Sumanth Doddapaneni
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Signal Processing
- Information Systems
- Computer Networks and Communications
- Co-authors
- Mitesh M. KhapraShreya GoyalBalaraman RavindranAnoop KunchukuttanPratyush KumarG. RameshSujit Kumar SahooDivyanshu Kakwani
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (7 papers)Speech Recognition and Synthesis (4 papers)
- Journals
- ACM Computing SurveysTransactions of the Association for Computational LinguisticsSN Computer Science
- Partner nations
- IndiaUnited KingdomUnited States
In The Last Decade
Sumanth Doddapaneni
14 papers receiving 192 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 179
- Computer Vision and Pattern Recognition 38
- Signal Processing 27
- Information Systems 10
- Computer Networks and Communications 9
Countries citing papers authored by Sumanth Doddapaneni
This map shows the geographic impact of Sumanth Doddapaneni'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 Sumanth Doddapaneni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumanth Doddapaneni more than expected).
Fields of papers citing papers by Sumanth Doddapaneni
This network shows the impact of papers produced by Sumanth Doddapaneni. 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 Sumanth Doddapaneni. The network helps show where Sumanth Doddapaneni may publish in the future.
Co-authorship network of co-authors of Sumanth Doddapaneni
This figure shows the co-authorship network connecting the top 25 collaborators of Sumanth Doddapaneni. A scholar is included among the top collaborators of Sumanth Doddapaneni 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 Sumanth Doddapaneni. Sumanth Doddapaneni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 63 | |
| 7 | 17 | |
| 8 | 2 | |
| 9 | 9 | |
| 10 | 13 | |
| 11 | 64 | |
| 12 | 3 | |
| 13 | 22 | |
| 14 | Bitions@DravidianLangTech-EACL2021: Ensemble of Multilingual Language Models with Pseudo Labeling for offence Detection in Dravidian Languages | 1 |
About Sumanth Doddapaneni
Sumanth Doddapaneni is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 14 papers that have together received 208 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers) and Speech Recognition and Synthesis (4 papers). The work is most often cited by research in Artificial Intelligence (179 citations), Signal Processing (27 citations) and Computer Vision and Pattern Recognition (38 citations). Sumanth Doddapaneni has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Mitesh M. Khapra, Shreya Goyal, Balaraman Ravindran, Anoop Kunchukuttan, Pratyush Kumar, G. Ramesh, Sujit Kumar Sahoo, Divyanshu Kakwani, V. Raghavan and Pratyush Kumar. Their work appears in journals such as ACM Computing Surveys, Transactions of the Association for Computational Linguistics and SN Computer Science.
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.