Manoj Sharma

89 total papers · 774 total citations
51 papers, 528 citations indexed

About

Manoj Sharma is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Modeling and Simulation. According to data from OpenAlex, Manoj Sharma has authored 51 papers receiving a total of 528 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Electrical and Electronic Engineering, 11 papers in Biomedical Engineering and 7 papers in Modeling and Simulation. Recurrent topics in Manoj Sharma's work include Low-power high-performance VLSI design (13 papers), Fractional Differential Equations Solutions (7 papers) and Advancements in Semiconductor Devices and Circuit Design (7 papers). Manoj Sharma is often cited by papers focused on Low-power high-performance VLSI design (13 papers), Fractional Differential Equations Solutions (7 papers) and Advancements in Semiconductor Devices and Circuit Design (7 papers). Manoj Sharma collaborates with scholars based in India, Saudi Arabia and Nepal. Manoj Sharma's co-authors include Bhishma Karki, Renu Jain, Arun Uniyal, Ram Bharos Yadav, Amrindra Pal, Abdullah Saad Alsubaie, Mohammad Ayoub Khan, Khaled H. Mahmoud, Partha Sarkar and Youssef Trabelsi and has published in prestigious journals such as Physica B Condensed Matter, Journal of Materials Science Materials in Electronics and IEEE photonics journal.

In The Last Decade

Manoj Sharma

45 papers receiving 481 citations

Hit Papers

Tuning sensitivity of bim... 2024 2026 2024 25 50 75

Author Peers

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

Author Last Decade Papers Cites
Manoj Sharma 248 216 128 75 52 51 528
Litao Zhang 38 0.2× 58 0.3× 54 0.4× 17 0.2× 4 0.1× 74 504
Ezzat G. Bakhoum 221 0.9× 181 0.8× 9 0.1× 17 0.2× 15 0.3× 57 576
Omar Kahouli 286 1.2× 47 0.2× 26 0.2× 57 0.8× 15 0.3× 58 480
Fanwei Meng 94 0.4× 63 0.3× 15 0.1× 74 1.0× 8 0.2× 44 580
Rafael Guzmán-Cabrera 108 0.4× 56 0.3× 19 0.1× 103 1.4× 16 0.3× 72 591
Jan‐Frederik Pietschmann 156 0.6× 145 0.7× 30 0.2× 79 1.1× 5 0.1× 32 617
Kai Zhang 277 1.1× 55 0.3× 124 1.0× 15 0.2× 14 0.3× 28 512
Jian Liu 131 0.5× 153 0.7× 55 0.4× 49 0.7× 3 0.1× 40 526
Christian Großmann 50 0.2× 69 0.3× 13 0.1× 15 0.2× 12 0.2× 48 600
Vassilis G. Papanicolaou 49 0.2× 42 0.2× 23 0.2× 9 0.1× 7 0.1× 46 562

Countries citing papers authored by Manoj Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Manoj Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manoj Sharma

This figure shows the co-authorship network connecting the top 25 collaborators of Manoj Sharma. A scholar is included among the top collaborators of Manoj Sharma 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 Manoj Sharma. Manoj Sharma 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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