Mohammed Diab
Impact in
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
- Robotics and Automated Systems
- Artificial Intelligence top 10%
- AI-based Problem Solving and Planning
- Semantic Web and Ontologies
- Logic, Reasoning, and Knowledge
- Reinforcement Learning in Robotics
Papers in
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- AI-based Problem Solving and Planning 9
- Semantic Web and Ontologies 4
- Logic, Reasoning, and Knowledge 3
- Reinforcement Learning in Robotics 2
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- Robot Manipulation and Learning 3
- Co-authors
- Jan Rosell (7 shared papers)Aliakbar Akbari (3 shared papers)Daniel Beßler (2 shared papers)Michael Beetz (3 shared papers)Mohamed Elhelw (2 shared papers)Alberto Olivares‐Alarcos (2 shared papers)Maki K. Habib (2 shared papers)Stefano Borgo (3 shared papers)
- Journals
- Robotics and Autonomous Systems (1 paper)The Knowledge Engineering Review (1 paper)Applied Sciences (1 paper)IEEE Access (1 paper)International Journal of Social Robotics (1 paper)
- Partner nations
- United KingdomSpainGermany
In The Last Decade
Mohammed Diab
16 papers receiving 208 citations
Peers
Comparison fields: 5 of 62
- Control and Systems Engineering 97
- Artificial Intelligence 105
- Industrial and Manufacturing Engineering 28
- Computer Vision and Pattern Recognition 48
- Medical Laboratory Technology 3
Countries citing papers authored by Mohammed Diab
This map shows the geographic impact of Mohammed Diab'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 Mohammed Diab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Diab more than expected).
Fields of papers citing papers by Mohammed Diab
This network shows the impact of papers produced by Mohammed Diab. 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 Mohammed Diab. The network helps show where Mohammed Diab may publish in the future.
Co-authors
The 25 scholars most cited alongside Mohammed Diab, 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 | 2019 | 70 | |
| 2 | 2019 | 41 | |
| 3 | 2020 | 19 | |
| 4 | 2022 | 18 | |
| 5 | 2012 | 12 | |
| 6 | 2020 | 11 | |
| 7 | 2016 | 11 | |
| 8 | 2022 | 9 | |
| 9 | 2021 | 8 | |
| 10 | 2024 | 6 | |
| 11 | 2021 | 4 | |
| 12 | 2024 | 3 | |
| 13 | 2013 | 3 | |
| 14 | 2022 | 2 | |
| 15 | 2023 | 2 | |
| 16 | 2025 | 1 | |
| 17 | 2021 | 0 |
About Mohammed Diab
Mohammed Diab is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Social Psychology and Molecular Biology, having authored 17 papers that have together received 220 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (9 papers), Robotic Path Planning Algorithms (4 papers), Semantic Web and Ontologies (4 papers), Logic, Reasoning, and Knowledge (3 papers), Robot Manipulation and Learning (3 papers), Reinforcement Learning in Robotics (2 papers), Human-Automation Interaction and Safety (2 papers) and Social Robot Interaction and HRI (2 papers). The work is most often cited by research in Control and Systems Engineering (97 citations), Artificial Intelligence (105 citations), Industrial and Manufacturing Engineering (28 citations), Computer Vision and Pattern Recognition (48 citations) and Medical Laboratory Technology (3 citations). Mohammed Diab has collaborated with scholars based in United Kingdom, Spain and Germany. Frequent co-authors include Jan Rosell, Aliakbar Akbari, Daniel Beßler, Michael Beetz, Mohamed Elhelw, Alberto Olivares‐Alarcos, Maki K. Habib, Stefano Borgo, Julita Bermejo–Alonso and Howard Li. Their work appears in journals such as Robotics and Autonomous Systems, The Knowledge Engineering Review, Applied Sciences, IEEE Access and International Journal of Social Robotics.
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.