Ming S. Hung

1.3k citations
36 papers · 1.0k · h-index 17

Impact in

Papers in

Ming S. Hung

34 papers receiving 951 citations

Peers

Ming S. Hung
Comparison fields: 5 of 131
  • Industrial and Manufacturing Engineering 220
  • Management Science and Operations Research 182
  • Artificial Intelligence 319
  • Computational Theory and Mathematics 115
  • Accounting 75
Replace Xu Yu with:
Xu Yu China
Chilukuri K. Mohan India
Hedieh Sajedi Iran
John Fulcher Australia
Gilles Mauris France
Subhash C. Narula United States
Fabio Caraffini United Kingdom
Zhaohui Zheng United States
Alan W. Johnson United States
Ming S. Hung relative to Xu Yu China Xu Yu's profile →
Citations per field
00.5×6.3×
Xu Yu · 1×
Citations per year

Countries citing papers authored by Ming S. Hung

Since Specialization
Citations

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

Fields of papers citing papers by Ming S. Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Ming S. 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 Ming S. Hung Line = papers co-authored together Ming S. Hung links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996238
2 1993156
3 198088
4 199361
5 197855
6 199340
7 198839
8 198337
9 199931
10 199329
11 198728
12 200222
13 199621
14 199021
15 199519
16 198419
17 197818
18 200716
19 197915
20 198813

About Ming S. Hung

Ming S. Hung is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering, Control and Systems Engineering, Signal Processing and Computer Networks and Communications, having authored 36 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (13 papers), Optimization and Mathematical Programming (5 papers), Advanced Manufacturing and Logistics Optimization (5 papers), Data Management and Algorithms (5 papers), Optimization and Packing Problems (5 papers), Advanced Queuing Theory Analysis (3 papers), Fuzzy Logic and Control Systems (3 papers) and Optimization and Search Problems (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (220 citations), Management Science and Operations Research (182 citations), Artificial Intelligence (319 citations), Computational Theory and Mathematics (115 citations) and Accounting (75 citations). Ming S. Hung has collaborated with scholars based in United States, Hong Kong and Cambodia. Frequent co-authors include Michael Y. Hu, Murali Shanker, Walter O. Rom, Allan D. Waren, James R. Brown, Leon S. Lasdon, Abraham Mehrez, G. Peter Zhang, B. Eddy Patuwo and Chia‐Shin Chung. Their work appears in journals such as Journal of the Operational Research Society, Computers & Operations Research, Operations Research, European Journal of Operational Research and Decision Sciences.

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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