K. Singhal

1.6k citations
56 papers · 1.2k indexed · h-index 18

K. Singhal

51 papers receiving 1.1k citations

Peers

K. Singhal
Comparison fields: 5 of 140
  • Statistics and Probability 138
  • Hardware and Architecture 96
  • Statistics, Probability and Uncertainty 76
  • Electrical and Electronic Engineering 582
  • Computational Theory and Mathematics 119
Replace Pras Pathmanathan with:
Pras Pathmanathan United States
Peter Arbenz Switzerland
Feng‐Hsiag Hsiao Taiwan
A. Di Bucchianico Netherlands
Κ.J. Åström Sweden
Ali Muhammad Ali Rushdi Saudi Arabia
M. C. Bartholomew‐Biggs United Kingdom
Ariela Sofer United States
Mehmet Şahinoglu United States
Marco Aurélio C. Pacheco Brazil
K. Singhal relative to Pras Pathmanathan United States Pras Pathmanathan's profile →
Citations per field
00.5×4.9×
Pras Pathmanathan · 1×
Citations per year

Countries citing papers authored by K. Singhal

Since Specialization
Citations

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

Fields of papers citing papers by K. Singhal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside K. Singhal, 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 K. Singhal Line = papers co-authored together K. Singhal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20051
2 20031
3 19901
4 198858
5 19886
6 198712
7 19860
8 198611
9 198530
10 198543
11 198446
12 19797
13 19792
14 1978181
15 197419
16 19747
17 197310
18 19731
19 197312
20 197111

About K. Singhal

K. Singhal is a scholar working on Computational Theory and Mathematics, Statistics and Probability, Signal Processing, Electrical and Electronic Engineering and Numerical Analysis, having authored 56 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advancements in Semiconductor Devices and Circuit Design (8 papers), Low-power high-performance VLSI design (8 papers), Analog and Mixed-Signal Circuit Design (7 papers), Digital Filter Design and Implementation (6 papers), Matrix Theory and Algorithms (6 papers), Sensor Technology and Measurement Systems (5 papers), Electromagnetic Compatibility and Noise Suppression (5 papers) and Electromagnetic Simulation and Numerical Methods (5 papers). The work is most often cited by research in Statistics and Probability (138 citations), Hardware and Architecture (96 citations), Statistics, Probability and Uncertainty (76 citations), Electrical and Electronic Engineering (582 citations) and Computational Theory and Mathematics (119 citations). K. Singhal has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include J. Vlach, Jerald F. Lawless, T.R. Viswanathan, K. Nagaraj, E.L. Heasell, Colin C. McAndrew, Milan Vlach, H. K. Kesavan, Steve McKinney and Antonio Ciampi. Their work appears in journals such as Electronics Letters, Mechanism and Machine Theory, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Electron Devices and Semiconductor Science and Technology.

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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