Micheal Hewett
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Pharmacology top 5%
- Artificial Intelligence top 10%
- Genetics
- Co-authors
- Russ B. AltmanDiane E. OliverDaniel L. RubinTeri E. KleinJoshua M. StuartStanley Yung‐Chuan LiuMildred K. ChoKatrina L. Easton
- Topics
- Biomedical Text Mining and Ontologies (4 papers)Semantic Web and Ontologies (4 papers)AI-based Problem Solving and Planning (4 papers)
- Partner nations
- United States
In The Last Decade
Micheal Hewett
13 papers receiving 619 citations
Peers
Comparison fields: 5 of 95
- Molecular Biology 410
- Computational Theory and Mathematics 176
- Pharmacology 149
- Artificial Intelligence 138
- Genetics 103
Countries citing papers authored by Micheal Hewett
This map shows the geographic impact of Micheal Hewett'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 Micheal Hewett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Micheal Hewett more than expected).
Fields of papers citing papers by Micheal Hewett
This network shows the impact of papers produced by Micheal Hewett. 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 Micheal Hewett. The network helps show where Micheal Hewett may publish in the future.
Co-authorship network of co-authors of Micheal Hewett
This figure shows the co-authorship network connecting the top 25 collaborators of Micheal Hewett. A scholar is included among the top collaborators of Micheal Hewett 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 Micheal Hewett. Micheal Hewett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 305 | |
| 4 | 6 | |
| 5 | 7 | |
| 6 | 254 | |
| 7 | Computational Perceptual Attention | 4 |
| 8 | 20 | |
| 9 | 32 | |
| 10 | The Algernon Abstract Machine: Compiling and Executing Rule-Based Programs | 0 |
| 11 | 11 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | The heuristic refinement method for deriving solution structures of proteins | 2 |
| 15 | A Layered Environment for Reasoning about Action | 21 |
| 16 | Learning control heuristics in BB1 | 3 |
About Micheal Hewett
Micheal Hewett is a scholar working on Software, Computer Networks and Communications and Artificial Intelligence, having authored 16 papers that have together received 669 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Semantic Web and Ontologies (4 papers) and AI-based Problem Solving and Planning (4 papers). The work is most often cited by research in Pharmacology (149 citations), Computational Theory and Mathematics (176 citations) and Molecular Biology (410 citations). Micheal Hewett has collaborated with scholars based in United States. Frequent co-authors include Russ B. Altman, Diane E. Oliver, Daniel L. Rubin, Teri E. Klein, Joshua M. Stuart, Stanley Yung‐Chuan Liu, Mildred K. Cho, Katrina L. Easton, Jean Chang and Ray W. Fergerson. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and The Pharmacogenomics Journal.
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.