Angshuman Parashar

38 papers receiving 2.1k citations

Hit Papers

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Peers

Angshuman Parashar
Comparison fields: 5 of 63
  • Electrical and Electronic Engineering 1.1k
  • Computer Vision and Pattern Recognition 978
  • Hardware and Architecture 973
  • Artificial Intelligence 588
  • Computer Networks and Communications 560
Replace Rangharajan Venkatesan with:
Rangharajan Venkatesan United States
Yakun Sophia Shao United States
Xuehai Qian United States
Hyoukjun Kwon United States
Anurag Mukkara United States
Minsoo Rhu South Korea
Zidong Du China
Jing Pu United States
Jingwen Leng China
Michael Pellauer United States
Angshuman Parashar relative to Rangharajan Venkatesan United States Rangharajan Venkatesan's profile →
Citations per field
00.5×1.5×
Rangharajan Venkatesan · 1×
Citations per year

Countries citing papers authored by Angshuman Parashar

Since Specialization
Citations

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

Fields of papers citing papers by Angshuman Parashar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Angshuman Parashar

This figure shows the co-authorship network connecting the top 25 collaborators of Angshuman Parashar. A scholar is included among the top collaborators of Angshuman Parashar 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 Angshuman Parashar. Angshuman Parashar 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 16
3 1
4 3
5 2
6 10
7 17
8 116
9 6
10
Timeloop: A Systematic Approach to DNN Accelerator Evaluationbreakdown →
344
11
A Data-Centric Approach for Modeling and Estimating Efficiency of Dataflows for Accelerator Design
5
12
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach
3
13 276
14 11
15 25
16 27
17 62
18 49
19 9
20 39

About Angshuman Parashar

Angshuman Parashar is a scholar working on Computational Mathematics, Hardware and Architecture and Computer Networks and Communications, having authored 38 papers that have together received 2.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (25 papers), Advanced Neural Network Applications (12 papers) and Embedded Systems Design Techniques (9 papers). The work is most often cited by research in Hardware and Architecture (973 citations), Computational Mathematics (69 citations) and Computer Vision and Pattern Recognition (978 citations). Angshuman Parashar has collaborated with scholars based in United States, United Kingdom and Malaysia. Frequent co-authors include Joel Emer, Brucek Khailany, Anurag Mukkara, Rangharajan Venkatesan, Michael Pellauer, Stephen W. Keckler, William J. Dally, Antonio Puglielli, Minsoo Rhu and Tushar Krishna. Their work appears in journals such as Image and Vision Computing, ACM Transactions on Computer Systems and ACM SIGPLAN Notices.

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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