Matthew B. Rhudy
- Aerospace Engineering top 1%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Yu GuJason N. GrossMarcello R. NapolitanoHaiyang ChaoMarcello NapolitanoWonkeun YounSrikanth GururajanAm Cho
- Topics
- Target Tracking and Data Fusion in Sensor Networks (35 papers)Inertial Sensor and Navigation (33 papers)Aerospace and Aviation Technology (24 papers)
- Partner nations
- United StatesSouth KoreaItaly
In The Last Decade
Matthew B. Rhudy
68 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 113
- Aerospace Engineering 774
- Artificial Intelligence 473
- Control and Systems Engineering 224
- Electrical and Electronic Engineering 150
- Computer Vision and Pattern Recognition 105
Countries citing papers authored by Matthew B. Rhudy
This map shows the geographic impact of Matthew B. Rhudy'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 Matthew B. Rhudy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew B. Rhudy more than expected).
Fields of papers citing papers by Matthew B. Rhudy
This network shows the impact of papers produced by Matthew B. Rhudy. 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 Matthew B. Rhudy. The network helps show where Matthew B. Rhudy may publish in the future.
Co-authorship network of co-authors of Matthew B. Rhudy
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew B. Rhudy. A scholar is included among the top collaborators of Matthew B. Rhudy 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 Matthew B. Rhudy. Matthew B. Rhudy 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 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 16 | |
| 8 | 9 | |
| 9 | 28 | |
| 10 | 20 | |
| 11 | 28 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 15 | |
| 15 | 2 | |
| 16 | 7 | |
| 17 | 28 | |
| 18 | 10 | |
| 19 | 13 | |
| 20 | 24 |
About Matthew B. Rhudy
Matthew B. Rhudy is a scholar working on Aerospace Engineering, Architecture and Artificial Intelligence, having authored 73 papers that have together received 1.1k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (35 papers), Inertial Sensor and Navigation (33 papers) and Aerospace and Aviation Technology (24 papers). The work is most often cited by research in Aerospace Engineering (774 citations), Artificial Intelligence (473 citations) and Control and Systems Engineering (224 citations). Matthew B. Rhudy has collaborated with scholars based in United States, South Korea and Italy. Frequent co-authors include Yu Gu, Jason N. Gross, Marcello R. Napolitano, Haiyang Chao, Marcello Napolitano, Wonkeun Youn, Srikanth Gururajan, Am Cho, Joseph M. Mahoney and Mario Luca Fravolini. Their work appears in journals such as Journal of Biomechanics, Sensors and IEEE Transactions on Aerospace and Electronic Systems.
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.