Kunal Dahiya

430 citations
13 papers · 205 indexed · h-index 7
Topics
Text and Document Classification Technologies (4 papers)Machine Learning and Data Classification (4 papers)Building Energy and Comfort Optimization (3 papers)
Partner nations
IndiaJapanUnited States

In The Last Decade

Kunal Dahiya

12 papers receiving 189 citations

Peers

Kunal Dahiya
Comparison fields: 5 of 45
  • Computer Vision and Pattern Recognition 81
  • Artificial Intelligence 70
  • Mechanical Engineering 42
  • Media Technology 38
  • Automotive Engineering 35
Replace Markus Murschitz with:
Markus Murschitz Austria
Pengwen Dai China
Hanjiang Dong China
Yibing Zhao China
J. Surendiran India
Horng-Horng Lin Taiwan
Timothy Malche India
Thiago M. Paixão Brazil
Mukesh Kumar Maheshwari South Korea
Kavaskar Sekar India
Kunal Dahiya relative to Markus Murschitz Austria Markus Murschitz's profile →
Citations per field
00.5×3.2×
Markus Murschitz · 1×
Citations per year

Countries citing papers authored by Kunal Dahiya

Since Specialization
Citations

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

Fields of papers citing papers by Kunal Dahiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunal Dahiya

This figure shows the co-authorship network connecting the top 25 collaborators of Kunal Dahiya. A scholar is included among the top collaborators of Kunal Dahiya 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 Kunal Dahiya. Kunal Dahiya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 13
2 0
3 3
4 9
5 3
6 5
7 9
8 5
9 8
10
SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
9
11
DeepXML: Scalable & Accurate Deep Extreme Classification for Matching User Queries to Advertiser Bid Phrases
1
12 37
13 103

About Kunal Dahiya

Kunal Dahiya is a scholar working on Building and Construction, Artificial Intelligence and Environmental Engineering, having authored 13 papers that have together received 205 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (4 papers), Machine Learning and Data Classification (4 papers) and Building Energy and Comfort Optimization (3 papers). The work is most often cited by research in Media Technology (38 citations), Computer Vision and Pattern Recognition (81 citations) and Automotive Engineering (35 citations). Kunal Dahiya has collaborated with scholars based in India, Japan and United States. Frequent co-authors include C. Krishna Mohan, Dinesh Singh, Manik Varma, Yashoteja Prabhu, Rahul Agrawal, Hirozumi Yamaguchi, Aya Hagishima, Sumeet Agarwal, Purushottam Kar and Teruo Higashino. Their work appears in journals such as IEEE Access, Pervasive and Mobile Computing and Buildings.

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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