Hung Hung

5.8k citations
117 papers · 3.1k · h-index 28

Impact in

Papers in

Hung Hung

113 papers receiving 2.9k citations

Peers

Hung Hung
Comparison fields: 5 of 173
  • Statistics and Probability 1.6k
  • Management Science and Operations Research 658
  • Statistics, Probability and Uncertainty 328
  • Computational Mathematics 24
  • Signal Processing 428
Replace Noah Simon with:
Noah Simon United States
Berwin A. Turlach Australia
J. Sunil Rao United States
Juliane Schäfer Switzerland
Annie Qu United States
William F. Rosenberger United States
Jianhua Z. Huang United States
Wenjiang Fu United States
Yuedong Wang United States
Mahlet G. Tadesse United States
Hung Hung relative to Noah Simon United States Noah Simon's profile →
Citations per field
00.5×4.7×
Noah Simon · 1×
Citations per year

Countries citing papers authored by Hung Hung

Since Specialization
Citations

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

Fields of papers citing papers by Hung Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hung Hung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hung Hung Line = papers co-authored together Hung Hung links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988369
2 2009245
3 2007195
4 1997191
5 2002152
6 2009121
7 2009110
8 200587
9 201168
10 200263
11 200260
12 200758
13 200651
14 200650
15 200150
16 198750
17 201245
18 201043
19 201441
20 201039

About Hung Hung

Hung Hung is a scholar working on Statistics and Probability, Management Science and Operations Research, Economics and Econometrics, Statistics, Probability and Uncertainty and Condensed Matter Physics, having authored 117 papers that have together received 3.1k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (64 papers), Optimal Experimental Design Methods (32 papers), Health Systems, Economic Evaluations, Quality of Life (22 papers), Meta-analysis and systematic reviews (16 papers), Statistical Methods and Inference (15 papers), Advanced Causal Inference Techniques (12 papers), Statistical Methods and Bayesian Inference (10 papers) and GaN-based semiconductor devices and materials (9 papers). The work is most often cited by research in Statistics and Probability (1.6k citations), Management Science and Operations Research (658 citations), Statistics, Probability and Uncertainty (328 citations), Computational Mathematics (24 citations) and Signal Processing (428 citations). Hung Hung has collaborated with scholars based in United States, Taiwan and Japan. Frequent co-authors include Robert T. O’Neill, Sue‐Jane Wang, M. Kaveh, Yi Tsong, Chin‐Tsang Chiang, Ohidul Siddiqui, John Lawrence, Péter Bauer, Lu Cui and Yeh‐Fong Chen. Their work appears in journals such as Journal of Biopharmaceutical Statistics, Biometrical Journal, Statistics in Biopharmaceutical Research, Statistics in Medicine and Pharmaceutical Statistics.

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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