Sameer Khurana

615 citations
23 papers · 318 · h-index 9

Impact in

    • Music and Audio Processing
    • Speech and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Topic Modeling

Papers in

Sameer Khurana

19 papers receiving 304 citations

Peers

Sameer Khurana
Comparison fields: 5 of 63
  • Signal Processing 80
  • Artificial Intelligence 143
  • Molecular Biology 132
  • Computational Theory and Mathematics 26
  • Experimental and Cognitive Psychology 14
Replace Dukka B. KC with:
Dukka B. KC United States
Bihter Daş Türkiye
Catherine Breslin United Kingdom
Haoyong Zhang China
Jianwei Zhu China
David Goddeau United States
Advait Balaji United States
Diamantino Caseiro Portugal
Jaume Baixeries Spain
Danilo Horta Brazil
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Citations per field
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Dukka B. KC · 1×
Citations per year

Countries citing papers authored by Sameer Khurana

Since Specialization
Citations

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

Fields of papers citing papers by Sameer Khurana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018149
2 201633
3 201824
4 202323
5 202014
6 202014
7 20198
8 20178
9 20238
10 20228
11 20236
12 20246
13 20174
14 20244
15 20223
16 20232
17 20242
18 20251
19 20231
20 20250

About Sameer Khurana

Sameer Khurana is a scholar working on Artificial Intelligence, Signal Processing, Molecular Biology, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 318 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (15 papers), Music and Audio Processing (11 papers), Natural Language Processing Techniques (9 papers), Speech and Audio Processing (6 papers), Topic Modeling (4 papers), Robotics and Automated Systems (1 paper), Computational Drug Discovery Methods (1 paper) and Protein purification and stability (1 paper). The work is most often cited by research in Signal Processing (80 citations), Artificial Intelligence (143 citations), Molecular Biology (132 citations), Computational Theory and Mathematics (26 citations) and Experimental and Cognitive Psychology (14 citations). Sameer Khurana has collaborated with scholars based in United States, Qatar and France. Frequent co-authors include Reda Rawi, Gwo-Yu Chuang, Halima Bensmail, Raghvendra Mall, Khalid Kunji, James Glass, Ahmed Ali, Antoine Laurent, Leonid Karlinsky and Maryam Najafian. Their work appears in journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Open Journal of Signal Processing, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) and arXiv (Cornell University).

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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