Suraj Maharjan
- Materials Chemistry top 10%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Molecular Biology
- Electrical and Electronic Engineering
- Co-authors
- Thamar SolorioLaijin LuNan ZhouShoujun ZhuXiaohuan ZhaoYubin SongBai YangJunhu Zhang
- Topics
- Natural Language Processing Techniques (10 papers)Topic Modeling (6 papers)Handwritten Text Recognition Techniques (5 papers)
- Partner nations
- United StatesChinaMexico
In The Last Decade
Suraj Maharjan
31 papers receiving 824 citations
Peers
Comparison fields: 5 of 107
- Materials Chemistry 426
- Artificial Intelligence 269
- Biomedical Engineering 107
- Molecular Biology 84
- Electrical and Electronic Engineering 55
Countries citing papers authored by Suraj Maharjan
This map shows the geographic impact of Suraj Maharjan'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 Suraj Maharjan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suraj Maharjan more than expected).
Fields of papers citing papers by Suraj Maharjan
This network shows the impact of papers produced by Suraj Maharjan. 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 Suraj Maharjan. The network helps show where Suraj Maharjan may publish in the future.
Co-authorship network of co-authors of Suraj Maharjan
This figure shows the co-authorship network connecting the top 25 collaborators of Suraj Maharjan. A scholar is included among the top collaborators of Suraj Maharjan 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 Suraj Maharjan. Suraj Maharjan 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 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 24 | |
| 6 | 23 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | MPST: A Corpus of Movie Plot Synopses with Tags | 4 |
| 10 | Folksonomication: Predicting Tags for Movies from Plot Synopses Using Emotion Flow Encoded Neural Network | 3 |
| 11 | 2 | |
| 12 | 6 | |
| 13 | CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings | 7 |
| 14 | 33 | |
| 15 | 29 | |
| 16 | Using Wide Range of Features for Author profiling. | 4 |
| 17 | 51 | |
| 18 | 100 | |
| 19 | Machine Translation Evaluation Metric for Text Alignment. | 4 |
| 20 | A Simple Approach to Author Profiling in MapReduce. | 9 |
About Suraj Maharjan
Suraj Maharjan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Transplantation, having authored 33 papers that have together received 857 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (6 papers) and Handwritten Text Recognition Techniques (5 papers). The work is most often cited by research in Materials Chemistry (426 citations), Artificial Intelligence (269 citations) and Linguistics and Language (25 citations). Suraj Maharjan has collaborated with scholars based in United States, China and Mexico. Frequent co-authors include Thamar Solorio, Laijin Lu, Nan Zhou, Shoujun Zhu, Xiaohuan Zhao, Yubin Song, Bai Yang, Junhu Zhang, Hai‐Yu Wang and Lei Wang. Their work appears in journals such as PLoS ONE, Chemical Communications and Nanoscale.
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.