Aayush Ankit

1.8k citations
34 papers · 1.2k · h-index 16

Impact in

Papers in

Aayush Ankit

33 papers receiving 1.1k citations

Peers

Aayush Ankit
Comparison fields: 5 of 71
  • Hardware and Architecture 117
  • Electrical and Electronic Engineering 895
  • Artificial Intelligence 385
  • Computer Vision and Pattern Recognition 213
  • Cellular and Molecular Neuroscience 153
Replace Zhenhua Zhu with:
Zhenhua Zhu China
Syed Shakib Sarwar United States
Phil Knag United States
Michael DeBole United States
Shihui Yin United States
Takashi Morie Japan
Cheng-Xin Xue Taiwan
Shanshi Huang United States
Arindam Sanyal United States
Aayush Ankit relative to Zhenhua Zhu China Zhenhua Zhu's profile →
Citations per field
00.5×1.5×1.9×
Zhenhua Zhu · 1×
Citations per year

Countries citing papers authored by Aayush Ankit

Since Specialization
Citations

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

Fields of papers citing papers by Aayush Ankit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aayush Ankit, 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 Aayush Ankit Line = papers co-authored together Aayush Ankit 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 2019299
2 2022127
3 201994
4 202085
5 201880
6 201768
7 201856
8 202056
9 202030
10 202028
11 201726
12 202126
13 201825
14 202121
15 201720
16 201918
17 201715
18 202213
19 201713
20 201912

About Aayush Ankit

Aayush Ankit is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (28 papers), Ferroelectric and Negative Capacitance Devices (20 papers), CCD and CMOS Imaging Sensors (8 papers), Neural dynamics and brain function (7 papers), Machine Learning and ELM (5 papers), Semiconductor materials and devices (5 papers), Advanced Neural Network Applications (5 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Hardware and Architecture (117 citations), Electrical and Electronic Engineering (895 citations), Artificial Intelligence (385 citations), Computer Vision and Pattern Recognition (213 citations) and Cellular and Molecular Neuroscience (153 citations). Aayush Ankit has collaborated with scholars based in United States, India and Lebanon. Frequent co-authors include Kaushik Roy, Abhronil Sengupta, Indranil Chakraborty, Syed Shakib Sarwar, Priyadarshini Panda, Amogh Agrawal, Dejan Milojičić, John Paul Strachan, Wen‐mei Hwu and Paolo Faraboschi. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Micro, ACM Journal on Emerging Technologies in Computing Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and IBM Journal of Research and Development.

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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