Genta Indra Winata
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Signal Processing
- Language and Linguistics
- Co-authors
- Pascale FungZhaojiang LinAndrea MadottoZihan LiuSamuel CahyawijayaPeng XuChien-Sheng WuAlham Fikri Aji
- Topics
- Natural Language Processing Techniques (34 papers)Topic Modeling (30 papers)Speech Recognition and Synthesis (8 papers)
- Journals
- Machine Learning Science and TechnologyRare & Special e-Zone (The Hong Kong University of Science and Technology)Monash University Research Portal (Monash University)
- Partner nations
- Hong KongUnited StatesIndonesia
In The Last Decade
Genta Indra Winata
39 papers receiving 587 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 562
- Computer Vision and Pattern Recognition 82
- Information Systems 60
- Signal Processing 39
- Language and Linguistics 17
Countries citing papers authored by Genta Indra Winata
This map shows the geographic impact of Genta Indra Winata'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 Genta Indra Winata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Genta Indra Winata more than expected).
Fields of papers citing papers by Genta Indra Winata
This network shows the impact of papers produced by Genta Indra Winata. 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 Genta Indra Winata. The network helps show where Genta Indra Winata may publish in the future.
Co-authorship network of co-authors of Genta Indra Winata
This figure shows the co-authorship network connecting the top 25 collaborators of Genta Indra Winata. A scholar is included among the top collaborators of Genta Indra Winata 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 Genta Indra Winata. Genta Indra Winata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 25 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 6 | |
| 11 | 10 | |
| 12 | 5 | |
| 13 | 6 | |
| 14 | 45 | |
| 15 | 82 | |
| 16 | 28 | |
| 17 | 43 | |
| 18 | 41 | |
| 19 | 7 | |
| 20 | Nora the empathetic psychologist | 8 |
About Genta Indra Winata
Genta Indra Winata is a scholar working on Artificial Intelligence, Structural Biology and Linguistics and Language, having authored 45 papers that have together received 617 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (34 papers), Topic Modeling (30 papers) and Speech Recognition and Synthesis (8 papers). The work is most often cited by research in Artificial Intelligence (562 citations), Computer Vision and Pattern Recognition (82 citations) and Signal Processing (39 citations). Genta Indra Winata has collaborated with scholars based in Hong Kong, United States and Indonesia. Frequent co-authors include Pascale Fung, Zhaojiang Lin, Andrea Madotto, Zihan Liu, Samuel Cahyawijaya, Peng Xu, Chien-Sheng Wu, Alham Fikri Aji, Sebastian Ruder and Ayu Purwarianti. Their work appears in journals such as Machine Learning Science and Technology, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Monash University Research Portal (Monash 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.