James Q. Smith
Impact in
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- Multi-Criteria Decision Making
- Artificial Intelligence top 5%
- Bayesian Modeling and Causal Inference
- AI-based Problem Solving and Planning
Papers in
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- Bayesian Modeling and Causal Inference 7
- Bayesian Methods and Mixture Models 2
- AI-based Problem Solving and Planning 1
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- Data Quality and Management 2
- Multi-Criteria Decision Making 1
- Co-authors
- Robert M. Oliver (3 shared papers)Paul Goodwin (1 shared paper)Martin Straume (1 shared paper)James Locke (1 shared paper)James R. Lynn (1 shared paper)Andrew J. Millar (1 shared paper)Anthony Hall (1 shared paper)Paul E. Anderson (1 shared paper)
- Journals
- Journal of the Operational Research Society (2 papers)Electronic Journal of Statistics (1 paper)Annals of Operations Research (1 paper)International Journal of Approximate Reasoning (1 paper)The Annals of Statistics (1 paper)
- Partner nations
- United KingdomBrazilUnited States
In The Last Decade
James Q. Smith
15 papers receiving 547 citations
Peers
Comparison fields: 5 of 93
- Management Science and Operations Research 93
- Artificial Intelligence 233
- Statistics and Probability 52
- Plant Science 226
- General Decision Sciences 11
Countries citing papers authored by James Q. Smith
This map shows the geographic impact of James Q. Smith'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 James Q. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Q. Smith more than expected).
Fields of papers citing papers by James Q. Smith
This network shows the impact of papers produced by James Q. Smith. 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 James Q. Smith. The network helps show where James Q. Smith may publish in the future.
Co-authors
The 19 scholars most cited alongside James Q. Smith, 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 | 2006 | 257 | |
| 2 | 1991 | 160 | |
| 3 | 1991 | 44 | |
| 4 | 1989 | 43 | |
| 5 | 2014 | 23 | |
| 6 | 2011 | 23 | |
| 7 | 1992 | 12 | |
| 8 | 2015 | 11 | |
| 9 | 2018 | 6 | |
| 10 | 2010 | 3 | |
| 11 | 2003 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2012 | 2 | |
| 14 | 1984 | 2 | |
| 15 | 1983 | 1 | |
| 16 | Multiagent Bayesian Forecasting of Time Series with Graphical Models | 2009 | 0 |
| 17 | 2005 | 0 |
About James Q. Smith
James Q. Smith is a scholar working on Artificial Intelligence, Management Science and Operations Research, Cognitive Neuroscience, Signal Processing and Experimental and Cognitive Psychology, having authored 17 papers that have together received 591 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), Mental Health Research Topics (2 papers), Data Quality and Management (2 papers), Time Series Analysis and Forecasting (2 papers), Functional Brain Connectivity Studies (2 papers), Bayesian Methods and Mixture Models (2 papers), AI-based Problem Solving and Planning (1 paper) and Multi-Criteria Decision Making (1 paper). The work is most often cited by research in Management Science and Operations Research (93 citations), Artificial Intelligence (233 citations), Statistics and Probability (52 citations), Plant Science (226 citations) and General Decision Sciences (11 citations). James Q. Smith has collaborated with scholars based in United Kingdom, Brazil and United States. Frequent co-authors include Robert M. Oliver, Paul Goodwin, Martin Straume, James Locke, James R. Lynn, Andrew J. Millar, Anthony Hall, Paul E. Anderson, Kieron D. Edwards and Neeraj Salathia. Their work appears in journals such as Journal of the Operational Research Society, Electronic Journal of Statistics, Annals of Operations Research, International Journal of Approximate Reasoning and The Annals of Statistics.
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.