Bhavani Raskutti
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Signal Processing
- Co-authors
- Adam KowalczykIngrid ZukermanChristopher LeckieYingying WenPeter K. CampbellIan B. ThomasJonathan OliverMichael Niemann
- Topics
- Imbalanced Data Classification Techniques (4 papers)Natural Language Processing Techniques (4 papers)Text and Document Classification Technologies (3 papers)
- Journals
- International Journal of Human-Computer StudiesUser Modeling and User-Adapted InteractionACM SIGKDD Explorations Newsletter
- Partner nations
- AustraliaUnited States
In The Last Decade
Bhavani Raskutti
18 papers receiving 471 citations
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 424
- Information Systems 111
- Computer Vision and Pattern Recognition 98
- Electrical and Electronic Engineering 53
- Signal Processing 41
Countries citing papers authored by Bhavani Raskutti
This map shows the geographic impact of Bhavani Raskutti'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 Bhavani Raskutti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bhavani Raskutti more than expected).
Fields of papers citing papers by Bhavani Raskutti
This network shows the impact of papers produced by Bhavani Raskutti. 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 Bhavani Raskutti. The network helps show where Bhavani Raskutti may publish in the future.
Co-authorship network of co-authors of Bhavani Raskutti
This figure shows the co-authorship network connecting the top 25 collaborators of Bhavani Raskutti. A scholar is included among the top collaborators of Bhavani Raskutti 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 Bhavani Raskutti. Bhavani Raskutti 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 | 2 | |
| 3 | Supervised machine learning techniques for question answering | 1 |
| 4 | 3 | |
| 5 | 191 | |
| 6 | 5 | |
| 7 | 119 | |
| 8 | Using Unlabelled Data for Text Classification through Addition of Cluster Parameters | 18 |
| 9 | 25 | |
| 10 | 3 | |
| 11 | 30 | |
| 12 | 33 | |
| 13 | An evaluation of criteria for measuring the quality of clusters | 24 |
| 14 | 3 | |
| 15 | 15 | |
| 16 | 20 | |
| 17 | 3 | |
| 18 | 21 |
About Bhavani Raskutti
Bhavani Raskutti is a scholar working on Artificial Intelligence, Information Systems and Signal Processing, having authored 18 papers that have together received 517 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (4 papers), Natural Language Processing Techniques (4 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (424 citations), Information Systems (111 citations) and Computer Vision and Pattern Recognition (98 citations). Bhavani Raskutti has collaborated with scholars based in Australia and United States. Frequent co-authors include Adam Kowalczyk, Ingrid Zukerman, Christopher Leckie, Adam Kowalczyk, Yingying Wen, Peter K. Campbell, Ian B. Thomas, Jonathan Oliver, Michael Niemann and David Albrecht. Their work appears in journals such as International Journal of Human-Computer Studies, User Modeling and User-Adapted Interaction and ACM SIGKDD Explorations Newsletter.
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.