Ian H. Sloan
- Numerical Analysis top 0.05%
- Mathematical Approximation and Integration 100
- Modeling and Simulation top 0.2%
- Fractional Differential Equations Solutions 28
- Applied Mathematics top 0.2%
- Mathematical functions and polynomials 64
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- Probabilistic and Robust Engineering Design 32
- Computational Theory and Mathematics top 0.2%
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- Electromagnetic Scattering and Analysis 41
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- Advanced Numerical Methods in Computational Mathematics 39
- Advanced Numerical Analysis Techniques 38
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- Numerical methods in engineering 36
- Co-authors
- Frances Y. KuoHenryk WoźniakowskiStephen JoeRobert S. WomersleyVidar ThoméeJosef DickXiaoqun WangWilliam E. Smith
- Journals
- Mathematics of Computation (46 papers)Numerische Mathematik (25 papers)SIAM Journal on Numerical Analysis (23 papers)
- Partner nations
- AustraliaUnited StatesGermany
In The Last Decade
Ian H. Sloan
258 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Numerical Analysis 3.9k
- Modeling and Simulation 975
- Applied Mathematics 2.0k
- Statistics, Probability and Uncertainty 1.3k
- Computational Theory and Mathematics 1.4k
Countries citing papers authored by Ian H. Sloan
This map shows the geographic impact of Ian H. Sloan'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 Ian H. Sloan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian H. Sloan more than expected).
Fields of papers citing papers by Ian H. Sloan
This network shows the impact of papers produced by Ian H. Sloan. 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 Ian H. Sloan. The network helps show where Ian H. Sloan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ian H. Sloan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 1 | |
| 2 | 2020 | 6 | |
| 3 | A New Probe of Gaussianity and Isotropy for CMB Maps | 2019 | 1 |
| 4 | 2015 | 8 | |
| 5 | 2014 | 33 | |
| 6 | 2007 | 11 | |
| 7 | 2006 | 3 | |
| 8 | 2005 | 20 | |
| 9 | 1991 | 5 | |
| 10 | 1991 | 10 | |
| 11 | 1991 | 15 | |
| 12 | 1991 | 39 | |
| 13 | 1990 | 2 | |
| 14 | 1989 | 29 | |
| 15 | 1989 | 38 | |
| 16 | 1986 | 9 | |
| 17 | 1986 | 5 | |
| 18 | 1983 | 12 | |
| 19 | 1976 | 89 | |
| 20 | 1964 | 93 |
About Ian H. Sloan
Ian H. Sloan is a scholar working on Numerical Analysis, Applied Mathematics and Modeling and Simulation, having authored 266 papers that have together received 7.8k indexed citations. Recurring topics across this work include Mathematical Approximation and Integration (100 papers), Mathematical functions and polynomials (64 papers), Electromagnetic Scattering and Analysis (41 papers), Advanced Numerical Methods in Computational Mathematics (39 papers), Advanced Numerical Analysis Techniques (38 papers), Numerical methods in engineering (36 papers), Probabilistic and Robust Engineering Design (32 papers) and Fractional Differential Equations Solutions (28 papers). The work is most often cited by research in Numerical Analysis (3.9k citations), Modeling and Simulation (975 citations) and Applied Mathematics (2.0k citations). Ian H. Sloan has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Frances Y. Kuo, Henryk Woźniakowski, Stephen Joe, Robert S. Womersley, Vidar Thomée, Josef Dick, Xiaoqun Wang, William E. Smith, Ivan G. Graham and Sunil Kumar. Their work appears in journals such as Mathematics of Computation, Numerische Mathematik, SIAM Journal on Numerical Analysis, Journal of Complexity and Nuclear Physics A.
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.