Mohammad Shaker
Impact in
- Artificial Intelligence top 10%
- Artificial Intelligence in Games
- Machine Learning and Algorithms
- Machine Learning and Data Classification
- Reinforcement Learning in Robotics
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- Educational Games and Gamification
Papers in
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- Artificial Intelligence in Games 5
- Machine Learning and Algorithms 2
- Reinforcement Learning in Robotics 2
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- GABA and Rice Research 2
- Co-authors
- Noor Shaker (7 shared papers)Julian Togelius (3 shared papers)Eyke Hüllermeier (3 shared papers)Leyla Nazari (2 shared papers)Ewa Ropelewska (2 shared papers)Mariusz Szymanek (1 shared paper)Yousef Abbaspour‐Gilandeh (1 shared paper)A R Kiani (1 shared paper)
In The Last Decade
Mohammad Shaker
15 papers receiving 207 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 147
- Developmental and Educational Psychology 41
- Computer Vision and Pattern Recognition 39
- Sociology and Political Science 61
- 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-authors
The 21 scholars most cited alongside Mohammad Shaker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 79 | |
| 2 | 2013 | 43 | |
| 3 | 2013 | 34 | |
| 4 | 2013 | 18 | |
| 5 | 2015 | 10 | |
| 6 | 2020 | 7 | |
| 7 | 2021 | 4 | |
| 8 | 2008 | 4 | |
| 9 | 2021 | 3 | |
| 10 | A Quantitative Approach for Modelling and Personalizing Player Experience in First-Person Shooter Games. | 2013 | 3 |
| 11 | 2015 | 2 | |
| 12 | Active Learning for Player Modeling | 2015 | 2 |
| 13 | 2025 | 2 | |
| 14 | TECHNICAL EVALUATION OF IMPLEMENTED DRIP IRRIGATION SYSTEMS IN THE GARDENS OF GOLESTAN PROVINCE | 2014 | 2 |
| 15 | 2023 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About Mohammad Shaker
Mohammad Shaker is a scholar working on Artificial Intelligence, Plant Science, Sociology and Political Science, Soil Science and Economics and Econometrics, 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), GABA and Rice Research (2 papers), Machine Learning and Algorithms (2 papers), Reinforcement Learning in Robotics (2 papers), Sports Analytics and Performance (2 papers), Irrigation Practices and Water Management (2 papers) and Recycling and Waste Management Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (147 citations), Developmental and Educational Psychology (41 citations), Computer Vision and Pattern Recognition (39 citations), Sociology and Political Science (61 citations) and Control and Systems Engineering (32 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, Mariusz Szymanek, Yousef Abbaspour‐Gilandeh, A R Kiani, Vikash Kumar and Ajmir Khan. Their work appears in journals such as Journal of Food Process Engineering, American Journal of Dermatopathology, Knowledge-Based Systems, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Sensors.
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.