Jordan Freitas
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Signal Processing
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- Mahesan NiranjanAndrew H. GeeRandal DoucChristopher JacksonDuncan S. CallawayDaniel M. KammenJohn David N. DionisioAndrew Nguyen
- Topics
- Neural Networks and Applications (4 papers)Target Tracking and Data Fusion in Sensor Networks (4 papers)Aging, Elder Care, and Social Issues (2 papers)
- Partner nations
- United StatesUnited KingdomSouth Sudan
In The Last Decade
Jordan Freitas
11 papers receiving 191 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 127
- Control and Systems Engineering 76
- Signal Processing 26
- Electrical and Electronic Engineering 26
- Computer Vision and Pattern Recognition 20
Countries citing papers authored by Jordan Freitas
This map shows the geographic impact of Jordan Freitas'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 Jordan Freitas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordan Freitas more than expected).
Fields of papers citing papers by Jordan Freitas
This network shows the impact of papers produced by Jordan Freitas. 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 Jordan Freitas. The network helps show where Jordan Freitas may publish in the future.
Co-authorship network of co-authors of Jordan Freitas
This figure shows the co-authorship network connecting the top 25 collaborators of Jordan Freitas. A scholar is included among the top collaborators of Jordan Freitas 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 Jordan Freitas. Jordan Freitas 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 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 3 | |
| 7 | 147 | |
| 8 | 9 | |
| 9 | 19 | |
| 10 | Sequential Bayesian Estimation And Model Selection Applied To Neural Networks | 7 |
| 11 | Robust Full Bayesian Learning for Neural Networks | 6 |
| 12 | Neural networks for pneumatic actuator fault detection | 8 |
About Jordan Freitas
Jordan Freitas is a scholar working on Computer Science Applications, Philosophy and Artificial Intelligence, having authored 12 papers that have together received 214 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Target Tracking and Data Fusion in Sensor Networks (4 papers) and Aging, Elder Care, and Social Issues (2 papers). The work is most often cited by research in Artificial Intelligence (127 citations), Control and Systems Engineering (76 citations) and Signal Processing (26 citations). Jordan Freitas has collaborated with scholars based in United States, United Kingdom and South Sudan. Frequent co-authors include Mahesan Niranjan, Andrew H. Gee, Randal Douc, Christopher Jackson, Duncan S. Callaway, Daniel M. Kammen, John David N. Dionisio, Andrew Nguyen, William J. Bosl and AH Gee. Their work appears in journals such as Proceedings of the IEEE, Neural Computation and Biomédica.
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.