Patricia Hough
- Numerical Analysis top 10%
- Advanced Optimization Algorithms Research 3
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- Numerical Methods and Algorithms 3
- Matrix Theory and Algorithms 2
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- Risk and Safety Analysis 2
- Probabilistic and Robust Engineering Design 2
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- Metaheuristic Optimization Algorithms Research 2
- Algorithms and Data Compression 2
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- Fault Detection and Control Systems 2
Patricia Hough
11 papers receiving 227 citations
Peers
Comparison fields: 5 of 75
- Numerical Analysis 52
- Metals and Alloys 14
- Computational Theory and Mathematics 67
- Statistics, Probability and Uncertainty 15
- Artificial Intelligence 59
Countries citing papers authored by Patricia Hough
This map shows the geographic impact of Patricia Hough'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 Patricia Hough with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patricia Hough more than expected).
Fields of papers citing papers by Patricia Hough
This network shows the impact of papers produced by Patricia Hough. 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 Patricia Hough. The network helps show where Patricia Hough may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Patricia Hough, 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 | 2020 | 18 | |
| 2 | Dakota Software Training: Uncertainty Quantification. | 2016 | 0 |
| 3 | 2015 | 9 | |
| 4 | 2013 | 1 | |
| 5 | Feasibility, economics, and environmental impact of producing 90 billion gallons of ethanol per year by 2030 | 2009 | 15 |
| 6 | 2007 | 39 | |
| 7 | Modern Machine Learning for Automatic Optimization Algorithm Selection. | 2006 | 8 |
| 8 | 2002 | 7 | |
| 9 | 2001 | 111 | |
| 10 | Library for Nonlinear Optimization | 2001 | 1 |
| 11 | Asynchronous Parallel Pattern Search | 2000 | 1 |
| 12 | 1997 | 35 |
About Patricia Hough
Patricia Hough is a scholar working on Numerical Analysis, Statistics, Probability and Uncertainty, Metals and Alloys, Software and Computational Theory and Mathematics, having authored 12 papers that have together received 245 indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (3 papers), Numerical Methods and Algorithms (3 papers), Metaheuristic Optimization Algorithms Research (2 papers), Risk and Safety Analysis (2 papers), Fault Detection and Control Systems (2 papers), Probabilistic and Robust Engineering Design (2 papers), Matrix Theory and Algorithms (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Numerical Analysis (52 citations), Metals and Alloys (14 citations), Computational Theory and Mathematics (67 citations), Statistics, Probability and Uncertainty (15 citations) and Artificial Intelligence (59 citations). Patricia Hough has collaborated with scholars based in United States and Japan. Frequent co-authors include Tamara G. Kolda, Virginia Torczon, Stephen A. Vavasis, Juan Meza, Ricardo Oliva, Lauren L. Beghini, Konrad Thürmer, Paul J. Gibbs, Christopher W. San Marchi and Jonathan A. Zimmerman. Their work appears in journals such as ACM Transactions on Mathematical Software, JOM, SIAM Journal on Scientific Computing, SIAM Journal on Optimization and SIAM Journal on Matrix Analysis and Applications.
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.