Nan Ye

4.9k citations
189 papers · 3.6k · h-index 28

Impact in

Papers in

Nan Ye

169 papers receiving 3.5k citations

Peers

Nan Ye
Comparison fields: 5 of 181
  • Building and Construction 778
  • Civil and Structural Engineering 1.1k
  • Mechanical Engineering 763
  • Computational Mathematics 12
  • Automotive Engineering 211
Replace Jianchun Li with:
Jianchun Li Australia
Zijun Zhang China
Xin Zhang China
Fei Dai China
Chunwei Zhang China
Jun Wu China
Vivek Patel India
Yang Yu China
Loke Kok Foong Vietnam
Ting Zhang China
Nan Ye relative to Jianchun Li Australia Jianchun Li's profile →
Citations per field
00.5×1.5×
Jianchun Li · 1×
Citations per year

Countries citing papers authored by Nan Ye

Since Specialization
Citations

This map shows the geographic impact of Nan Ye'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 Nan Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan Ye more than expected).

Fields of papers citing papers by Nan Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nan Ye. 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 Nan Ye. The network helps show where Nan Ye may publish in the future.

Co-authors

The 25 scholars most cited alongside Nan Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nan Ye Line = papers co-authored together Nan Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 189 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016308
2 2014237
3 2015224
4 2014220
5 2016170
6 2014167
7
DESPOT: Online POMDP Planning with Regularization
2013152
8 2020135
9 2017113
10 2013111
11 2017111
12 201678
13 201659
14 202051
15 201750
16 201750
17 202144
18 201439
19 201339
20 202038

About Nan Ye

Nan Ye is a scholar working on Electrical and Electronic Engineering, Mechanical Engineering, Materials Chemistry, Artificial Intelligence and Civil and Structural Engineering, having authored 189 papers that have together received 3.6k indexed citations. Recurring topics across this work include Optical Network Technologies (19 papers), Photonic and Optical Devices (18 papers), Advanced Photonic Communication Systems (18 papers), Semiconductor Lasers and Optical Devices (14 papers), Advanced Fiber Laser Technologies (9 papers), Bauxite Residue and Utilization (8 papers), Machine Learning and Algorithms (8 papers) and Reinforcement Learning in Robotics (6 papers). The work is most often cited by research in Building and Construction (778 citations), Civil and Structural Engineering (1.1k citations), Mechanical Engineering (763 citations), Computational Mathematics (12 citations) and Automotive Engineering (211 citations). Nan Ye has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Jiakuan Yang, David Hsu, Bo Xiao, Sha Liang, Wee Sun Lee, Jingping Hu, Xinyuan Ke, Yong Hu, Qifei Huang and John L. Provis. Their work appears in journals such as Journal of Lightwave Technology, Scientific Reports, Optics Communications, Journal of the American Ceramic Society and Metals.

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.

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