Sankit Kassa

422 citations
34 papers · 244 · h-index 9

Impact in

Papers in

Sankit Kassa

30 papers receiving 239 citations

Peers

Sankit Kassa
Comparison fields: 5 of 37
  • Computational Theory and Mathematics 165
  • Electrical and Electronic Engineering 169
  • Atomic and Molecular Physics, and Optics 55
  • Industrial and Manufacturing Engineering 12
  • Artificial Intelligence 32
Replace Zhufei Chu with:
Zhufei Chu China
Kyle Hsu United States
Min Feng China
Nohpill Park United States
Daniel Rehfeldt Germany
N. Prasanth Anthapadmanabhan United States
Sung‐Chuan Fang Taiwan
Anand Ganti United States
Valeriy Balabanov Taiwan
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Citations per field
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Citations per year

Countries citing papers authored by Sankit Kassa

Since Specialization
Citations

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

Fields of papers citing papers by Sankit Kassa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201538
2 201827
3 201725
4 202424
5 202313
6 202513
7 202510
8 20218
9 20238
10 20257
11 20167
12 20237
13 20247
14 20246
15 20176
16 20195
17 20235
18 20244
19 20164
20 20224

About Sankit Kassa

Sankit Kassa is a scholar working on Computational Theory and Mathematics, Electrical and Electronic Engineering, Biomedical Engineering, Atomic and Molecular Physics, and Optics and Artificial Intelligence, having authored 34 papers that have together received 244 indexed citations. Recurring topics across this work include Quantum-Dot Cellular Automata (28 papers), Advanced Memory and Neural Computing (16 papers), Advancements in Semiconductor Devices and Circuit Design (10 papers), Quantum and electron transport phenomena (6 papers), Semiconductor materials and devices (6 papers), Molecular Communication and Nanonetworks (5 papers), Quantum Computing Algorithms and Architecture (5 papers) and Low-power high-performance VLSI design (4 papers). The work is most often cited by research in Computational Theory and Mathematics (165 citations), Electrical and Electronic Engineering (169 citations), Atomic and Molecular Physics, and Optics (55 citations), Industrial and Manufacturing Engineering (12 citations) and Artificial Intelligence (32 citations). Sankit Kassa has collaborated with scholars based in India, Türkiye and Taiwan. Frequent co-authors include R. K. Nagaria, Seyed‐Sajad Ahmadpour, Neeraj Kumar Misra, R Karthik, Nima Jafari Navimipour, Ketan Kotecha, Narendar Vadthiya, Noor Ul Ain, Manoj Kumar and Thompson Stephan. Their work appears in journals such as Nano Communication Networks, Journal of Computational Electronics, Materials Science and Engineering B, Analog Integrated Circuits and Signal Processing and Engineering Applications of Artificial Intelligence.

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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