Gabriel Terejanu
- Artificial Intelligence top 5%
- Materials Chemistry
- Aerospace Engineering top 10%
- Statistics, Probability and Uncertainty top 2%
- Catalysis top 10%
- Co-authors
- Tarunraj SinghPeter ScottPuneet SinglaAndreas HeydenEric A. WalkerWenqiang YangSalai Cheettu AmmalKenji Miki
- Topics
- Target Tracking and Data Fusion in Sensor Networks (11 papers)Probabilistic and Robust Engineering Design (10 papers)Machine Learning in Materials Science (8 papers)
- Partner nations
- United StatesIndiaEgypt
In The Last Decade
Gabriel Terejanu
43 papers receiving 798 citations
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 313
- Materials Chemistry 262
- Aerospace Engineering 152
- Statistics, Probability and Uncertainty 133
- Catalysis 117
Countries citing papers authored by Gabriel Terejanu
This map shows the geographic impact of Gabriel Terejanu'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 Gabriel Terejanu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Terejanu more than expected).
Fields of papers citing papers by Gabriel Terejanu
This network shows the impact of papers produced by Gabriel Terejanu. 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 Gabriel Terejanu. The network helps show where Gabriel Terejanu may publish in the future.
Co-authorship network of co-authors of Gabriel Terejanu
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Terejanu. A scholar is included among the top collaborators of Gabriel Terejanu 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 Gabriel Terejanu. Gabriel Terejanu 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 | 3 | |
| 3 | 0 | |
| 4 | 12 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 24 | |
| 8 | 2 | |
| 9 | 5 | |
| 10 | 80 | |
| 11 | 18 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | 3 | |
| 15 | 5 | |
| 16 | 10 | |
| 17 | 34 | |
| 18 | A Decision-Centric Framework for Density Forecasting. | 1 |
| 19 | A novel Gaussian Sum Filter Method for accurate solution to the nonlinear filtering problem | 13 |
| 20 | An adaptive Gaussian sum filter for the spacecraft attitude estimation problem | 2 |
About Gabriel Terejanu
Gabriel Terejanu is a scholar working on Statistics, Probability and Uncertainty, Catalysis and Computational Theory and Mathematics, having authored 47 papers that have together received 831 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (11 papers), Probabilistic and Robust Engineering Design (10 papers) and Machine Learning in Materials Science (8 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (133 citations), Catalysis (117 citations) and Artificial Intelligence (313 citations). Gabriel Terejanu has collaborated with scholars based in United States, India and Egypt. Frequent co-authors include Tarunraj Singh, Peter Scott, Puneet Singla, Andreas Heyden, Eric A. Walker, Wenqiang Yang, Salai Cheettu Ammal, Kenji Miki, Osman Mamun and Robert Moser. Their work appears in journals such as IEEE Transactions on Automatic Control, Scientific Reports and ACS Catalysis.
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.