Jon Saad-Falcon
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Signal Processing
- Computer Networks and Communications
- Co-authors
- Christopher PottsOmar KhattabMatei ZahariaKeshav SanthanamArman CohanOmar ShaikhAmanpreet SinghLuca Soldaini
- Topics
- Topic Modeling (5 papers)Natural Language Processing Techniques (3 papers)Multimodal Machine Learning Applications (2 papers)
- Journals
- Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language TechnologiesProceedings of the 31st ACM International Conference on Information & Knowledge Management
- Partner nations
- United States
In The Last Decade
Jon Saad-Falcon
9 papers receiving 156 citations
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 127
- Computer Vision and Pattern Recognition 52
- Information Systems 35
- Signal Processing 7
- Computer Networks and Communications 6
Countries citing papers authored by Jon Saad-Falcon
This map shows the geographic impact of Jon Saad-Falcon'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 Jon Saad-Falcon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Saad-Falcon more than expected).
Fields of papers citing papers by Jon Saad-Falcon
This network shows the impact of papers produced by Jon Saad-Falcon. 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 Jon Saad-Falcon. The network helps show where Jon Saad-Falcon may publish in the future.
Co-authorship network of co-authors of Jon Saad-Falcon
This figure shows the co-authorship network connecting the top 25 collaborators of Jon Saad-Falcon. A scholar is included among the top collaborators of Jon Saad-Falcon 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 Jon Saad-Falcon. Jon Saad-Falcon 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 | 30 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | 114 | |
| 8 | 2 | |
| 9 | 5 |
About Jon Saad-Falcon
Jon Saad-Falcon is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 9 papers that have together received 170 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (3 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Artificial Intelligence (127 citations), Computer Vision and Pattern Recognition (52 citations) and Health Informatics (3 citations). Jon Saad-Falcon has collaborated with scholars based in United States. Frequent co-authors include Christopher Potts, Omar Khattab, Matei Zaharia, Keshav Santhanam, Arman Cohan, Omar Shaikh, Amanpreet Singh, Luca Soldaini, Radu Florian and Md Arafat Sultan. Their work appears in journals such as Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
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.