Rahaf Aljundi
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Radiology, Nuclear Medicine and Imaging top 10%
- Electrical and Electronic Engineering
- Control and Systems Engineering top 10%
- Co-authors
- Tinne TuytelaarsSarah ParisotMarc MasanaAleš LeonardisGreg SlabaughXu JiaPunarjay ChakravartyEugene Belilovsky
- Topics
- Domain Adaptation and Few-Shot Learning (13 papers)Multimodal Machine Learning Applications (6 papers)COVID-19 diagnosis using AI (5 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- SwitzerlandBelgiumCanada
In The Last Decade
Rahaf Aljundi
15 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 823
- Radiology, Nuclear Medicine and Imaging 156
- Electrical and Electronic Engineering 101
- Control and Systems Engineering 73
Countries citing papers authored by Rahaf Aljundi
This map shows the geographic impact of Rahaf Aljundi'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 Rahaf Aljundi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rahaf Aljundi more than expected).
Fields of papers citing papers by Rahaf Aljundi
This network shows the impact of papers produced by Rahaf Aljundi. 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 Rahaf Aljundi. The network helps show where Rahaf Aljundi may publish in the future.
Co-authorship network of co-authors of Rahaf Aljundi
This figure shows the co-authorship network connecting the top 25 collaborators of Rahaf Aljundi. A scholar is included among the top collaborators of Rahaf Aljundi 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 Rahaf Aljundi. Rahaf Aljundi 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 | 3 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 10 | |
| 6 | 25 | |
| 7 | 1 | |
| 8 | A continual learning survey: Defying forgetting in classification tasksbreakdown → | 974 |
| 9 | 49 | |
| 10 | 61 | |
| 11 | Online continual learning with no task boundaries. | 13 |
| 12 | Continual learning: A comparative study on how to defy forgetting in classification tasks. | 81 |
| 13 | Online Continual Learning with Maximal Interfered Retrieval | 109 |
| 14 | Selfless Sequential Learning | 11 |
| 15 | Expert Gate: Lifelong Learning with a Network of Expertsbreakdown → | 323 |
About Rahaf Aljundi
Rahaf Aljundi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 1.7k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (13 papers), Multimodal Machine Learning Applications (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (823 citations) and Radiology, Nuclear Medicine and Imaging (156 citations). Rahaf Aljundi has collaborated with scholars based in Switzerland, Belgium and Canada. Frequent co-authors include Tinne Tuytelaars, Sarah Parisot, Marc Masana, Aleš Leonardis, Greg Slabaugh, Xu Jia, Punarjay Chakravarty, Eugene Belilovsky, Min Lin and M. Caccia. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.