Michael C. Fu

10.5k total citations · 2 hit papers
263 papers, 6.5k citations indexed

About

Michael C. Fu is a scholar working on Management Science and Operations Research, Artificial Intelligence and Management Information Systems. According to data from OpenAlex, Michael C. Fu has authored 263 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 118 papers in Management Science and Operations Research, 53 papers in Artificial Intelligence and 47 papers in Management Information Systems. Recurrent topics in Michael C. Fu's work include Simulation Techniques and Applications (81 papers), Advanced Queuing Theory Analysis (44 papers) and Stochastic processes and financial applications (38 papers). Michael C. Fu is often cited by papers focused on Simulation Techniques and Applications (81 papers), Advanced Queuing Theory Analysis (44 papers) and Stochastic processes and financial applications (38 papers). Michael C. Fu collaborates with scholars based in United States, China and South Korea. Michael C. Fu's co-authors include Steven I. Marcus, Jian-Qiang Hu, Jiaqiao Hu, Saul I. Gass, Chun‐Hung Chen, Hyeong Soo Chang, Yijie Peng, Donghai He, Loo Hay Lee and Fred Glover and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Management Science.

In The Last Decade

Michael C. Fu

241 papers receiving 6.2k citations

Hit Papers

Feature Article: Optimization for simulation: Theory vs. ... 2002 2026 2010 2018 2002 2014 100 200 300 400 500

Peers

Michael C. Fu
Comparison fields: 5 of 154
  • Management Science and Operations Research 3.0k
  • Industrial and Manufacturing Engineering 1.4k
  • Management Information Systems 1.2k
  • Computational Theory and Mathematics 1.1k
  • Artificial Intelligence 1.1k
Replace Barry L. Nelson with:
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Citations per field, relative to Michael C. Fu
Michael C. Fu · 1×
Citations per year, relative to Michael C. Fu
Michael C. Fu · 1×

Countries citing papers authored by Michael C. Fu

Since Specialization
Citations

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

Fields of papers citing papers by Michael C. Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael C. Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Michael C. Fu. A scholar is included among the top collaborators of Michael C. Fu 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 Michael C. Fu. Michael C. Fu 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
# Work Indexed citations
1 1
2 0
3 0
4 2
5 0
6 7
7 3
8 1
9 6
10 1
11 2
12 9
13 6
14 10
15
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control
25
16 3
17 4
18 1
19 50
20
A Proposed Virtual Design Review Environment
3

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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