Michael D. Howard
- Computer Networks and Communications top 5%
- Cognitive Neuroscience top 10%
- Mechanical Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Co-authors
- David W. PaytonMike DailyRajan BhattacharyyaCraig LeeNicholas KetzRandall C. O’ReillyR.S. WallacePraveen K. Pilly
- Topics
- Neural dynamics and brain function (5 papers)Neuroscience and Neuropharmacology Research (5 papers)Memory and Neural Mechanisms (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceCognitive ScienceFrontiers in Neuroscience
- Partner nations
- United States
In The Last Decade
Michael D. Howard
21 papers receiving 550 citations
Peers
Comparison fields: 5 of 88
- Computer Networks and Communications 195
- Cognitive Neuroscience 186
- Mechanical Engineering 178
- Computer Vision and Pattern Recognition 125
- Artificial Intelligence 82
Countries citing papers authored by Michael D. Howard
This map shows the geographic impact of Michael D. Howard'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 Michael D. Howard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Howard more than expected).
Fields of papers citing papers by Michael D. Howard
This network shows the impact of papers produced by Michael D. Howard. 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 Michael D. Howard. The network helps show where Michael D. Howard may publish in the future.
Co-authorship network of co-authors of Michael D. Howard
This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Howard. A scholar is included among the top collaborators of Michael D. Howard 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 Michael D. Howard. Michael D. Howard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 28 | |
| 6 | 14 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 7 | |
| 14 | 156 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 4 | |
| 18 | 52 | |
| 19 | 40 | |
| 20 | 19 |
About Michael D. Howard
Michael D. Howard is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Neurology, having authored 23 papers that have together received 585 indexed citations. Recurring topics across this work include Neural dynamics and brain function (5 papers), Neuroscience and Neuropharmacology Research (5 papers) and Memory and Neural Mechanisms (5 papers). The work is most often cited by research in Cognitive Neuroscience (186 citations), Computer Networks and Communications (195 citations) and Human-Computer Interaction (34 citations). Michael D. Howard has collaborated with scholars based in United States. Frequent co-authors include David W. Payton, Mike Daily, Rajan Bhattacharyya, Craig Lee, Nicholas Ketz, Randall C. O’Reilly, R.S. Wallace, Praveen K. Pilly, J. Jerald and Craig A. Lee. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Cognitive Science and Frontiers in Neuroscience.
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.