Jeffrey Sorensen
- Artificial Intelligence top 0.5%
- Epidemiology
- Information Systems top 5%
- Signal Processing top 5%
- Sociology and Political Science top 10%
- Co-authors
- Aron CulottaLucy VassermanLucas DixonNithum ThainJohn LiImed ZitouniRuhi SarikayaDanai Khemasuwan
- Topics
- Natural Language Processing Techniques (16 papers)Topic Modeling (14 papers)Hate Speech and Cyberbullying Detection (12 papers)
- Partner nations
- United StatesGreeceFrance
In The Last Decade
Jeffrey Sorensen
54 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Artificial Intelligence 1.5k
- Epidemiology 244
- Information Systems 232
- Signal Processing 154
- Sociology and Political Science 144
Countries citing papers authored by Jeffrey Sorensen
This map shows the geographic impact of Jeffrey Sorensen'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 Jeffrey Sorensen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey Sorensen more than expected).
Fields of papers citing papers by Jeffrey Sorensen
This network shows the impact of papers produced by Jeffrey Sorensen. 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 Jeffrey Sorensen. The network helps show where Jeffrey Sorensen may publish in the future.
Co-authorship network of co-authors of Jeffrey Sorensen
This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey Sorensen. A scholar is included among the top collaborators of Jeffrey Sorensen 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 Jeffrey Sorensen. Jeffrey Sorensen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 53 | |
| 9 | 20 | |
| 10 | 135 | |
| 11 | 44 | |
| 12 | 31 | |
| 13 | 9 | |
| 14 | 22 | |
| 15 | 55 | |
| 16 | 17 | |
| 17 | Syntax Based Reordering with Automatically Derived Rules for Improved Statistical Machine Translation | 28 |
| 18 | 13 | |
| 19 | Statistical Natural Language Generation for Speech-to-Speech Machine Translation | 13 |
| 20 | Carcinomas of the digestive system in Denmark 1943-1956; cancer incidence in Denmark. VI. | 4 |
About Jeffrey Sorensen
Jeffrey Sorensen is a scholar working on Critical Care and Intensive Care Medicine, Artificial Intelligence and Applied Microbiology and Biotechnology, having authored 58 papers that have together received 2.2k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Topic Modeling (14 papers) and Hate Speech and Cyberbullying Detection (12 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Health Informatics (39 citations) and Critical Care and Intensive Care Medicine (134 citations). Jeffrey Sorensen has collaborated with scholars based in United States, Greece and France. Frequent co-authors include Aron Culotta, Lucy Vasserman, Lucas Dixon, Nithum Thain, John Li, Imed Zitouni, Ruhi Sarikaya, Danai Khemasuwan, Samuel M. Brown and Ithan D. Peltan. Their work appears in journals such as CHEST Journal, Critical Care Medicine and Transplantation.
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.