Thomas M. Howard
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Biomedical Engineering
- Co-authors
- Nicholas RoyJacob ArkinRohan PaulMatthew R. WalterStefanie TellexDerya AksarayFelix DuvalletAnthony Stentz
- Topics
- Multimodal Machine Learning Applications (14 papers)Natural Language Processing Techniques (11 papers)Topic Modeling (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceControl and Systems Engineering
- Journals
- The International Journal of Robotics ResearchIEEE Robotics and Automation LettersArXiv.org
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Thomas M. Howard
28 papers receiving 355 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 240
- Computer Vision and Pattern Recognition 195
- Control and Systems Engineering 104
- Aerospace Engineering 37
- Biomedical Engineering 31
Countries citing papers authored by Thomas M. Howard
This map shows the geographic impact of Thomas M. 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 Thomas M. Howard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas M. Howard more than expected).
Fields of papers citing papers by Thomas M. Howard
This network shows the impact of papers produced by Thomas M. 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 Thomas M. Howard. The network helps show where Thomas M. Howard may publish in the future.
Co-authorship network of co-authors of Thomas M. Howard
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas M. Howard. A scholar is included among the top collaborators of Thomas M. 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 Thomas M. Howard. Thomas M. 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 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 7 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 28 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 5 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | Efficient Grounding of Abstract Spatial Concepts for Natural Language Interaction with Robot Manipulators | 4 |
| 15 | 15 | |
| 16 | 4 | |
| 17 | Inferring Maps and Behaviors from Natural Language Instructions | 10 |
| 18 | 20 | |
| 19 | 35 | |
| 20 | Efficient Natural Language Interfaces for Assistive Robots | 9 |
About Thomas M. Howard
Thomas M. Howard is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human Factors and Ergonomics, having authored 31 papers that have together received 369 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (14 papers), Natural Language Processing Techniques (11 papers) and Topic Modeling (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (195 citations), Artificial Intelligence (240 citations) and Control and Systems Engineering (104 citations). Thomas M. Howard has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Nicholas Roy, Jacob Arkin, Rohan Paul, Matthew R. Walter, Stefanie Tellex, Derya Aksaray, Felix Duvallet, Anthony Stentz, Sachithra Hemachandra and Nicholas Roy. Their work appears in journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters and ArXiv.org.
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.