Sushil Subramanian

29 total papers · 460 total citations
17 papers, 159 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 159 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 Analog and Mixed-Signal Circuit Design (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 Analog and Mixed-Signal Circuit Design (3 papers). Sushil Subramanian collaborates with scholars based in India, United States and Switzerland. Sushil Subramanian's co-authors include Todor Mladenov, Jong-Seok Park, Stefano Pellerano, Esdras Juarez-Hernandez, Thomas F. Watson, Shavindra Premaratne, Satoshi Suzuki, Mustafijur Rahman, Santanu Chaudhury and Hossein Hashemi 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 153 citations

Author Peers

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

Author						Papers	Cites
Sushil Subramanian	110	75	40	24	18	17	159
Federico Faggin	149 1.4×	30 0.4×	40 1.0×	26 1.1×	8 0.4×	19	242
Bruno Martin	91 0.8×	39 0.5×	37 0.9×	7 0.3×	14 0.8×	27	166
Ian Stobert	223 2.0×	69 0.9×	39 1.0×	47 2.0×	10 0.6×	20	263
Boris Zadov	67 0.6×	31 0.4×	38 0.9×	21 0.9×	18 1.0×	14	163
Safeen Huda	177 1.6×	66 0.9×	21 0.5×	17 0.7×	13 0.7×	17	251
Fredrik Jönsson	92 0.8×	38 0.5×	39 1.0×	35 1.5×	22 1.2×	16	165
Haokun Li	117 1.1×	174 2.3×	79 2.0×	12 0.5×	9 0.5×	20	198
Bo Fang	73 0.7×	80 1.1×	38 0.9×	26 1.1×	86 4.8×	19	211
Alex Chen	99 0.9×	23 0.3×	7 0.2×	24 1.0×	17 0.9×	20	154
Jean Rousset	150 1.4×	20 0.3×	12 0.3×	22 0.9×	5 0.3×	29	228

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

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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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