Sushil Subramanian

467 total citations
17 papers, 161 citations indexed

About

Sushil Subramanian is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sushil Subramanian has authored 17 papers receiving a total of 161 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Electrical and Electronic Engineering, 6 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sushil Subramanian's work include Quantum and electron transport phenomena (4 papers), Quantum Computing Algorithms and Architecture (4 papers) and VLSI and Analog Circuit Testing (3 papers). Sushil Subramanian is often cited by papers focused on Quantum and electron transport phenomena (4 papers), Quantum Computing Algorithms and Architecture (4 papers) and VLSI and Analog Circuit Testing (3 papers). Sushil Subramanian collaborates with scholars based in India, United States and Netherlands. Sushil Subramanian's co-authors include Todor Mladenov, Stefano Pellerano, Jong-Seok Park, Satoshi Suzuki, Shavindra Premaratne, Mustafijur Rahman, Esdras Juarez-Hernandez, Thomas F. Watson, Hossein Hashemi and Bishnu Patra and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, Pattern Recognition and Information Sciences.

In The Last Decade

Sushil Subramanian

14 papers receiving 155 citations

Peers

Sushil Subramanian
Comparison fields: 5 of 20
  • Electrical and Electronic Engineering 111
  • Atomic and Molecular Physics, and Optics 76
  • Artificial Intelligence 41
  • Biomedical Engineering 24
  • Computer Vision and Pattern Recognition 18
Replace Safeen Huda with:
Safeen Huda Canada
Eric Chang United States
Ghasem Pasandi United States
Kenichi Ohhata Japan
Zhouyi Hu Hong Kong
Haokun Li China
Jiahao Huo China
Sjoerd van der Heide Netherlands
Juliana Müller Germany
Safeen Huda Canada View profile →
Citations per field, relative to Sushil Subramanian
Sushil Subramanian · 1×
Citations per year, relative to Sushil Subramanian
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Countries citing papers authored by Sushil Subramanian

Since Specialization
Citations

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

Fields of papers citing papers by Sushil Subramanian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sushil Subramanian

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

All Works

17 of 17 papers shown
# Work Indexed citations
1 5
2 23
3 58
4 38
5 0
6 1
7 1
8 4
9 4
10 6
11 3
12 1
13 2
14 3
15 2
16 1
17 9

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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