Amr Sharaf

447 total citations
11 papers, 100 citations indexed

About

Amr Sharaf is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research. According to data from OpenAlex, Amr Sharaf has authored 11 papers receiving a total of 100 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Management Science and Operations Research. Recurrent topics in Amr Sharaf's work include Topic Modeling (3 papers), Machine Learning and Algorithms (2 papers) and Multimodal Machine Learning Applications (2 papers). Amr Sharaf is often cited by papers focused on Topic Modeling (3 papers), Machine Learning and Algorithms (2 papers) and Multimodal Machine Learning Applications (2 papers). Amr Sharaf collaborates with scholars based in United States, Egypt and Kuwait. Amr Sharaf's co-authors include Marwan Torki, Motaz El-Saban, Mohamed E. Hussein, Hal Daumé, Arti Nanda, Qasem A. Alsaleh, Hany Hassan, Yiren Wang, Renkun Ni and Arul Menezes and has published in prestigious journals such as International Journal of Dermatology, Journal de Mycologie Médicale and arXiv (Cornell University).

In The Last Decade

Amr Sharaf

9 papers receiving 94 citations

Peers

Amr Sharaf
Comparison fields: 5 of 35
  • Artificial Intelligence 61
  • Computer Vision and Pattern Recognition 46
  • Epidemiology 18
  • Dermatology 16
  • Biomedical Engineering 13
Replace Diping Song with:
Diping Song China
Christopher Semturs United States
Forhad Uddin Hasan Chowdhury Bangladesh
Taner Danışman Türkiye
Thomas Tanay Sweden
Santisudha Panigrahi India
Matthias Perkonigg Austria
Vihari Piratla India
Suria S. Mannil United States
Jianchun Zhao China
Diping Song China View profile →
Citations per field, relative to Amr Sharaf
Amr Sharaf · 1×
Citations per year, relative to Amr Sharaf
Amr Sharaf · 1×

Countries citing papers authored by Amr Sharaf

Since Specialization
Citations

This map shows the geographic impact of Amr Sharaf'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 Amr Sharaf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amr Sharaf more than expected).

Fields of papers citing papers by Amr Sharaf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amr Sharaf. 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 Amr Sharaf. The network helps show where Amr Sharaf may publish in the future.

Co-authorship network of co-authors of Amr Sharaf

This figure shows the co-authorship network connecting the top 25 collaborators of Amr Sharaf. A scholar is included among the top collaborators of Amr Sharaf 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 Amr Sharaf. Amr Sharaf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
# Work Indexed citations
1 12
2 4
3 5
4 3
5
Data Augmentation for Meta-Learning
1
6 16
7
Residual Loss Prediction: Reinforcement Learning With No Incremental Feedback
0
8 4
9 36
10 0
11 19

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.

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2026