations

2.

Washburn, Robert B., et al.. (1996). <title>Search algorithms for model-based SAR ATR</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2757. 279–293. 12 indexed citations

3.

Chang, Kuo‐Chu & Robert Fung. (1995). Symbolic probabilistic inference with both discrete and continuous variables. IEEE Transactions on Systems Man and Cybernetics. 25(6). 910–916. 12 indexed citations

4.

Fung, Robert, et al.. (1995). Applying Bayesian networks to information retrieval. Communications of the ACM. 38(3). 42–42. 61 indexed citations

5.

Fung, Robert, et al.. (1993). Bayesian Inference with Node Aggregation for Information Retrieval.. Text REtrieval Conference. 151–161. 2 indexed citations

6.

Crawford, Stuart L. & Robert Fung. (1992). An analysis of two probabilistic model induction techniques. Statistics and Computing. 2(2). 83–90. 9 indexed citations

7.

Fung, Robert & Stuart L. Crawford. (1990). Constructor: a system for the induction of probabilistic models. National Conference on Artificial Intelligence. 762–769. 38 indexed citations

8.

Bache, Thomas C., Steven R. Bratt, James Z. Wang, et al.. (1990). The Intelligent Monitoring System. Bulletin of the Seismological Society of America. 80(6B). 1833–1851. 59 indexed citations

9.

Chang, Kuo‐Chu & Robert Fung. (1989). Node aggregation for distributed inference in Bayesian networks. International Joint Conference on Artificial Intelligence. 265–270. 9 indexed citations

10.

Fung, Robert, et al.. (1989). An architecture for probabilistic concept-based information retrieval. 455–467. 24 indexed citations

11.

Tse, Edison & Robert Fung. (1988). Structure composing for situation assessment. 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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