Rusul Khaleel Ibrahim

1.9k citations
16 papers · 1.4k indexed · 1 hit paper · h-index 12

Rusul Khaleel Ibrahim

16 papers receiving 1.3k citations

Hit Papers

Machine learning methods for better water quality prediction4612019202620212023100200300400

Peers

Rusul Khaleel Ibrahim
Comparison fields: 5 of 118
  • Water Science and Technology 614
  • Catalysis 282
  • Environmental Engineering 440
  • Filtration and Separation 64
  • Industrial and Manufacturing Engineering 143
Replace Hassan Pahlavanzadeh with:
Hassan Pahlavanzadeh Iran
Li Fu China
Baolin Hou China
Wensheng Zhang Australia
Amid P. Khodadoust United States
Wookeun Bae South Korea
Soumyadeep Mukhopadhyay Malaysia
Daeseung Kyung South Korea
José Saldanha Matos Portugal
Pedro Robles Chile
Rusul Khaleel Ibrahim relative to Hassan Pahlavanzadeh Iran Hassan Pahlavanzadeh's profile →
Citations per field
00.5×
Hassan Pahlavanzadeh · 1×
Citations per year

Countries citing papers authored by Rusul Khaleel Ibrahim

Since Specialization
Citations

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

Fields of papers citing papers by Rusul Khaleel Ibrahim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rusul Khaleel 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 Rusul Khaleel Ibrahim. The network helps show where Rusul Khaleel Ibrahim may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Rusul Khaleel Ibrahim, 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 Rusul Khaleel Ibrahim Line = papers co-authored together Rusul Khaleel Ibrahim links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202021
2 202018
3 2019113
4 201917
5 201934
6
Machine learning methods for better water quality predictionbreakdown →
2019461
7 201974
8 2018226
9 20182
10 201810
11 201810
12 201717
13 201716
14 2016236
15 2016105
16 201011

About Rusul Khaleel Ibrahim

Rusul Khaleel Ibrahim is a scholar working on Catalysis, Electrochemistry and Water Science and Technology, having authored 16 papers that have together received 1.4k indexed citations. Recurring topics across this work include Ionic liquids properties and applications (6 papers), Hydrological Forecasting Using AI (4 papers), Electrochemical Analysis and Applications (3 papers), Water Quality Monitoring Technologies (2 papers), Ocean Waves and Remote Sensing (2 papers), Graphene and Nanomaterials Applications (2 papers), Adsorption and biosorption for pollutant removal (2 papers) and Analytical Chemistry and Sensors (2 papers). The work is most often cited by research in Water Science and Technology (614 citations), Catalysis (282 citations) and Environmental Engineering (440 citations). Rusul Khaleel Ibrahim has collaborated with scholars based in Malaysia, Oman and Egypt. Frequent co-authors include Mohammed Abdulhakim Alsaadi, Maan Hayyan, Shaliza Ibrahim, Ahmed El‐Shafie, Adeeb Hayyan, Haitham Abdulmohsin Afan, Ali Najah Ahmed, Chow Ming Fai, Faridah Othman and Mohammad Ehteram. Their work appears in journals such as Journal of Molecular Liquids, Sustainability, Water Science & Technology, Journal of Hydrology and Environmental Science and Pollution Research.

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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