Srinivas Sunkara
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Speech and dialogue systems
- Natural Language Processing Techniques
- AI in Service Interactions
- Speech Recognition and Synthesis
- Domain Adaptation and Few-Shot Learning
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- Multimodal Machine Learning Applications
Papers in
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- Web Data Mining and Analysis 3
- Expert finding and Q&A systems 1
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- Topic Modeling 3
- Speech and dialogue systems 1
- AI in Service Interactions 1
- Co-authors
- Xiaoxue Zang (3 shared papers)Abhinav Rastogi (2 shared papers)Raghav Gupta (1 shared paper)Pranav Khaitan (1 shared paper)David Burstein (1 shared paper)Shabnam Jaffer (1 shared paper)Edmond Sabo (1 shared paper)Jindong Chen (3 shared papers)
- Journals
- Human Pathology (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Srinivas Sunkara
4 papers receiving 302 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 252
- Computer Vision and Pattern Recognition 54
- Human-Computer Interaction 10
- Information Systems 30
- Computer Science Applications 7
Countries citing papers authored by Srinivas Sunkara
This map shows the geographic impact of Srinivas Sunkara'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 Srinivas Sunkara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srinivas Sunkara more than expected).
Fields of papers citing papers by Srinivas Sunkara
This network shows the impact of papers produced by Srinivas Sunkara. 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 Srinivas Sunkara. The network helps show where Srinivas Sunkara may publish in the future.
Co-authors
The 14 scholars most cited alongside Srinivas Sunkara, 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 | 2020 | 248 | |
| 2 | 2007 | 34 | |
| 3 | 2021 | 25 | |
| 4 | 2021 | 13 | |
| 5 | 2025 | 0 |
About Srinivas Sunkara
Srinivas Sunkara is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology and Oncology, having authored 5 papers that have together received 320 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (3 papers), Topic Modeling (3 papers), Multimodal Machine Learning Applications (2 papers), Video Analysis and Summarization (1 paper), Speech and dialogue systems (1 paper), AI in Service Interactions (1 paper), Cell death mechanisms and regulation (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Artificial Intelligence (252 citations), Computer Vision and Pattern Recognition (54 citations), Human-Computer Interaction (10 citations), Information Systems (30 citations) and Computer Science Applications (7 citations). Srinivas Sunkara has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Xiaoxue Zang, Abhinav Rastogi, Raghav Gupta, Pranav Khaitan, David Burstein, Shabnam Jaffer, Edmond Sabo, Jindong Chen, Ruby Lee and Zecheng He. Their work appears in journals such as Human Pathology and Proceedings of the AAAI Conference on Artificial Intelligence.
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.