Robik Shrestha
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Health Informatics
- Radiology, Nuclear Medicine and Imaging
- Signal Processing
- Co-authors
- Christopher KananKushal KafleScott CohenBrian PriceDamien TeneyDavid D. B. BatesEhsan AbbasnejadGiuseppe Corrias
- Topics
- Multimodal Machine Learning Applications (5 papers)Domain Adaptation and Few-Shot Learning (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)
- Journals
- Frontiers in Artificial IntelligenceFrontiers in Digital HealthAdelaide Research & Scholarship (AR&S) (University of Adelaide)
- Partner nations
- United StatesAustraliaItaly
In The Last Decade
Robik Shrestha
7 papers receiving 120 citations
Peers
Comparison fields: 5 of 28
- Computer Vision and Pattern Recognition 102
- Artificial Intelligence 98
- Health Informatics 5
- Radiology, Nuclear Medicine and Imaging 5
- Signal Processing 4
Countries citing papers authored by Robik Shrestha
This map shows the geographic impact of Robik Shrestha'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 Robik Shrestha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robik Shrestha more than expected).
Fields of papers citing papers by Robik Shrestha
This network shows the impact of papers produced by Robik Shrestha. 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 Robik Shrestha. The network helps show where Robik Shrestha may publish in the future.
Co-authorship network of co-authors of Robik Shrestha
This figure shows the co-authorship network connecting the top 25 collaborators of Robik Shrestha. A scholar is included among the top collaborators of Robik Shrestha 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 Robik Shrestha. Robik Shrestha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 10 | |
| 3 | 10 | |
| 4 | On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law | 7 |
| 5 | 31 | |
| 6 | 17 | |
| 7 | 49 |
About Robik Shrestha
Robik Shrestha is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 7 papers that have together received 126 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (5 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (102 citations), Health Informatics (5 citations) and Artificial Intelligence (98 citations). Robik Shrestha has collaborated with scholars based in United States, Australia and Italy. Frequent co-authors include Christopher Kanan, Kushal Kafle, Scott Cohen, Brian Price, Damien Teney, David D. B. Bates, Ehsan Abbasnejad, Giuseppe Corrias, Yusuf E. Erdi and Anton van den Hengel. Their work appears in journals such as Frontiers in Artificial Intelligence, Frontiers in Digital Health and Adelaide Research & Scholarship (AR&S) (University of Adelaide).
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.