Mohammed Nazim Uddin

55 total papers · 590 total citations
40 papers, 325 citations indexed

About

Mohammed Nazim Uddin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Mohammed Nazim Uddin has authored 40 papers receiving a total of 325 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 9 papers in Information Systems. Recurrent topics in Mohammed Nazim Uddin's work include Recommender Systems and Techniques (6 papers), Artificial Intelligence in Healthcare (6 papers) and Smart Agriculture and AI (4 papers). Mohammed Nazim Uddin is often cited by papers focused on Recommender Systems and Techniques (6 papers), Artificial Intelligence in Healthcare (6 papers) and Smart Agriculture and AI (4 papers). Mohammed Nazim Uddin collaborates with scholars based in Bangladesh, South Korea and United States. Mohammed Nazim Uddin's co-authors include Seung-Bo Park, Mohammad Arif Hossain, Yeong Min Jang, Sohrab Hossain, Geun‐Sik Jo, S. M. Riazul Islam, Kyung Sup Kwak, Trong Hai Duong, Ngoc Thanh Nguyên and Geun Sik Jo and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Diagnostics.

In The Last Decade

Mohammed Nazim Uddin

35 papers receiving 300 citations

Author Peers

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

Author Last Decade Papers Cites
Mohammed Nazim Uddin 117 76 60 39 33 40 325
M. Hema 60 0.5× 47 0.6× 23 0.4× 26 0.7× 16 0.5× 46 288
Sunil Kumar 150 1.3× 73 1.0× 72 1.2× 15 0.4× 7 0.2× 25 356
Mohamed Doheir 111 0.9× 41 0.5× 81 1.4× 11 0.3× 21 0.6× 37 285
G. Pradeepini 91 0.8× 54 0.7× 41 0.7× 34 0.9× 25 0.8× 41 239
Anand Shanker Tewari 79 0.7× 141 1.9× 70 1.2× 20 0.5× 6 0.2× 35 287
Sujala D. Shetty 109 0.9× 90 1.2× 30 0.5× 4 0.1× 6 0.2× 32 269
Ahlam Almusharraf 77 0.7× 50 0.7× 32 0.5× 21 0.5× 49 1.5× 43 360
Ayat Alrosan 105 0.9× 69 0.9× 64 1.1× 3 0.1× 17 0.5× 23 302
Dost Muhammad Khan 127 1.1× 42 0.6× 77 1.3× 47 1.2× 42 1.3× 25 341
Muhammed J. A. Patwary 158 1.4× 37 0.5× 65 1.1× 26 0.7× 14 0.4× 43 357

Countries citing papers authored by Mohammed Nazim Uddin

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed Nazim Uddin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed Nazim Uddin. 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 Mohammed Nazim Uddin. The network helps show where Mohammed Nazim Uddin may publish in the future.

Co-authorship network of co-authors of Mohammed Nazim Uddin

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Nazim Uddin. A scholar is included among the top collaborators of Mohammed Nazim Uddin 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 Mohammed Nazim Uddin. Mohammed Nazim Uddin 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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