Simran Khanuja
Impact in
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
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- Speech and Audio Processing
- Music and Audio Processing
Papers in
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- Natural Language Processing Techniques 5
- Topic Modeling 5
- Speech Recognition and Synthesis 3
- Sentiment Analysis and Opinion Mining 1
- Speech and dialogue systems 1
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- Multimodal Machine Learning Applications 1
- Co-authors
- Alexis Conneau (2 shared papers)Ankur Bapna (2 shared papers)Vera Axelrod (2 shared papers)Jason Riesa (2 shared papers)Yu Zhang (1 shared paper)Min Ma (1 shared paper)Siddharth Dalmia (1 shared paper)Clara E. Rivera (1 shared paper)
- Journals
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)Interspeech 2022 (1 paper)
- Partner nations
- United StatesHong KongUnited Arab Emirates
In The Last Decade
Simran Khanuja
8 papers receiving 95 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 97
- Signal Processing 21
- Hardware and Architecture 2
- Computer Vision and Pattern Recognition 6
- Language and Linguistics 3
Countries citing papers authored by Simran Khanuja
This map shows the geographic impact of Simran Khanuja'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 Simran Khanuja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simran Khanuja more than expected).
Fields of papers citing papers by Simran Khanuja
This network shows the impact of papers produced by Simran Khanuja. 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 Simran Khanuja. The network helps show where Simran Khanuja may publish in the future.
Co-authors
The 25 scholars most cited alongside Simran Khanuja, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 73 | |
| 2 | 2022 | 10 | |
| 3 | 2023 | 6 | |
| 4 | 2023 | 6 | |
| 5 | 2023 | 5 | |
| 6 | 2021 | 4 | |
| 7 | 2024 | 3 | |
| 8 | 2019 | 2 |
About Simran Khanuja
Simran Khanuja is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Visual Arts and Performing Arts and Infectious Diseases, having authored 8 papers that have together received 109 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (5 papers), Topic Modeling (5 papers), Speech Recognition and Synthesis (3 papers), Aesthetic Perception and Analysis (1 paper), Visual Culture and Art Theory (1 paper), Multimodal Machine Learning Applications (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and Speech and dialogue systems (1 paper). The work is most often cited by research in Artificial Intelligence (97 citations), Signal Processing (21 citations), Hardware and Architecture (2 citations), Computer Vision and Pattern Recognition (6 citations) and Language and Linguistics (3 citations). Simran Khanuja has collaborated with scholars based in United States, Hong Kong and United Arab Emirates. Frequent co-authors include Alexis Conneau, Ankur Bapna, Vera Axelrod, Jason Riesa, Yu Zhang, Min Ma, Siddharth Dalmia, Clara E. Rivera, Partha Talukdar and Melvin Johnson. Their work appears in journals such as Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Interspeech 2022.
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.