Mohammad Shaker
- Artificial Intelligence top 10%
- Sociology and Political Science
- Developmental and Educational Psychology
- Computer Vision and Pattern Recognition
- Control and Systems Engineering
- Co-authors
- Noor ShakerJulian TogeliusEyke HüllermeierLeyla NazariEwa RopelewskaA R KianiYousef Abbaspour‐GilandehMariusz Szymanek
- Topics
- Artificial Intelligence in Games (5 papers)Digital Games and Media (4 papers)Irrigation Practices and Water Management (2 papers)
- Cited by
- Artificial IntelligenceDevelopmental and Educational PsychologyComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaSensorsMachine Learning
In The Last Decade
Mohammad Shaker
15 papers receiving 207 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 147
- Sociology and Political Science 61
- Developmental and Educational Psychology 41
- Computer Vision and Pattern Recognition 39
- Control and Systems Engineering 32
Countries citing papers authored by Mohammad Shaker
This map shows the geographic impact of Mohammad Shaker'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 Mohammad Shaker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Shaker more than expected).
Fields of papers citing papers by Mohammad Shaker
This network shows the impact of papers produced by Mohammad Shaker. 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 Mohammad Shaker. The network helps show where Mohammad Shaker may publish in the future.
Co-authorship network of co-authors of Mohammad Shaker
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Shaker. A scholar is included among the top collaborators of Mohammad Shaker 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 Mohammad Shaker. Mohammad Shaker 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 | 2 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 79 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 10 | |
| 12 | Active Learning for Player Modeling | 2 |
| 13 | TECHNICAL EVALUATION OF IMPLEMENTED DRIP IRRIGATION SYSTEMS IN THE GARDENS OF GOLESTAN PROVINCE | 2 |
| 14 | 43 | |
| 15 | 34 | |
| 16 | A Quantitative Approach for Modelling and Personalizing Player Experience in First-Person Shooter Games. | 3 |
| 17 | 18 | |
| 18 | 4 |
About Mohammad Shaker
Mohammad Shaker is a scholar working on Soil Science, Artificial Intelligence and Plant Science, having authored 18 papers that have together received 214 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (5 papers), Digital Games and Media (4 papers) and Irrigation Practices and Water Management (2 papers). The work is most often cited by research in Artificial Intelligence (147 citations), Developmental and Educational Psychology (41 citations) and Computer Vision and Pattern Recognition (39 citations). Mohammad Shaker has collaborated with scholars based in Denmark, Iran and Syria. Frequent co-authors include Noor Shaker, Julian Togelius, Eyke Hüllermeier, Leyla Nazari, Ewa Ropelewska, A R Kiani, Yousef Abbaspour‐Gilandeh, Mariusz Szymanek, Claude Duguay and Kecheng Li. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and Machine Learning.
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.