S. Abubakar

19 total papers · 604 total citations
13 papers, 467 citations indexed

About

S. Abubakar is a scholar working on Water Science and Technology, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, S. Abubakar has authored 13 papers receiving a total of 467 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Water Science and Technology, 2 papers in Industrial and Manufacturing Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in S. Abubakar's work include Adsorption and biosorption for pollutant removal (3 papers), Water Quality and Pollution Assessment (2 papers) and Heavy Metal Pollution Remediation (2 papers). S. Abubakar is often cited by papers focused on Adsorption and biosorption for pollutant removal (3 papers), Water Quality and Pollution Assessment (2 papers) and Heavy Metal Pollution Remediation (2 papers). S. Abubakar collaborates with scholars based in Nigeria, Malaysia and United Kingdom. S. Abubakar's co-authors include Ibrahim Mohammed Lawal, Ahmad Hussaini Jagaba, Isaac John Umaru, S. R. M. Kutty, Aiban Abdulhakim Saeed Ghaleb, Najib Mohammed Yahya Almahbashi, Ibrahim Hassan, Azmatullah Noor, Gasim Hayder and Baker Nasser Saleh Al-dhawi and has published in prestigious journals such as IEEE Access, Journal of Environmental Management and Journal of Water Process Engineering.

In The Last Decade

S. Abubakar

11 papers receiving 450 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
S. Abubakar	201	131	112	52	41	13	467
Changgil Son	214 1.1×	150 1.1×	76 0.7×	62 1.2×	33 0.8×	18	438
S. Kanmani	141 0.7×	169 1.3×	120 1.1×	57 1.1×	49 1.2×	13	405
Qian Tang	150 0.7×	59 0.5×	98 0.9×	73 1.4×	34 0.8×	27	439
Joachim Behrendt	203 1.0×	191 1.5×	141 1.3×	63 1.2×	41 1.0×	29	448
Gerardo Coppola	109 0.5×	49 0.4×	91 0.8×	68 1.3×	28 0.7×	16	452
Hossein Ghiasinejad	179 0.9×	79 0.6×	39 0.3×	49 0.9×	40 1.0×	12	411
Tuoyuan Cheng	192 1.0×	85 0.6×	61 0.5×	43 0.8×	92 2.2×	12	494
Saeeda Yousaf	108 0.5×	121 0.9×	173 1.5×	51 1.0×	24 0.6×	19	451
Dong Wang	139 0.7×	110 0.8×	43 0.4×	41 0.8×	101 2.5×	16	483
Si Wan	134 0.7×	59 0.5×	65 0.6×	137 2.6×	30 0.7×	24	408

Countries citing papers authored by S. Abubakar

Since Specialization

Citations

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

Fields of papers citing papers by S. Abubakar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Abubakar

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

All Works

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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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