Mark Ibrahim
Impact in
-
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Machine Learning in Healthcare
Papers in
-
- Adversarial Robustness in Machine Learning 2
- Explainable Artificial Intelligence (XAI) 2
- Anomaly Detection Techniques and Applications 1
- Machine Learning and Data Classification 1
-
- Multimodal Machine Learning Applications 1
- Advanced Neural Network Applications 1
- Co-authors
- John Paisley (1 shared paper)Ivan Evtimov (2 shared papers)Cristian Canton Ferrer (2 shared papers)Caner Hazırbaş (3 shared papers)Albert Gordo (1 shared paper)Tal Hassner (1 shared paper)Chenliang Xu (1 shared paper)Zhiheng Li (1 shared paper)
- Partner nations
- United States
In The Last Decade
Mark Ibrahim
3 papers receiving 76 citations
Peers
Comparison fields: 5 of 47
- Health Informatics 6
- Artificial Intelligence 60
- Computer Vision and Pattern Recognition 14
- Information Systems and Management 4
- Computer Science Applications 3
Countries citing papers authored by Mark Ibrahim
This map shows the geographic impact of Mark Ibrahim'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 Mark Ibrahim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Ibrahim more than expected).
Fields of papers citing papers by Mark Ibrahim
This network shows the impact of papers produced by Mark Ibrahim. 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 Mark Ibrahim. The network helps show where Mark Ibrahim may publish in the future.
Co-authors
The 12 scholars most cited alongside Mark Ibrahim, 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 | 67 | |
| 2 | 2023 | 11 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 0 | |
| 5 | 2024 | 0 |
About Mark Ibrahim
Mark Ibrahim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Physical Therapy, Sports Therapy and Rehabilitation, Developmental and Educational Psychology and Biomedical Engineering, having authored 5 papers that have together received 79 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Multimodal Machine Learning Applications (1 paper), Mechanics and Biomechanics Studies (1 paper), Anomaly Detection Techniques and Applications (1 paper), Sports and Physical Education Research (1 paper), Machine Learning and Data Classification (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Health Informatics (6 citations), Artificial Intelligence (60 citations), Computer Vision and Pattern Recognition (14 citations), Information Systems and Management (4 citations) and Computer Science Applications (3 citations). Mark Ibrahim has collaborated with scholars based in United States. Frequent co-authors include John Paisley, Ivan Evtimov, Cristian Canton Ferrer, Caner Hazırbaş, Albert Gordo, Tal Hassner, Chenliang Xu, Zhiheng Li, Diane Bouchacourt and Jiachen Sun.
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.