Chee-Yee Chong

2.9k total citations
92 papers, 2.0k citations indexed

About

Chee-Yee Chong is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Chee-Yee Chong has authored 92 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Artificial Intelligence, 37 papers in Computer Networks and Communications and 21 papers in Control and Systems Engineering. Recurrent topics in Chee-Yee Chong's work include Target Tracking and Data Fusion in Sensor Networks (66 papers), Distributed Sensor Networks and Detection Algorithms (33 papers) and Fault Detection and Control Systems (13 papers). Chee-Yee Chong is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (66 papers), Distributed Sensor Networks and Detection Algorithms (33 papers) and Fault Detection and Control Systems (13 papers). Chee-Yee Chong collaborates with scholars based in United States, Sweden and Canada. Chee-Yee Chong's co-authors include Kuo‐Chu Chang, Shozo Mori, Roland P. Malhamé, Shintaro Mori, William H. Barker, A. Debs, Michael Athans, Yaakov Bar‐Shalom, Rocky K. C. Chang and Wolfgang Koch and has published in prestigious journals such as IEEE Transactions on Automatic Control, Proceedings of the IEEE and Automatica.

In The Last Decade

Chee-Yee Chong

85 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chee-Yee Chong United States 24 1.1k 746 710 565 261 92 2.0k
Minghui Zhu United States 24 764 0.7× 1.3k 1.7× 1.9k 2.7× 565 1.0× 152 0.6× 110 3.2k
Peng Li China 29 542 0.5× 1.2k 1.7× 699 1.0× 1.1k 1.9× 229 0.9× 162 3.0k
Stelios C. A. Thomopoulos United States 19 1.1k 1.0× 492 0.7× 1.1k 1.5× 494 0.9× 315 1.2× 169 1.9k
Samrat L. Sabat India 21 548 0.5× 192 0.3× 550 0.8× 672 1.2× 346 1.3× 109 1.7k
Andrea Simonetto Netherlands 21 611 0.6× 299 0.4× 568 0.8× 486 0.9× 119 0.5× 76 1.6k
Rui Mendes Portugal 12 2.6k 2.4× 726 1.0× 261 0.4× 370 0.7× 100 0.4× 24 3.5k
A.G. Parlos United States 25 726 0.7× 1.2k 1.6× 143 0.2× 674 1.2× 191 0.7× 96 2.2k
Yan Liang China 25 1.3k 1.2× 1.0k 1.4× 700 1.0× 334 0.6× 546 2.1× 232 2.3k
Michel Kieffer France 19 484 0.4× 911 1.2× 412 0.6× 369 0.7× 249 1.0× 146 2.0k

Countries citing papers authored by Chee-Yee Chong

Since Specialization
Citations

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

Fields of papers citing papers by Chee-Yee Chong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee-Yee Chong. 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 Chee-Yee Chong. The network helps show where Chee-Yee Chong may publish in the future.

Co-authorship network of co-authors of Chee-Yee Chong

This figure shows the co-authorship network connecting the top 25 collaborators of Chee-Yee Chong. A scholar is included among the top collaborators of Chee-Yee Chong 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 Chee-Yee Chong. Chee-Yee Chong 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.
Bar‐Shalom, Yaakov, et al.. (2022). Estimation for a Feedback System With a Desired Final State and Intermittent Stochastic Inputs. IEEE Transactions on Aerospace and Electronic Systems. 58(6). 5351–5360.
2.
Chong, Chee-Yee, Kuo‐Chu Chang, & Shozo Mori. (2018). A Review of Forty Years of Distributed Estimation. 1–8. 18 indexed citations
3.
Chong, Chee-Yee, Shozo Mori, Felix Govaers, & Wolfgang Koch. (2014). Comparison of tracklet fusion and distributed Kalman filter for track fusion. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 1–8. 15 indexed citations
4.
Chong, Chee-Yee & Shozo Mori. (2013). Optimal fusion for non-zero process noise. International Conference on Information Fusion. 365–371. 10 indexed citations
5.
Mori, Shozo & Chee-Yee Chong. (2013). Performance analysis of graph-based track stitching. International Conference on Information Fusion. 196–203. 9 indexed citations
6.
Mori, Shozo, Kuo‐Chu Chang, & Chee-Yee Chong. (2012). Comparison of track fusion rules and track association metrics. International Conference on Information Fusion. 1996–2003. 24 indexed citations
7.
Chong, Chee-Yee. (2012). Graph approaches for data association. International Conference on Information Fusion. 1578–1585. 17 indexed citations
8.
Chang, Rocky K. C., Chee-Yee Chong, & Shozo Mori. (2010). Analytical and Computational Evaluation of Scalable Distributed Fusion Algorithms. IEEE Transactions on Aerospace and Electronic Systems. 46(4). 2022–2034. 54 indexed citations
9.
Chong, Chee-Yee, et al.. (2009). Efficient multiple hypothesis tracking by track segment graph. International Conference on Information Fusion. 2177–2184. 30 indexed citations
10.
Mori, Shozo, Chee-Yee Chong, & Kuo‐Chu Chang. (2009). Track association and fusion using Janossy measure density functions. 1634–1641. 2 indexed citations
11.
Chang, Kuo‐Chu, Chee-Yee Chong, & Shuji Mori. (2008). On scalable distributed sensor fusion. International Conference on Information Fusion. 1–8. 12 indexed citations
12.
Mori, Shintaro, et al.. (2008). Continuous-time interacting multiple model extrapolation. International Conference on Information Fusion. 1–8. 3 indexed citations
13.
Pravia, Marco A., R. Prasanth, P.O. Arambel, Candace L. Sidner, & Chee-Yee Chong. (2008). Generation of a fundamental data set for hard/soft information fusion. International Conference on Information Fusion. 1–8. 33 indexed citations
14.
Fortunato, Evan M., et al.. (2007). Generalized Murty's algorithm with application to multiple hypothesis tracking. 1–8. 14 indexed citations
15.
Mori, Shozo, William H. Barker, Chee-Yee Chong, & Kuo‐Chu Chang. (2002). Track association and track fusion with nondeterministic target dynamics. IEEE Transactions on Aerospace and Electronic Systems. 38(2). 659–668. 86 indexed citations
16.
Hill, David J. & Chee-Yee Chong. (1989). Lyapunov functions of lur'e-postnikov form for structure preserving models of power systems. Automatica. 25(3). 453–460. 30 indexed citations
17.
Mori, Shozo, Kuo‐Chu Chang, & Chee-Yee Chong. (1987). Tracking Aircraft by Acoustic Sensors; Multiple Hypothesis Approach Applied to Possibly Unresolved Measurements. American Control Conference. 24(24). 1099–1105. 13 indexed citations
18.
Chong, Chee-Yee, Kuo‐Chu Chang, & Shozo Mori. (1987). Tracking Multiple Air Tragets with Distributed Acoustic Sensors. American Control Conference. 24(24). 1831–1836. 4 indexed citations
19.
Chong, Chee-Yee, et al.. (1984). Statistical Synthesis of Physically Based Load Models with Applications to Cold Load Pickup. IEEE Power Engineering Review. PER-4(7). 33–33. 5 indexed citations
20.
Chong, Chee-Yee & Michael Athans. (1976). On the periodic coordination of linear stochastic systems. Automatica. 12(4). 321–335. 24 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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