Di Lu
- Ocean Engineering top 1%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Lian LianZheng ZengChengke XiongHeng JiVı́tor CarvalhoLeonardo NevesNing ZhangChenxin Lyu
- Topics
- Underwater Vehicles and Communication Systems (21 papers)Topic Modeling (12 papers)Natural Language Processing Techniques (11 papers)
- Partner nations
- ChinaUnited StatesChile
In The Last Decade
Di Lu
65 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 131
- Ocean Engineering 469
- Artificial Intelligence 382
- Computer Vision and Pattern Recognition 313
- Aerospace Engineering 272
- Control and Systems Engineering 193
Countries citing papers authored by Di Lu
This map shows the geographic impact of Di Lu'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 Di Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Lu more than expected).
Fields of papers citing papers by Di Lu
This network shows the impact of papers produced by Di Lu. 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 Di Lu. The network helps show where Di Lu may publish in the future.
Co-authorship network of co-authors of Di Lu
This figure shows the co-authorship network connecting the top 25 collaborators of Di Lu. A scholar is included among the top collaborators of Di Lu 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 Di Lu. Di Lu 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 | 0 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 26 | |
| 8 | 0 | |
| 9 | 19 | |
| 10 | 27 | |
| 11 | 20 | |
| 12 | Cross-lingual Structure Transfer for Zero-resource Event Extraction | 5 |
| 13 | 99 | |
| 14 | 5 | |
| 15 | Embracing Non-Traditional Linguistic Resources for Low-resource Language Name Tagging | 6 |
| 16 | 1 | |
| 17 | RPI BLENDER TAC-KBP2016 System Description. | 10 |
| 18 | RPI BLENDER TAC-KBP2015 system description | 13 |
| 19 | 1 | |
| 20 | USING FINITE ELEMENT METHOD TO CALCULATE 3D THERMAL DISTRIBUTION IN THE END REGION OF TURBO GENERATOR | 3 |
About Di Lu
Di Lu is a scholar working on Ocean Engineering, Communication and Space and Planetary Science, having authored 74 papers that have together received 1.3k indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (21 papers), Topic Modeling (12 papers) and Natural Language Processing Techniques (11 papers). The work is most often cited by research in Ocean Engineering (469 citations), Computer Vision and Pattern Recognition (313 citations) and Artificial Intelligence (382 citations). Di Lu has collaborated with scholars based in China, United States and Chile. Frequent co-authors include Lian Lian, Zheng Zeng, Chengke Xiong, Heng Ji, Vı́tor Carvalho, Leonardo Neves, Ning Zhang, Chenxin Lyu, Yufei Jin and Caoyang Yu. Their work appears in journals such as Water Research, Communications of the ACM and IEEE Access.
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.