Amith Singhee

39 papers receiving 854 citations

Peers

Amith Singhee
Comparison fields: 5 of 62
  • Hardware and Architecture 394
  • Statistics, Probability and Uncertainty 124
  • Electrical and Electronic Engineering 696
  • Numerical Analysis 37
  • Management Science and Operations Research 46
Replace Kyung-Su Kang with:
Kyung-Su Kang South Korea
D.C. Yu United States
Steve Yang United States
Vanessa López United States
Clemens-August Thole Germany
Steve Chan United States
Martin Schlüter Germany
Shaun A. Forth United Kingdom
Vaibhav Donde United States
Kathleen M. Gegner United States
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Citations per field
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Citations per year

Countries citing papers authored by Amith Singhee

Since Specialization
Citations

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

Fields of papers citing papers by Amith Singhee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Amith Singhee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Amith Singhee Line = papers co-authored together Amith Singhee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010142
2 2009126
3 200784
4 200775
5 200754
6 200852
7 200743
8 200842
9 200230
10 201029
11 201929
12 200924
13 201020
14 201420
15 202114
16 200814
17 201113
18 20158
19 20178
20 20167

About Amith Singhee

Amith Singhee is a scholar working on Hardware and Architecture, Statistics, Probability and Uncertainty, Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality and Computational Theory and Mathematics, having authored 42 papers that have together received 888 indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (17 papers), VLSI and Analog Circuit Testing (13 papers), Probabilistic and Robust Engineering Design (8 papers), Advancements in Semiconductor Devices and Circuit Design (7 papers), VLSI and FPGA Design Techniques (7 papers), Integrated Circuits and Semiconductor Failure Analysis (5 papers), Semiconductor materials and devices (5 papers) and Power System Reliability and Maintenance (4 papers). The work is most often cited by research in Hardware and Architecture (394 citations), Statistics, Probability and Uncertainty (124 citations), Electrical and Electronic Engineering (696 citations), Numerical Analysis (37 citations) and Management Science and Operations Research (46 citations). Amith Singhee has collaborated with scholars based in United States, India and China. Frequent co-authors include Rob A. Rutenbar, Benton Highsmith Calhoun, Hongzhou Liu, Haijing Wang, Takashi Ando, Amit Ranjan Trivedi, Saibal Mukhopadhyay, Jagabondhu Hazra, Kaushik Das and Deva P. Seetharam. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IBM Journal of Research and Development, Bulletin of the American Meteorological Society, IEEE Transactions on Electron Devices and Lecture notes in electrical engineering.

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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