Sergey Feldman
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Advanced Text Analysis Techniques
- Semantic Web and Ontologies
- Health Informatics top 10%
Papers in
-
- Topic Modeling 11
- Natural Language Processing Techniques 10
- Advanced Graph Neural Networks 3
- Authorship Attribution and Profiling 3
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- Data Quality and Management 2
- Co-authors
- Russell Power (1 shared paper)Chandra Bhagavatula (1 shared paper)Waleed Ammar (1 shared paper)Madeleine van Zuylen (1 shared paper)Oren Etzioni (1 shared paper)Kyle Lo (1 shared paper)Elly Trepman (1 shared paper)Maya R. Gupta (3 shared papers)
- Journals
- AI Magazine (2 papers)Transactions of the Association for Computational Linguistics (1 paper)JAMA Network Open (1 paper)EClinicalMedicine (1 paper)Journal of Proteome Research (1 paper)
- Partner nations
- United StatesCanadaSpain
In The Last Decade
Sergey Feldman
23 papers receiving 676 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 424
- Health Informatics 13
- Information Systems 145
- Information Systems and Management 26
- General Social Sciences 10
Countries citing papers authored by Sergey Feldman
This map shows the geographic impact of Sergey Feldman'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 Sergey Feldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Feldman more than expected).
Fields of papers citing papers by Sergey Feldman
This network shows the impact of papers produced by Sergey Feldman. 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 Sergey Feldman. The network helps show where Sergey Feldman may publish in the future.
Co-authors
The 25 scholars most cited alongside Sergey Feldman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 228 | |
| 2 | 2018 | 125 | |
| 3 | 2019 | 114 | |
| 4 | 2009 | 60 | |
| 5 | 2023 | 28 | |
| 6 | 2009 | 27 | |
| 7 | 2022 | 25 | |
| 8 | 2022 | 18 | |
| 9 | 2023 | 16 | |
| 10 | 2021 | 15 | |
| 11 | 2020 | 12 | |
| 12 | 2010 | 11 | |
| 13 | 2009 | 8 | |
| 14 | 2009 | 5 | |
| 15 | Revisiting Stein's paradox: multi-task averaging | 2014 | 4 |
| 16 | 2026 | 3 | |
| 17 | 2022 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2025 | 2 | |
| 20 | 2011 | 1 |
About Sergey Feldman
Sergey Feldman is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Applied Psychology and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 709 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers), Biomedical Text Mining and Ontologies (3 papers), Advanced Graph Neural Networks (3 papers), Authorship Attribution and Profiling (3 papers), Caching and Content Delivery (2 papers), Face and Expression Recognition (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Artificial Intelligence (424 citations), Health Informatics (13 citations), Information Systems (145 citations), Information Systems and Management (26 citations) and General Social Sciences (10 citations). Sergey Feldman has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include Russell Power, Chandra Bhagavatula, Waleed Ammar, Madeleine van Zuylen, Oren Etzioni, Kyle Lo, Elly Trepman, Maya R. Gupta, Doug Downey and Santosh Kumar Srivastava. Their work appears in journals such as AI Magazine, Transactions of the Association for Computational Linguistics, JAMA Network Open, EClinicalMedicine and Journal of Proteome Research.
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.