Kuldeep Singh
- Artificial Intelligence top 10%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Co-authors
- Anant GuptaSaeedeh ShekarpourJens LehmannSören AuerMaría-Esther VidalFabrizio OrlandiMohamad Yaser JaradehAndreas Both
- Topics
- Topic Modeling (14 papers)Natural Language Processing Techniques (11 papers)Semantic Web and Ontologies (10 papers)
- Cited by
- Artificial IntelligenceGeography, Planning and DevelopmentManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessKnowledge and Information Systems
- Partner nations
- GermanyUnited StatesIndia
In The Last Decade
Kuldeep Singh
23 papers receiving 217 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 184
- Information Systems 55
- Management Science and Operations Research 39
- Molecular Biology 26
- Computer Vision and Pattern Recognition 23
Countries citing papers authored by Kuldeep Singh
This map shows the geographic impact of Kuldeep Singh'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 Kuldeep Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuldeep Singh more than expected).
Fields of papers citing papers by Kuldeep Singh
This network shows the impact of papers produced by Kuldeep Singh. 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 Kuldeep Singh. The network helps show where Kuldeep Singh may publish in the future.
Co-authorship network of co-authors of Kuldeep Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Kuldeep Singh. A scholar is included among the top collaborators of Kuldeep Singh 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 Kuldeep Singh. Kuldeep Singh 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 | 15 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | Context-aware Entity Linking with Attentive Neural Networks on Wikidata Knowledge Graph | 1 |
| 13 | 38 | |
| 14 | 30 | |
| 15 | 33 | |
| 16 | 17 | |
| 17 | 9 | |
| 18 | 9 | |
| 19 | The Behavior of Temperature on Insulated(MgZrO 3 ) Diesel Engine Piston With ANSYS | 1 |
| 20 | 8 |
About Kuldeep Singh
Kuldeep Singh is a scholar working on Artificial Intelligence, Geography, Planning and Development and Information Systems, having authored 25 papers that have together received 238 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (11 papers) and Semantic Web and Ontologies (10 papers). The work is most often cited by research in Artificial Intelligence (184 citations), Geography, Planning and Development (22 citations) and Management Science and Operations Research (39 citations). Kuldeep Singh has collaborated with scholars based in Germany, United States and India. Frequent co-authors include Anant Gupta, Saeedeh Shekarpour, Jens Lehmann, Sören Auer, María-Esther Vidal, Fabrizio Orlandi, Mohamad Yaser Jaradeh, Andreas Both, Christoph Lange and Johannes Hoffart. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Knowledge and Information Systems.
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.