Lajanugen Logeswaran
- Artificial Intelligence top 5%
- Topic Modeling 12
- Natural Language Processing Techniques 11
- Text Readability and Simplification 5
- Speech and dialogue systems 2
- AI in Service Interactions 2
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- Multimodal Machine Learning Applications 5
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- Mental Health Research Topics 1
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- Fuel Cells and Related Materials 1
- Journals
- arXiv (Cornell University) (3 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- United StatesSouth KoreaCanada
In The Last Decade
Lajanugen Logeswaran
15 papers receiving 235 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 235
- Health Informatics 6
- Computer Vision and Pattern Recognition 68
- General Social Sciences 4
- Information Systems 25
Countries citing papers authored by Lajanugen Logeswaran
This map shows the geographic impact of Lajanugen Logeswaran'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 Lajanugen Logeswaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lajanugen Logeswaran more than expected).
Fields of papers citing papers by Lajanugen Logeswaran
This network shows the impact of papers produced by Lajanugen Logeswaran. 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 Lajanugen Logeswaran. The network helps show where Lajanugen Logeswaran may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Lajanugen Logeswaran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 9 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 20 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 2 | |
| 12 | 2022 | 7 | |
| 13 | An efficient framework for learning sentence representations | 2018 | 75 |
| 14 | 2018 | 40 | |
| 15 | 2018 | 54 | |
| 16 | Sentence Ordering using Recurrent Neural Networks | 2017 | 9 |
| 17 | 2016 | 31 |
About Lajanugen Logeswaran
Lajanugen Logeswaran is a scholar working on Artificial Intelligence, Software, Computer Vision and Pattern Recognition, Human-Computer Interaction and Experimental and Cognitive Psychology, having authored 17 papers that have together received 264 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (11 papers), Multimodal Machine Learning Applications (5 papers), Text Readability and Simplification (5 papers), Speech and dialogue systems (2 papers), AI in Service Interactions (2 papers), Mental Health Research Topics (1 paper) and Fuel Cells and Related Materials (1 paper). The work is most often cited by research in Artificial Intelligence (235 citations), Health Informatics (6 citations), Computer Vision and Pattern Recognition (68 citations), General Social Sciences (4 citations) and Information Systems (25 citations). Lajanugen Logeswaran has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Honglak Lee, Dragomir Radev, Samy Bengio, David Jurgens, Sohee Yang, Sungmin Cha, Minjoon Seo, Yao Fu, Muhammad Khalifa and Lu Wang. Their work appears in journals such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.