Samyak Parajuli
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging
- Electrical and Electronic Engineering
- Aerospace Engineering
- Co-authors
- Steven BasartDan HendrycksDawn SongTyler ZhuSaurav KadavathJacob SteinhardtJustin GilmerFengqiu Wang
- Topics
- Digital Games and Media (2 papers)Educational Games and Gamification (2 papers)Artificial Intelligence in Games (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRadiology, Nuclear Medicine and Imaging
- Journals
- Machine Vision and Applications2021 IEEE/CVF International Conference on Computer Vision (ICCV)TU/e Research Portal
- Partner nations
- United StatesNetherlandsIndia
In The Last Decade
Samyak Parajuli
4 papers receiving 489 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 361
- Computer Vision and Pattern Recognition 314
- Radiology, Nuclear Medicine and Imaging 41
- Electrical and Electronic Engineering 20
- Aerospace Engineering 16
Countries citing papers authored by Samyak Parajuli
This map shows the geographic impact of Samyak Parajuli'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 Samyak Parajuli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samyak Parajuli more than expected).
Fields of papers citing papers by Samyak Parajuli
This network shows the impact of papers produced by Samyak Parajuli. 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 Samyak Parajuli. The network helps show where Samyak Parajuli may publish in the future.
Co-authorship network of co-authors of Samyak Parajuli
This figure shows the co-authorship network connecting the top 25 collaborators of Samyak Parajuli. A scholar is included among the top collaborators of Samyak Parajuli 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 Samyak Parajuli. Samyak Parajuli 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 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalizationbreakdown → | 503 |
About Samyak Parajuli
Samyak Parajuli is a scholar working on Developmental and Educational Psychology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 6 papers that have together received 510 indexed citations. Recurring topics across this work include Digital Games and Media (2 papers), Educational Games and Gamification (2 papers) and Artificial Intelligence in Games (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (314 citations), Artificial Intelligence (361 citations) and Radiology, Nuclear Medicine and Imaging (41 citations). Samyak Parajuli has collaborated with scholars based in United States, Netherlands and India. Frequent co-authors include Steven Basart, Dan Hendrycks, Dawn Song, Tyler Zhu, Saurav Kadavath, Jacob Steinhardt, Justin Gilmer, Fengqiu Wang, Norman Mu and Sek Chai. Their work appears in journals such as Machine Vision and Applications, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and TU/e Research Portal.
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.