Debashis De

9.0k citations
439 papers · 5.5k indexed · 1 hit paper · h-index 35

Debashis De

407 papers receiving 5.3k citations

Hit Papers

Internet of Things (IoT) for Smart Precision Agriculture ...4012018202620202023100200300400

Peers

Debashis De
Comparison fields: 5 of 165
  • Computational Theory and Mathematics 1.4k
  • Computer Networks and Communications 1.7k
  • Electrical and Electronic Engineering 2.9k
  • Information Systems 555
  • Computer Vision and Pattern Recognition 426
Replace Mehdi Hosseinzadeh with:
Mehdi Hosseinzadeh Iran
Ashutosh Kumar Singh India
Songfeng Lu China
Sotirios K. Goudos Greece
Fagen Li China
Ákos Lédeczi United States
Lu Wang China
Sanguthevar Rajasekaran United States
Jianping Wang China
Yushu Zhang China
Debashis De relative to Mehdi Hosseinzadeh Iran Mehdi Hosseinzadeh's profile →
Citations per field
00.5×3.9×
Mehdi Hosseinzadeh · 1×
Citations per year

Countries citing papers authored by Debashis De

Since Specialization
Citations

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

Fields of papers citing papers by Debashis De

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
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3 20245
4 20241
5 20241
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14 20221
15 202253
16 20214
17 202116
18 20196
19 20184
20
A novel approach of And-Or-Inverter (AOI) gate design for QCA
200918

About Debashis De

Debashis De is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Information Systems, having authored 439 papers that have together received 5.5k indexed citations. Recurring topics across this work include Quantum-Dot Cellular Automata (108 papers), Advanced Memory and Neural Computing (77 papers), IoT and Edge/Fog Computing (66 papers), Quantum and electron transport phenomena (48 papers), Advancements in Semiconductor Devices and Circuit Design (47 papers), Energy Efficient Wireless Sensor Networks (35 papers), Advanced MIMO Systems Optimization (35 papers) and Cellular Automata and Applications (27 papers). The work is most often cited by research in Computational Theory and Mathematics (1.4k citations), Computer Networks and Communications (1.7k citations), Electrical and Electronic Engineering (2.9k citations), Information Systems (555 citations) and Computer Vision and Pattern Recognition (426 citations). Debashis De has collaborated with scholars based in India, Australia and Malaysia. Frequent co-authors include Jadav Chandra Das, Anwesha Mukherjee, Nurzaman Ahmed, Md. Iftekhar Hussain, Partha Pratim Ray, Dinesh Dash, Manash Chanda, Amit Bhattacharyya, Kunal Das and Deepsubhra Guha Roy. Their work appears in journals such as Microsystem Technologies, Wireless Personal Communications, IET Nanobiotechnology, Nano Communication Networks and IEEE Access.

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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