Prashant Sridhar

611 citations
12 papers · 337 · h-index 7

Impact in

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

Papers in

    • Speech Recognition and Synthesis 11
    • Natural Language Processing Techniques 6
    • Topic Modeling 2
    • Advanced Text Analysis Techniques 1
    • Speech and dialogue systems 1
    • Speech and Audio Processing 6
    • Music and Audio Processing 4

Prashant Sridhar

10 papers receiving 318 citations

Peers

Prashant Sridhar
Comparison fields: 5 of 33
  • Signal Processing 260
  • Artificial Intelligence 276
  • Computational Mechanics 24
  • Computer Vision and Pattern Recognition 18
  • Cognitive Neuroscience 15
Replace Chenda Li with:
Chenda Li China
Aswin Shanmugam Subramanian United States
Matt Shannon United Kingdom
Ladislav Mošner Czechia
Zelin Wu United States
Naoyuki Kamo Japan
Soyeon Choe South Korea
Hsin-Te Hwang Taiwan
Deyi Tuo China
Prashant Sridhar relative to Chenda Li China Chenda Li's profile →
Citations per field
00.5×10×16×
Chenda Li · 1×
Citations per year

Countries citing papers authored by Prashant Sridhar

Since Specialization
Citations

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

Fields of papers citing papers by Prashant Sridhar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2019217
2 202344
3 201930
4 202315
5 20239
6 20197
7 20236
8 20215
9 20243
10 20241
11 20240
12 20240

About Prashant Sridhar

Prashant Sridhar is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Infectious Diseases and Organic Chemistry, having authored 12 papers that have together received 337 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (11 papers), Speech and Audio Processing (6 papers), Natural Language Processing Techniques (6 papers), Music and Audio Processing (4 papers), Topic Modeling (2 papers), Advanced Text Analysis Techniques (1 paper), Advanced Data Compression Techniques (1 paper) and Speech and dialogue systems (1 paper). The work is most often cited by research in Signal Processing (260 citations), Artificial Intelligence (276 citations), Computational Mechanics (24 citations), Computer Vision and Pattern Recognition (18 citations) and Cognitive Neuroscience (15 citations). Prashant Sridhar has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Ignacio López Moreno, Hannah Muckenhirn, Kevin Wilson, Zelin Wu, Ron J. Weiss, Quan Wang, Jia Ye, John R. Hershey, Rif A. Saurous and Kwangyoun Kim.

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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