Divya Mahajan

1.3k citations
31 papers · 873 indexed · 1 hit paper · h-index 13
Topics
Parallel Computing and Optimization Techniques (12 papers)Low-power high-performance VLSI design (7 papers)Embedded Systems Design Techniques (7 papers)

In The Last Decade

Divya Mahajan

28 papers receiving 849 citations

Hit Papers

From high-level deep neural models to FPGAs2016202620192022201650100150200250

Peers

Divya Mahajan
Comparison fields: 5 of 61
  • Electrical and Electronic Engineering 536
  • Hardware and Architecture 380
  • Computer Vision and Pattern Recognition 266
  • Artificial Intelligence 213
  • Computer Networks and Communications 205
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Amir Yazdanbakhsh United States
Ben Keller United States
Emmanuel Amaro United States
Cody Hao Yu United States
Hardik Sharma United States
Kalin Ovtcharov Canada
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Citations per field
00.5×1.5×1.9×
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Citations per year

Countries citing papers authored by Divya Mahajan

Since Specialization
Citations

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

Fields of papers citing papers by Divya Mahajan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Divya Mahajan

This figure shows the co-authorship network connecting the top 25 collaborators of Divya Mahajan. A scholar is included among the top collaborators of Divya Mahajan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Divya Mahajan. Divya Mahajan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 0
3 1
4 0
5 5
6 0
7 2
8 7
9 25
10 6
11 28
12 2
13 1
14 29
15 173
16 32
17 2
18 11
19 31
20 17

About Divya Mahajan

Divya Mahajan is a scholar working on Hardware and Architecture, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 873 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (12 papers), Low-power high-performance VLSI design (7 papers) and Embedded Systems Design Techniques (7 papers). The work is most often cited by research in Hardware and Architecture (380 citations), Computational Mathematics (12 citations) and Computer Vision and Pattern Recognition (266 citations). Divya Mahajan has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Hadi Esmaeilzadeh, Jongse Park, Amir Yazdanbakhsh, Joon Kyung Kim, Hardik Sharma, Emmanuel Amaro, Pejman Lotfi-Kamran, Asit Mishra, Bradley Thwaites and Ziliang Zong. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGPLAN Notices and IEEE Micro.

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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