Mark A. Motter
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Aerospace Engineering top 10%
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Co-authors
- José C. Prı́ncipeJeongho ChoDeniz ErdoğmuşMichael OlCale ZeuneJing LanJulio ChuDennis Carter
- Topics
- Neural Networks and Applications (12 papers)Target Tracking and Data Fusion in Sensor Networks (9 papers)Aerospace and Aviation Technology (9 papers)
- Partner nations
- United StatesGermany
In The Last Decade
Mark A. Motter
36 papers receiving 350 citations
Peers
Comparison fields: 5 of 59
- Control and Systems Engineering 192
- Artificial Intelligence 151
- Aerospace Engineering 117
- Computer Networks and Communications 31
- Computer Vision and Pattern Recognition 30
Countries citing papers authored by Mark A. Motter
This map shows the geographic impact of Mark A. Motter'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 Mark A. Motter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Motter more than expected).
Fields of papers citing papers by Mark A. Motter
This network shows the impact of papers produced by Mark A. Motter. 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 Mark A. Motter. The network helps show where Mark A. Motter may publish in the future.
Co-authorship network of co-authors of Mark A. Motter
This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Motter. A scholar is included among the top collaborators of Mark A. Motter 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 Mark A. Motter. Mark A. Motter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | Towards an Open, Distributed Software Architecture for UxS Operations | 3 |
| 5 | 8 | |
| 6 | Remotely Piloted Vehicles for Experimental Flight Control Testing | 2 |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 10 | |
| 10 | 13 | |
| 11 | Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle | 3 |
| 12 | Autonomous Flying Controls Testbed | 4 |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 8 | |
| 17 | 7 | |
| 18 | Control of the NASA Langley 16-foot transonic tunnel with the self-organizing feature map | 2 |
| 19 | 97 | |
| 20 | 6 |
About Mark A. Motter
Mark A. Motter is a scholar working on Control and Systems Engineering, Aerospace Engineering and Artificial Intelligence, having authored 38 papers that have together received 375 indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Target Tracking and Data Fusion in Sensor Networks (9 papers) and Aerospace and Aviation Technology (9 papers). The work is most often cited by research in Control and Systems Engineering (192 citations), Aerospace Engineering (117 citations) and Artificial Intelligence (151 citations). Mark A. Motter has collaborated with scholars based in United States and Germany. Frequent co-authors include José C. Prı́ncipe, Jeongho Cho, Deniz Erdoğmuş, Michael Ol, Cale Zeune, Jing Lan, Julio Chu, Dennis Carter, Nelson Guerreiro and Anthony Calise. Their work appears in journals such as Proceedings of the IEEE, Neurocomputing and International Journal of Robust and Nonlinear Control.
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.