Anuj Pathania

1.1k citations
46 papers · 776 · h-index 16

Impact in

Papers in

Anuj Pathania

43 papers receiving 760 citations

Peers

Anuj Pathania
Comparison fields: 5 of 46
  • Hardware and Architecture 538
  • Computer Networks and Communications 438
  • Electrical and Electronic Engineering 418
  • Computer Vision and Pattern Recognition 120
  • Information Systems 87
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Citations per year

Countries citing papers authored by Anuj Pathania

Since Specialization
Citations

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

Fields of papers citing papers by Anuj Pathania

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014117
2 201978
3 201466
4 201558
5 201652
6 201633
7 201832
8 202125
9 201924
10 201524
11 201924
12 202123
13 202020
14 202218
15 201717
16 201916
17 202115
18 201612
19 201611
20 201811

About Anuj Pathania

Anuj Pathania is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Information Systems, having authored 46 papers that have together received 776 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (35 papers), Interconnection Networks and Systems (23 papers), Embedded Systems Design Techniques (10 papers), Low-power high-performance VLSI design (9 papers), Advanced Data Storage Technologies (9 papers), Advanced Memory and Neural Computing (8 papers), Distributed and Parallel Computing Systems (5 papers) and Advanced Neural Network Applications (5 papers). The work is most often cited by research in Hardware and Architecture (538 citations), Computer Networks and Communications (438 citations), Electrical and Electronic Engineering (418 citations), Computer Vision and Pattern Recognition (120 citations) and Information Systems (87 citations). Anuj Pathania has collaborated with scholars based in Singapore, Germany and Netherlands. Frequent co-authors include Tulika Mitra, Jörg Henkel, Alok Prakash, Muhammad Shafique, Thannirmalai Somu Muthukaruppan, Martin Rapp, Santiago Pagani, Zhaoying Li, Neeraj Goel and Vanchinathan Venkataramani. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ACM Transactions on Embedded Computing Systems, ACM SIGPLAN Notices and IEEE Transactions on Parallel and Distributed Systems.

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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