Chung-Ching Chang

818 total citations
9 papers, 66 citations indexed

About

Chung-Ching Chang is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chung-Ching Chang has authored 9 papers receiving a total of 66 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Control and Systems Engineering, 5 papers in Electrical and Electronic Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chung-Ching Chang's work include Islanding Detection in Power Systems (3 papers), Video Surveillance and Tracking Methods (3 papers) and Microgrid Control and Optimization (3 papers). Chung-Ching Chang is often cited by papers focused on Islanding Detection in Power Systems (3 papers), Video Surveillance and Tracking Methods (3 papers) and Microgrid Control and Optimization (3 papers). Chung-Ching Chang collaborates with scholars based in United States and Netherlands. Chung-Ching Chang's co-authors include Sanjay Lall, Dimitry Gorinevsky, Hamid Aghajan, Hamid Aghajan, Eric Glover, Zoran Živković, Richard Kleihorst, Isaac Noble, Cícero Nogueira dos Santos and James Lee-Thorp and has published in prestigious journals such as IEEE Transactions on Power Systems and IEEE Transactions on Smart Grid.

In The Last Decade

Chung-Ching Chang

9 papers receiving 66 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chung-Ching Chang United States	5	51	43	8	5	5	9	66
Huiye Liu China	4	14 0.3×	46 1.1×	2 0.3×	13 2.6×	2 0.4×	10	66
P. Hestnes United States	4	28 0.5×	11 0.3×	3 0.4×	8 1.6×		7	54
Sergiy Popovych United States	4	7 0.1×	28 0.7×	4 0.5×	6 1.2×		7	55
Inesc Porto Portugal	3	28 0.5×	39 0.9×	1 0.1×	11 2.2×	3 0.6×	6	53
G. Brunello United States	5	74 1.5×	84 2.0×	1 0.1×	15 3.0×	2 0.4×	7	91
K. Chandram India	10	52 1.0×	301 7.0×	3 0.4×	2 0.4×	16 3.2×	33	312
Ron Brandl Germany	6	118 2.3×	113 2.6×		4 0.8×	2 0.4×	12	135
H. Al-Bataineh United States	2	17 0.3×	21 0.5×	4 0.5×	28 5.6×		4	51
C. Fu China	3	18 0.4×	34 0.8×		3 0.6×	1 0.2×	9	41
X. Zhu China	5	14 0.3×	16 0.4×	2 0.3×	1 0.2×	5 1.0×	7	41

Countries citing papers authored by Chung-Ching Chang

Since Specialization

Citations

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

Fields of papers citing papers by Chung-Ching Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung-Ching Chang. 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 Chung-Ching Chang. The network helps show where Chung-Ching Chang may publish in the future.

Co-authorship network of co-authors of Chung-Ching Chang

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

9 of 9 papers shown

1.

Santos, Cícero Nogueira dos, James Lee-Thorp, Isaac Noble, Chung-Ching Chang, & David Uthus. (2024). Memory Augmented Language Models through Mixture of Word Experts. 4425–4438. 2 indexed citations

2.

Chang, Chung-Ching, Dimitry Gorinevsky, & Sanjay Lall. (2015). Stability Analysis of Distributed Power Generation With Droop Inverters. IEEE Transactions on Power Systems. 30(6). 3295–3303. 19 indexed citations

3.

Chang, Chung-Ching, Dimitry Gorinevsky, & Sanjay Lall. (2014). Dynamical and Voltage Profile Stability of Inverter-Connected Distributed Power Generation. IEEE Transactions on Smart Grid. 5(4). 2093–2105. 19 indexed citations

4.

Glover, Eric, Chung-Ching Chang, Dimitry Gorinevsky, & Sanjay Lall. (2012). Frequency stability for distributed generation connected through grid-tie inverter. 1547. 1–6. 3 indexed citations

5.

Chang, Chung-Ching & Sanjay Lall. (2011). An explicit solution for optimal two-player decentralized control over TCP erasure channels with state feedback. 4717–4722. 5 indexed citations

6.

Chang, Chung-Ching & Sanjay Lall. (2011). Synthesis for optimal two-player decentralized control over TCP erasure channels with state feedback. 3824–3829. 4 indexed citations

7.

Živković, Zoran, et al.. (2008). Toward low latency gesture control using smart camera network. 1–8. 8 indexed citations

8.

Chang, Chung-Ching & Hamid Aghajan. (2007). A LQR spatiotemporal fusion technique for face profile collection in smart camera surveillance. 7. 365–370. 2 indexed citations

9.

Chang, Chung-Ching & Hamid Aghajan. (2007). Linear Dynamic Data Fusion Techniques for Face Orientation Estimation in Smart Camera Networks. 3. 44–51. 4 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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