Ali Braytee

49 papers receiving 469 citations

Peers

Ali Braytee
Comparison fields: 5 of 104
  • Computational Mathematics 11
  • Water Science and Technology 75
  • Computer Vision and Pattern Recognition 106
  • Artificial Intelligence 161
  • Civil and Structural Engineering 56
Replace Junaid Khan with:
Junaid Khan South Korea
Amira Bibo Sallow Iraq
Munesh Singh India
Kamilya Smagulova Kazakhstan
Yawei Zhao China
A. Helen Victoria India
John T. McCoy South Africa
Tobias Pielok Germany
Difan Deng Germany
Yasser A. Ali Saudi Arabia
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Citations per field
00.5×8.9×
Junaid Khan · 1×
Citations per year

Countries citing papers authored by Ali Braytee

Since Specialization
Citations

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

Fields of papers citing papers by Ali Braytee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ali Braytee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ali Braytee Line = papers co-authored together Ali Braytee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201742
2 201638
3 202232
4 201932
5 201725
6 202023
7 202022
8 201920
9 202320
10 201719
11 201619
12 202416
13 202316
14 201814
15 201512
16 201511
17 202210
18 20229
19 20229
20 20209

About Ali Braytee

Ali Braytee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Biomedical Engineering, having authored 56 papers that have together received 475 indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Multimodal Machine Learning Applications (5 papers), Structural Health Monitoring Techniques (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), AI in cancer detection (4 papers), Infrastructure Maintenance and Monitoring (4 papers), Membrane Separation Technologies (4 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Computational Mathematics (11 citations), Water Science and Technology (75 citations), Computer Vision and Pattern Recognition (106 citations), Artificial Intelligence (161 citations) and Civil and Structural Engineering (56 citations). Ali Braytee has collaborated with scholars based in Australia, India and China. Frequent co-authors include Paul Kennedy, Ali Anaissi, Daniel Catchpoole, Ali Altaee, Wei Liu, Madhu Goyal, Samir Mustapha, Mukesh Prasad, Osamah Naji and Wei Liu. Their work appears in journals such as Scientific Reports, Journal of Membrane Science, Energies, Lecture notes in computer science and VINE Journal of Information and Knowledge Management Systems.

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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