Michael Ikeda

559 citations
10 papers · 370 · h-index 5

Impact in

Papers in

Michael Ikeda

9 papers receiving 339 citations

Peers

Michael Ikeda
Comparison fields: 5 of 85
  • Statistical and Nonlinear Physics 201
  • Statistics and Probability 49
  • Experimental and Cognitive Psychology 32
  • Communication 16
  • Management Science and Operations Research 27
Replace Tiandong Wang with:
Tiandong Wang United States
Chongjun Fan China
D. J. Bartholomew
Kimon Drakopoulos United States
M. Amin Rahimian United States
Nicholas C. Valler United States
Taro Takaguchi Japan
Mathias Lindholm Sweden
Amulya Yadav United States
Jianlin Zhou China
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Citations per field
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Citations per year

Countries citing papers authored by Michael Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Michael Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Michael Ikeda, 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 Michael Ikeda Line = papers co-authored together Michael Ikeda links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 1990280
2 199047
3 201421
4 20118
5 20057
6
The anthropic principle does not support supernaturalism
20063
7
A Novel Multiple-Phase, Multiple-Component, Thermal Lattice Boltzmann Model
20122
8 20121
9
Numerical Simulation of Vapor-Liquid Equilibria of a Water-Ethanol Mixture
20111
10
Initial Results from a Nationwide BigMatch Matching of 2000 Census Data
20070

About Michael Ikeda

Michael Ikeda is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics, Artificial Intelligence, Electrical and Electronic Engineering and Statistics and Probability, having authored 10 papers that have together received 370 indexed citations. Recurring topics across this work include Lattice Boltzmann Simulation Studies (3 papers), Advanced Clustering Algorithms Research (2 papers), Phase Equilibria and Thermodynamics (2 papers), Complex Network Analysis Techniques (2 papers), Aerosol Filtration and Electrostatic Precipitation (2 papers), Heat and Mass Transfer in Porous Media (2 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper) and Census and Population Estimation (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (201 citations), Statistics and Probability (49 citations), Experimental and Cognitive Psychology (32 citations), Communication (16 citations) and Management Science and Operations Research (27 citations). Michael Ikeda has collaborated with scholars based in United States. Frequent co-authors include David Strauss, Laura Schaefer, Hubert Stein, Gerhard Wimmer‐Greinecker, Romuald Cichoń and Volkmar Falk. Their work appears in journals such as Journal of the American Statistical Association, Fluid Phase Equilibria, The Heart Surgery Forum, Computers & Fluids and D-Scholarship@Pitt (University of Pittsburgh).

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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