E. O'Hair
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 10%
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Environmental Engineering
- Co-authors
- Donald C. WunschShuhui LiMichael GiesselmannM. KristiansenT.G. EngelJ. DickensJ.N. MarxJ. Mańkowski
- Topics
- Neural Networks and Applications (6 papers)Energy Load and Power Forecasting (6 papers)Vacuum and Plasma Arcs (6 papers)
- Cited by
- Energy Engineering and Power TechnologyElectrical and Electronic EngineeringAerospace Engineering
- Journals
- IEEE Transactions on Energy ConversionIEEE Transactions on MagneticsIEEE Transactions on Plasma Science
- Partner nations
- United States
In The Last Decade
E. O'Hair
22 papers receiving 458 citations
Peers
Comparison fields: 5 of 58
- Electrical and Electronic Engineering 393
- Artificial Intelligence 145
- Aerospace Engineering 145
- Control and Systems Engineering 94
- Environmental Engineering 54
Countries citing papers authored by E. O'Hair
This map shows the geographic impact of E. O'Hair'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 E. O'Hair with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. O'Hair more than expected).
Fields of papers citing papers by E. O'Hair
This network shows the impact of papers produced by E. O'Hair. 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 E. O'Hair. The network helps show where E. O'Hair may publish in the future.
Co-authorship network of co-authors of E. O'Hair
This figure shows the co-authorship network connecting the top 25 collaborators of E. O'Hair. A scholar is included among the top collaborators of E. O'Hair 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 E. O'Hair. E. O'Hair is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 12 | |
| 3 | 70 | |
| 4 | 9 | |
| 5 | 14 | |
| 6 | 92 | |
| 7 | 250 | |
| 8 | 7 | |
| 9 | Multi-stream Extended Kalman Filter Training of Neural Networks on a Simd Parallel Machine | 1 |
| 10 | 1 | |
| 11 | Comparative Analysis of Regression and Neural Network Models for Wind Power | 1 |
| 12 | 3 | |
| 13 | 7 | |
| 14 | 4 | |
| 15 | 3 | |
| 16 | 10 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | The Crosbyton Solar Power Project: Solar bowl subsystems tests and analyses | 1 |
| 20 | 1 |
About E. O'Hair
E. O'Hair is a scholar working on Artificial Intelligence, Control and Systems Engineering and Electrical and Electronic Engineering, having authored 22 papers that have together received 496 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Energy Load and Power Forecasting (6 papers) and Vacuum and Plasma Arcs (6 papers). The work is most often cited by research in Energy Engineering and Power Technology (32 citations), Electrical and Electronic Engineering (393 citations) and Aerospace Engineering (145 citations). E. O'Hair has collaborated with scholars based in United States. Frequent co-authors include Donald C. Wunsch, Shuhui Li, Michael Giesselmann, M. Kristiansen, T.G. Engel, J. Dickens, J.N. Marx, J. Mańkowski, L.L. Hatfield and Martin S Piltch. Their work appears in journals such as IEEE Transactions on Energy Conversion, IEEE Transactions on Magnetics and IEEE Transactions on Plasma Science.
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.